the impact of personality, salience, and love of …

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THE IMPACT OF PERSONALITY SALIENCE AND LOVE OF MONEY ON

INVESTMENT DECISIONS

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DISSERTATION

SUBMITTED TO THE DEPARTMENT OF BUSINESS ADMINISTRATION

AND THE COMMITTEE FOR ADVANCED STUDIES AND RESEARCH

OF LAHORE SCHOOL OF ECONOMICS

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

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Samra Chaudary

October 25th 2019

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copy 2019 Lahore School of Economics All rights reserved1

1 The Lahore School of Economics hereby grants to the student permission to reproduce and to publish paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created The reproductionpublication will however carry the Lahore School of Economics copyright

ii

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by

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Samra Chaudary

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Submitted to the Department of Business Administration

on October 25th 2019 in Partial Fulfillment of the

Requirements for the Degree of Doctor of Philosophy

in Business Administration

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Abstract |

This dissertation investigates the impact of Personality Salience and Love of Money

(LoM) on an investorrsquos short-term investment decision (ST-D) and long-term investment

decisions (LT-D) The research of this dissertation falls under the discipline of behavioral

finance and uses Prospect Theory as a theoretical lens A succession of three papers

(models) was written on this theme The first paper has explored the impact of five types

of personality traits on ST-D and LT-D Moreover risk perception has been tested as a

mediator between each personality type and investment decisions The second paper

tested the effect of salience on ST-D and LT-D and it was also tested if the impact of

salience on ST-D and LT-D differed between individual investors and professional

investors Moreover it was also investigated whether the impact of salience on ST-D and

LT-D differed between female investors and male investors The third paper focused on

the effect of LoM on ST-D and LT-D and whether current income and future inheritance

moderated the relationship between LoM and both ST-D and LT-D The data were

collected by 277 individual and professional equity investors investing in Pakistan Stock

Exchange (PSX) The findings of the first paper were that individuals only with

neuroticism and extrovert personalities showed a significant relationship with ST-D

v

However investors with openness conscientiousness and extraversion personality traits

showed an effect on LT-D Risk perception was found to mediate the relationship of

extraversion openness agreeableness and conscientiousness personality traits and LT-

D only The results of the second paper found that salience has a significant positive

impact on both ST-D and LT-D Moreover individual investors and professional

investors were found significantly different from each other Furthermore the parametric

tests of difference between the two groups also showed that path coefficients of female

investors were significantly different from the path coefficient of male investors both for

ST-D and LT-D The third paper found that LoM showed a significant positive impact

on both short-term and long-term investment decisions Furthermore income moderated

the relationship between LoM and ST-D and did not moderate the relationship of LoM

with LT-D The expectation of receiving future inheritance moderated the relationship

between LoM and both ST-D and LT-D The findings of this research have implications

for psychologists economists and finance executives The findings will facilitate money

managers to cultivate a deeper understanding of their clientsrsquo behavior for ST-D and LT-

D Thus it is important that financial advisors include this behavioral aspect in their risk

models to improve the investment plans and decisions for their clients The study has

contributed to the growing body of applied behavioral research in the discipline of

finance especially to the literature on personality risk perception salience and LoM

used by investors while making investment decisions

Keywords personality type risk perception salience love of money short-term

investment decision long- term investment decision

Thesis supervisor Dr Sohail Zafar

Supervisorrsquos Title Professor

vi

Acknowledgments |

|

There are myriad individuals to acknowledge individually everyone who aided

me during this research and from whom I have learned considerably A special thanks

to Dr Shahid Amjad Chaudhry who by providing me with the opportunity to teach set

in motion my enrolment into the PhD program I would like to express my most sincere

gratitude to my supervisor Dr Sohail Zafar for his continuous encouragement and

patient guidance I also want to recognize my committee members Dr Syeda Rabab

Mudakkar and Dr Aamir Khan for providing direction and productive critiques to my

research I thank my teachers and everyone who voluntarily bore with me throughout the

process of my primary research

I also want to acknowledge collectively the colleagues with whom I worked with

the Lahore School of Economics for the last 8 years Contrary to the usual stereotypes

rather than competition the support by my peers who were on the same journey was

unequivocally sincere I am grateful to my best friend Qurat ul Ain for her consistent

support throughout this challenging process and to my uncle Amjad Bhatti who

encouraged me to enroll in the PhD program

Last but not least I thank all of my family including all my siblings Sadia Sidra

Zeenat Huma M Ali M Umar and especially my father Abdul Qadir for the

unconditional support and encouragement to pursue my interests and follow my dreams

I dedicate this work in the loving memory of my deceased mother Shamshad Akhter for

her wise thoughtful and motivational nurturing that kindled passion in me to accomplish

this milestone

vii

Table of Contents

Contents Abstract iv Acknowledgments vi Table of Contents vii List of Tables x

List of Figures xi 1 Introduction 1

11 Introduction 1

12 Research Context 9

13 Research Objectives and Questions 10

14 Key Findings Significance and Contributions 13

15 Organization of the Study 17

2 Paper I The impact of Investorsrsquo Personality and Risk Perception on Investment

Decisions 19 Abstract 19

21 Introduction 20

22 Theory and Hypotheses Development 24

221 Prospect Theory (PT 1979) 24

222 Theory of Planned Behavior (TPB 1991) 26

223 Risk as Feeling Theory (RaF 2001) 27

224 Competing Personality Taxonomies 28

225 Personality Type and Investment Decisions 32

226 Risk Perception and Investment Decisions 35

23 Data and Methodology 41

231 Measures 41

232 Methods 41

24 Results 46

241 Measurement Model 46

242 Structural Model 49

25 Discussion and Implications 56

26 Conclusion and Future Research 62

3 Paper II The Role of Salience in Investment Decisions Differences Between

Individual Investors and Professional Investors 65 Abstract 65

31 Introduction 66

viii


321 Prospect Theory 68

322 Heuristics and Investment Decisions 69

323 Salience and Investment Decision 70

324 Institutional Investors and Salience 74

325 Individual Investors and Salience 75

326 Gender and Salience 77


331 Measures 81

332 Methods 81

34 Results 84



343 Measurement Invariance Assessment 89

344 Multi-group Analysis 92



4 Paper III Love of Money and Investment Decisions Interaction of Income and

Inheritance 102

Abstract 102

41 Introduction 103



422 Theory of Planned Behavior 108

423 Monetary Intelligence (MI) Theory 109

424 Love of Money and Investment Decisions 109

425 Income Inheritance and Love of Money 113


431 Measures 118

432 Methods 119

44 Results 122



443 Moderation Effects of Current Income and Future Inheritance 128


ix

46 Conclusion and Future Research Direction 140

5 Conclusion 142 51 Introduction 142

52 Key Findings 143

53 Theoretical Implications 145

54 Practical Implications 148

55 Research Limitations and Future Research Directions 151

References 154

Appendices 207 Appendix I Supporting Literature for Relationships of Paper 1 207

Appendix II Supporting Literature for Relationships of Paper 2 209

Appendix III Supporting Literature for Relationships of Paper 3 212

Appendix IV List of Financial Institutions 214

Appendix V Paper 1 Structural Models (Mediation) 215

Appendix VI Questionnaire 220

x

List of Tables

Table 21 Summary of Personality Taxonomies 30 Table 22 Alignment Among the three main Five-Factor Models 32 Table 23 Descriptions of the Big-Five Personality Traits 33 Table 24 Inter factor Correlations and Square root of Average Variance Extracted 46 Table 25 Results of Measurement Model 48

Table 26 Convergent Validity and Construct Reliability of Constructs 49 Table 27 Heterotrait-Monotrait (HTMT) Ratio of Correlations 49 Table 28 Results of Total Effects of Personality Traits on ST-D and LT-D 52 Table 29 Mediation Results of Risk Perception 55

Table 31 Inter factor Correlations and Square root of Average Variance Extracted 84 Table 32 Results of Measurement Model 86

Table 33 Convergent Validity and Construct Reliability of Constructs 86 Table 34 Heterotrait-Monotrait (HTMT) Ratio of Correlations 86 Table 35 Results of Direct Effects of Salience on ST-D and LT-D 88

Table 36 Measurement Invariance of Composite Model of Individual Investors and

Professional Investors 91

Table 37 Measurement Invariance of Composite Model of Female Investors and Male

Investors 91 Table 38 Direct Effects for Professional Investors and Individual Investors 93

Table 39 MGA Results of Professional Investors and Individual Investors 93 Table 310 Direct Effects for Males and Females 94

Table 311 MGA Results of Males and Females 94

Table 41 Inter factor Correlations and Square root of Average Variance Extracted 122

Table 42 Results of Measurement Model 125 Table 43 Weights and Variance Inflation Factor of Constructs 126

Table 44 Convergent Validity and Construct Reliability of Constructs 126 Table 45 Heterotrait-Monotrait (HTMT) Ratio of Correlations 126 Table 46 Results of Direct Effects of LoM on ST-D and LT-D 128 Table 47 Moderation Results 131

xi

List of Figures

Figure11 The value function of prospect theory by Kahneman and Tversky (1979) 7 Figure 12 Yearly performance of PSX-100 since inception 10 Figure 21 Structural model about the relationships of five personality types with short-

term investment decisions with mediation by risk perception 40 Figure 22 Structural model about the relationships of five personality types with long-

term investment decisions with mediation by risk perception 40 Figure 31 Structural model about the relationship of Salience with short-term and

long-term investment decisions 80 Figure 41 Structural model about the relationship of Love of Money with short-term

and long-term investment decisions with the moderating effects of income and expect

to receive the future inheritance 118 Figure 42 The moderating effect of income on the relationships between LoM and

short-term investment decision The above illustration shows income at mean one

standard deviation above the mean (ie high-income) and one standard deviation

below the mean (ie low-income) 132 Figure 43 The no-moderating effect of income on the relationships between LoM and



below the mean (ie low-income) 132

Figure 44 The moderating effect of expectation of receiving inheritance on the

relationships between LoM and short-term investment decision 133 Figure 45 The moderating effect of expectation of receiving inheritance on the

relationships between LoM and Long-term investment decision 133

Figure 23 Structural model of the mediating effect of risk perception between

neuroticism and short-term investment decision 215 Figure 24 Structural model of the mediating effect of risk perception between

extraversion and short-term investment decision 215 Figure 25 Structural model of the mediating effect of risk perception between

openness and short-term investment decision 216


agreeableness and short-term investment decision 216 Figure 27 Structural model of the mediating effect of risk perception between

conscientiousness and short-term investment decision 217 Figure 28 Structural model of the mediating effect of risk perception between

neuroticism and long-term investment decision 217


extraversion and long-term investment decision 218 Figure 210 Structural model of the mediating effect of risk perception between

openness and long-term investment decision 218 Figure 211 Structural model of the mediating effect of risk perception between

agreeableness and long-term investment decision 219 Figure 212 Structural model of the mediating effect of risk perception between

conscientiousness and long-term investment decision 219

Introduction

1

1 Introduction

11 Introduction

Onersquos life is full of risky decisions from ordinary routine matters of daily life to matters

of life or death Individuals persistently face circumstances that require them to decide

between actions that differ in the level of risk (Riaz amp Hunjra 2016) Individual investors

and money managers are often confronted with risky decision-making choices as they are

expected to make decisions by taking into account the perceived levels of risk (Epstein

1994) An individualrsquos financial decision-making is a key factor for hisher long-term

financial wellbeing (Imasheva amp Kim 2017 Tang et al 2018a) Therefore it is important

to understand which factors influenced investorsrsquo financial decisions (Keller amp Siegrist

2006b) Decisions are a function of many constraints such as task structure the decision

makers cognitive representation of the task and the decision makers information

processing capabilities The process of decision-making has been investigated by many

disciplines eg economics statistics psychology philosophy and management science

Psychologists seemed to believe that they can best contribute to decision research by

exposing the psychological processes underlying judgment and choice They have tried to

place behavioral decision theory within a broader psychological context and have focused

on the significance of memory cognition conflict learning and feedback as relevant

factors that affect decision-making (Einhorn amp Hogarth 1981)

Individuals make investment decisions to save earnings for retirement (Clark-Murphy

amp Soutar 2004 Dreman Johnson MacGregor amp Slovic 2001) education expenses and

health care expenditures (Greenberg amp Hershfield 2019) Another reason for an

investment decision is the individualrsquos desire for making profits and increasing their capital

Samra Chaudary

2

(Keller amp Siegrist 2006a) Moreover 1) deregulations of financial services 2) social

security cuts and 3) tough economic conditions are also likely reasons for individuals to

invest (Gunnarsson amp Wahlund 1997) In this era of concern for retirement savings

employees try to understand how much to save where to invest and how to make lump-

sum payouts (McKenzie amp Liersch 2011) Consequently individuals all over the world

are facing more complex investment decisions than in the past (Imasheva amp Kim 2017

Shih amp Ke 2014)

The development of asset markets has offered more varied opportunities to invest in

several financial instruments (Lim et al 2013) These financial instruments have different

time horizons ie short and long The attractiveness of an investment strategy is

significantly determined by the investment horizon (Dierkes Erner amp Zeisberger 2010)

Attitudes towards investment horizon may vary across individuals and may depend on

different behavioral factors (Warren 2014) Some of those are investigated in this

dissertation According to Pennings Candel amp Egelkraut (2003) financial institutions

need new knowledge in order to develop new financial products or to improve the existing

ones Hence a better understanding of the short-term or long-term investment choice

process of the client is crucial for investors themselves as well as for financial institutions

involved in developing financial instruments for investors

An Individualrsquos decisions to invest in a firmrsquos securities are not merely driven by the

fundamentals of a firm (De Vries Erasmus amp Gerber 2017) but are prominently

influenced by psychological and behavioral factors related to investors such as personality

emotions (Szyszka amp Zielonka 2007 Akerlof amp Schiller 2009 Kahneman 2012 Tauni

Fang amp Iqbal 2016) attitude towards money (Keller amp Siegrist 2006a b) desire for

Introduction

3

immediate gratification (Warren 2016) locus of control (McInish 1982) attitude toward

saving (Euwals Eymann amp Boumlrsch-Supan 2004) risk attitudes (Morse1998 Tigges

Riegert Jonitz Brengelmann amp Engel 2000 Warneryd 2001) overconfidence and

behavioral biases (Baker amp Ricciardi 2014 Keller amp Siegrist 2006a Kiyilar amp Acar

2009 Kourtidis Sevic amp Chatzoglou 2011 Pompian 2012) The identification of

investorsrsquo related factors that hinder or stimulate their decision to make investments is of

high relevance (Keller amp Siegrist 2006a) Overlooking such important factors may have

severe negative effects on investment returns (Baker amp Ricciardi 2014) Therefore it is

argued that the behavioral aspect of an investor is relevant in devising effective strategies

by financial planners for their clientsrsquo wealth management

Investors sometimes behave irrationally in some of their investment decisions (Baker

amp Ricciardi 2014 De Bondt amp Thaler 1985 Kahneman amp Tversky 1979 Keller amp

Siegrist 2006a) Traditional financial models are unable to explain such irrational but real

behavior of investors (Firat amp Fettahoglou 2011) Behavioral finance models are deemed

more suitable to explain investor behavior that results in market anomalies because rational

models of conventional finance fail to explain such anomalies (Glaser Langer Reynders

amp Weber 2007) Previous studies on peoplersquos investment decisions were based on the

assumptions of modern finance theories (Black amp Scholes 1973 Markowitz 1952

Modigliani amp Miller 1958) Conventional finance theories assume that investors are

rational and want to maximize their profit for a certain level of risk However conventional

finance theories have been criticized both on the basis of their lack of explanatory power

and the validity of their assumptions (Takahashi ampTerano 2003) Yalcin Tatoglu and

Zaim (2016) have identified two bases of conventional finance theories firstly these

Samra Chaudary

4

theories assume that during the decision-making process humans behave rationally as

defined by the expected utility theory (EUT) secondly these theories advocate that

financial markets are efficient (rational) in a way that they reflect the accurate prices of

securities the so-called Efficient Market Hypothesis (EMH)

Efficient Market Hypothesis (EMH) stated that in an efficient market all the

available information is reflected in the observed current prices of financial assets The

assumptions of a perfect market are that there are no taxes no inflation no information

asymmetry no transaction cost no bankruptcy cost and investors are rational According

to EMH investors make rational decisions in the financial market and it would be

impossible for an investor to beat the market consistently on a risk-adjusted basis There

are three forms of EMH which are the weak form the semi-strong form and the strong

form In Weak form prices of financial assets reflect market-level data (price and volume)

In semi-strong form current prices of financial securities reflect market-level data and

publicly available data However in the strong form of EMH prevailing prices of the

securities reflect publicly as well as privately available data Hence as level of information

increases market becomes more efficient (Fama 1970)

However in decision-making investors have to take one course of action among

several uncertain investment alternatives However various studies (Black 1986 De

Bondt amp Thaler 1985 Warneryd 2001) detected so-called ldquoanomaliesrdquo in the returns that

were not explained by the EMH and rational models of portfolio choice Yalcin et al (2016)

have explained that both conventional finance and behavioral finance propose different

interpretations to explain the causes of observable market anomalies The advocates of

conventional finance claim that the anomalies can be explained by chance or by the

Introduction

5

presence of methodological errors In contrast advocates of behavioral finance claim these

anomalies are explainable through behavioral biases (Kliger amp Kudryavtsev 2010 Sahi

Arora amp Dhameja 2013)

The term expected utility was first introduced by Bernoulli (17381954) The

expected utility theory deals with the decision-making under the condition of uncertainty

ie when individuals are unaware of the outcome of the decision Expected utility theory

postulates that investors behaved rationally and tried to maximize their utilities by

evaluating all the investment alternatives and they restrict their feelings and they decide

only by using their brains as a super calculator or as emotionless robots Investors choose

between risky or uncertain prospects by calculating the utility of each decision outcome

multiplied by its probability to arrive at an expected value Friedman and Savage (1952)

had proposed that decision-makers look for maximum utility in all outcomes whereas

utility was generally defined as a degree of happiness satisfaction or contentment

Conventional finance theory was first questioned by Simon (1955) who argued that

individuals have bounded rationality and their actions are constrained by mental and

external restrictions which limit their rationality Slovic Fischhoff and Lichtenstein

(1977) also argued that because of limited information processing ability and not knowing

the guidelines of optimal information processing decision makerrsquos judgment is subject to

systematic biases The idea of limited rationality provided the foundation for the discipline

of behavioral finance as many researchers encountered counter-evidence against the

validity of rational decisions (De Bondt amp Thaler 1985 Kahneman amp Tversky 1979

Shleifer amp Summers 1990) These researchers concluded that in real-life decision-making

situations individuals were subject to some cognitive limitations

Samra Chaudary

6

The area of behavioral finance recognizes the importance of human behavioral

biases which plays a significant role in economic decisions made by individuals The field

picked up pace when Kahneman and Tversky (1979) proposed prospect theory and got

further recognition when three Nobel Prizes were awarded to behavioral economists

namely Daniel Kahneman in 2002 Robert Schiller in 2006 and most recently Richard

Thaler in 2017 Prospect theory by Kahneman and Tversky (1979) laid the foundation for

the discipline of behavioral finance It proposes that investorsrsquo decision-making is based

on the potential value of gains and losses rather than on actual value of gains and losses

This phenomenon occurs due to cognitive biases that affect the judgment about these gains

and losses Prospect theory assumes that the value function is a concave function in the

area of gain and thus risk-averse and is a convex function in the area of loss and thus risk-

taking Additionally the gradient of the value function is generally steeper in the area of

loss than in the area of gain which infers that a loss would have a larger effect (cause more

pain) on the decision-maker than a gain (would cause happiness)

In prospect theory the outcomes are estimated on the basis of the deviance from

the reference point which symbolizes the psychological origin the decision-maker assesses

the outcomes either as a gain or loss Moreover prospect theory suggests that decision-

makers estimate a gain as risk-aversion and a loss as risk-taking Even the identical problem

demonstrates risk-aversion behavior when the alternatives are shown in the area of gain it

also shows risk-taking behavior in the area of loss

According to prospect theory the value function is a concave function (a function

that is concave downward) in the region of gain which is above the reference point and

the function is convex (a function that is convex downward) in the region of loss which is

Introduction

7

below the reference point as shown in figure 11 This shows that the decision-makers show

risk-averse actions in the area of gain and risk-taking actions in the area of a loss

Figure11 The value function of prospect theory by Kahneman and Tversky (1979)

Kahneman and Tversky (1979) conducted a survey among faculty and students in

Israeli American and Swedish universities Subjects were given the following similar

problems as stated in Takemura (2014) To clarify this findings of their results are given

below

Problem 1 Which one of the following alternatives is preferred to the other

A a gain of $4000 with a probability of 80 (Prospect A = (4000 080)

B a certain gain of $3000 (Prospect B = (3000 100)


C a loss of $4000 with a probability of 80 (Prospect C = (-4000 080)

D a certain loss of $3000 (Prospect D = (-3000 100)

Samra Chaudary

8

For Problem 1 20 of 95 respondents selected A 80 preferred B Regarding Problem

2 92 of 95 respondents preferred C 8 opted for D This pattern of the majority

selection was consistent with the propositions of prospect theory that decision-makers are

risk-averse in the area of gain and risk-takers in the area of loss

The above example can further be clarified that in case of gains a big majority of

respondents (80) showed a preference for definite gains while only 20 of respondents

expressed the preference for probabilistic gains although the probabilistic gains were

higher Therefore they concluded that in case of gains respondents showed risk-averse

behavior Furthermore in the case of losses 92 of respondents chose probabilistic losses

while only 8 chose definite losses though probabilistic losses were higher Therefore

they showed preference for risk-taking which is an irrational behavior

The discipline of behavioral finance links the knowledge of finance and behavioral

decision-making The discipline discusses how investors think feel behave and decide

about their investments The subject also includes the awareness of psychological

processes that determine the decision-makersrsquo choices as well as systematic biases that

investors have and heuristics that investors use when making decisions Behavioral finance

emerged as a new discipline linking behavioral and psychological perspectives in economic

and financial decision-making in the 1980s (Kumar amp Goyal 2015) The field is emerging

within the broader context of economics and finance and has close interaction with both

psychology and sociology (Puustinen Maas amp Karjaluoto 2013 Shiller 2003

Subrahmanyam 2008) Shariff Al-Khasawneh and ElSharif (2012) conducted a survey

on university students in the Persian Gulf countries and found that respondents were not at

all familiar with behavioral finance or neuroscience concepts Riepe (2013) has

Introduction

9

emphasized that the future of behavioral finance is bright Huang Shieh and Kao (2016)

research based on ISI Web of Science (WOS) database searched from 1995 to 2013

covering 124 journals found that research papers in the area of behavioral finance are

increasing making it a significant area of study With the dynamic development of

financial markets more and more researchers are using behavioral finance as their research

paradigm

12 Research Context

Capital markets play an important role in any countryrsquos economic health Respondents

of this study were the active traders in the equity market Pakistan Stock Exchange (PSX-

100) was founded in 1991 and is the largest and most liquid stock index of Pakistan As of

February 23rd 2018 the market capitalization of PSX-100 was US$ 84 billion with an

average daily trading volume of US$95 billion There were 559 listed companies from 35

sectors From a population of almost 208 million (Pakistan Bureau of Statistics 2017)

there were only approximately 0248 million investors (including institutional and retail)

who were actively participating in the stock market This was barely 125 percent of the

countryrsquos population Out of the total investorsrsquo population (corporate and individual) of

the country Karachi has 74 percent investors Lahore has 18 percent and Islamabad has 8

percent investors (Central Depository Company 2018) Khwaja and Mian (2005) argued

that KSE-100 index depicts the typical attributes of an emerging market such as soaring

returns with extreme volatility low market capitalization but with large trading volumes

and high kurtosis in the returns distribution In 2002 for instance KSE-100 was announced

as the outperforming index in the world in terms of the percentage increase Consequently

the status of PSX was upgraded to Emerging Markets from Frontier Markets by Morgan

Samra Chaudary

10

Stanley Capital International (MSCI) in June 2016 According to the managing director of

IMF emerging economies contribute almost 60 percent of global GDP (Lagarde 2016)

This announcement anticipated more capital inflows from international markets indicating

brighter future prospects for PSX (Jabeen 2016) Figure 12 shows an overall upward trend

of yearly returns of PSX-100 since its inception

Kumar and Goyal (2015) proposed that future research in the discipline of behavioral

finance should concentrate on emerging stock markets as developing economies have

higher growth prospects It was also proposed that attention should be given to research

based on primary data to analyze the behavior of investors

Figure 12 Yearly performance of PSX-100 since inception

Source wwwpsxcompk

13 Research Objectives and Questions

This study is built on the notion that behavioral factors have an influence on the

decision-making process of investors The key objective of this dissertation is to investigate

Introduction

11

the effect of behavioral factors namely personality type of investors salience (familiarity

bias) and investorsrsquo love of money on their investment decisions In this sense this study

essentially aims at testing the Prospect Theory in many ways in the context of a developing

economy

There is a dearth of literature on the impact of Big-Five personality traits salience

(familiarity bias) and love of money on short-term and long-term investment decisions

There are numerous studies on the aforementioned three behavioral factors and their impact

on decision-making from developed economies (Ahearne Griever amp Warnock 2004

Belk amp Wallendorf 1990 Brunell amp Buelow 2017 Carnavale Inbar amp Lerner 2011

Coval amp Moskowitz 1999 Gentina Tang amp Gu 2018 Hampson Grimes Banister amp

McGoldrick 2018 Hirshleifer 2001 Keller amp Siegrist 2006a Lim amp Teo 1997

Mayfield Perdue amp Wooten 2008 Nicholson Soane Fenton‐OCreevy amp Willman

2005 Oehler Wendt Wedlich amp Horn 2018 Oehler amp Wedlich 2018 Satchell Bacon

Firth amp Corr 2018 Sekścińska Rudzinska-Wojciechowska amp Maison 2018 Tang 2016

1992 Tversky amp Kahneman 1986 1981 Tung amp Baumannb 2009 Vitell Singh amp

Paolillo 2007 Wang Keller amp Siegrist 2011 Weber amp Milliman 1997 Weber Blais amp

Betz 2002 Yalcin et al 2016) But research in the context of developing economies is

still relatively sparse (Bhardwaj amp Bhattacharjee 2010 Carol amp Samsinar 2011 De Vries

et al 2017 Jaiswal amp Kamil 2012 Li Jiang An Shen amp Jin 2009 Li amp Liu 2008

Metawa Hassan Metawa amp Safa 2019 Modesto Veludo-de-Oliveira Augusto Falciano

amp Villas Boas Perito 2014 Pak amp Mahmood 2015 Riaz amp Hunjra 2016 Tripathi amp

Chattopadhyay 2013)

Samra Chaudary

12

To the best of our knowledge there is scant empirical evidence on the primary research

question of the study and none in the emerging economy In order to accomplish the

research objective a number of following research questions have been developed 1a) Do

five personality types have an effect on short-term and long-term investment decisions

1b) Does risk perception mediate the relationship between personality types and short-term

and long-term investment decisions 2a) Does salience (familiarity bias) have an impact

on short-term and long-term investment decisions 2b) Whether the impact of salience on

short-term and long-term investment decisions differs between individual investors and

professional investors 2c) Whether the impact of salience on short-term and long-term

investment decisions differs between female investors and male investors 3a) What is the

relationship between Love of Money and short-term and long-term investment decisions

3b) Whether current income moderates the relationship of Love of Money and short-term

as well as long-term investment decisions 3c) Whether future inheritance moderates the

relationship of Love of Money and short-term as well as long-term investment decisions

It is crucially important to analyze investorsrsquo intentions (such as short-term vs long-

term) about investment and why they manage the investment in different ways If those

investment intentions are evident then researchers and financial advisors would be

interested to learn if those intentions are adaptable (Mayfield et al 2008) It has become

vital to recognize the spur of decision-making behavior of investors Such knowledge is

likely to be helpful for financial counselors to target investors correctly and communicate

with these investors more effectively (Wood amp Zaichkowsky 2004)

Introduction

13

14 Key Findings Significance and Contributions

The key findings of three papers are summarized in the following paragraph The

results of first paper are that investors only with neuroticism and extrovert personality traits

showed a significant positive relationship with ST-D However individuals with openness

conscientiousness and extraversion personalities showed a significant positive relationship

with LT-D Risk perception was found to mediate the relationship of extraversion with LT-

D openness with LT-D agreeableness with LT-D and conscientiousness personality trait

with LT-D There was no mediating effect of risk perception between relationship of five

personality types and ST-D The findings of the second paper are that salience has a

significant positive impact on both ST-D and LT-D Moreover individual investors and

professional investors were found significantly different from each other with respect to

impact of salience on decision making behavior both ST-D and LT-D Furthermore the

moderating effect of gender in relationship between salience and investment decision

showed that the path coefficients of female investors were significantly different from the

path coefficient of male investors both for ST-D and LT-D It was found that female

investors suffered more from salience bias than male investors In the third paper it was

found that LoM had a significant positive impact on both ST-D and on L-TD Moreover

income moderated the relationship between LoM and ST-D but did not moderate the

relationship of LoM with LT-D Paper three also tested moderating effect of inheritance

expectation on relationship between LoM and investment decisions The expectation of

receiving future inheritance was found to moderate the relationship between LoM and ST-

D as well as the relationship of LoM with LT-D

Samra Chaudary

14

The significance of these studies enhances the understanding of irrationality in

investment decision making Behavioral biases are inseparable from individualsrsquo decision-

making and can reasonably be understood with the lens of behavioral finance (Barberis amp

Thaler 2003) The complexity of irrational decisions by investors creates new challenges

for portfolio managers whose job is to manage their clientrsquos wealth Therefore the

knowledge of behavioral factors is imperative for the financial institutions and financial

planners to ensure that their customers are obtaining appropriate guidance Such findings

can also help professionals in recognizing the behaviors of clients and accordingly advise

them for short-term and long-term financial goals (Baker Filbeck amp Ricciardi 2017) The

understanding of behavioral factors operative in investors decision-making is likely to aid

managers to communicate better with their clients (Muradoglu amp Harvey 2012)

Moreover understanding of an investorrsquos behavior is likely to assist managers in assessing

how optimistic overconfident and risk-averse their specific clients are (Kahneman amp

Riepe 1998)

This research has made contributions in multiple forms Firstly as discussed

above investigating this area of finance is itself a theoretical contribution because the

paradigm is still young and emerging and needs more evidence from developing economies

to have more generalizable knowledge about the behavioral factors influencing investment

decision-making Secondly many other studies have used student samples (from a finance

course) as proxy for potential investors in the field of behavioral finance (Filbeck Hattield

amp Horvarth 2005 Lemrova Reiterova Fatenova Lemr amp Tang 2014 Li amp Liu 2008

Mayfield et al 2008 Oehler et al 2018 Wood amp Zaichkowsky 2004) but this study

collected responses from actual real-life investors It was also proposed that attention

Introduction

15

should be given to empirical research which should be based on primary data to analyze

the behavior of investors (Kumar amp Goyal 2015) This study has made a methodological

contribution by using primary data collected from actual investors instead of student

sample Thirdly this study has aimed to bridge the empirical gap between behavioral

factors and investment decisions To the best of our knowledge there have been no

research studies about the impact of Big-Five personality traits salience and love of money

on short-term and long-term investment decisions This was correct both in the context of

developing andor developed economies hence provides contextual contribution Fourthly

this study has extended the general model of prospect theory the theory of planned

behavior risk as feeling theory and monetary intelligence theory to another domain of

social behavior that is financial investment and has offered implications for understanding

behavior of individual investors and professional financial managers in the context of a

developing economy And lastly given the importance of these theories in the field of

social behavior the findings of this study also deliver interdisciplinary contributions

The novel findings of this research provide significant and meaningful

contributions to the emerging behavioral finance paradigm and offer practical implications

for financial institutions professional money managers individual investors and

regulatory authorities This research offers practical implications for individual investors

themselves and for professional financial managers In light of this study individual

investors can enhance knowledge of their own preferences and professional managers can

gain better understandings of their clientsrsquo preferences Such enhanced understanding is

expected to facilitate investment decision-making in a more meaningful manner

Investment advisors help their clients in investing money They must understand what is

Samra Chaudary

16

important to their customers in order to guide them and fulfill their clientsrsquo needs

commendably It may also be useful for advisors to identify potential investors based on

personality type risk perception familiarity bias money attitudes current income and

future wealth possession to segment the client accordingly and to develop suitable

investment strategies based on such segmentations

This research also contributes to the knowledge of the psychology of choices made by

investors in an emerging market By such enhanced insights market inefficiencies and

anomalies are likely to be better understood Financial planners may find useful strategies

to exploit numerous behavioral anomalies present in the financial markets Financial

managers from brokerage houses mutual fund companies and other financial institutions

may deliver a superior product service and targeted guidance to their customers once they

understand their clientsrsquo behavior which can influence their investment decisions

Investors should be mindful that familiarity bias sometimes could lead to

undiversified and sub-optimal portfolio building Hence acknowledging the presence of

such bias can help avoid sub-optimal diversification To avoid pitfalls of familiarity bias

financial planners would be well advised to communicate to investors that they should have

a long-term diversification plan with the aim of risk reduction and higher expected return

in their investment portfolios (Baker amp Ricciardi 2015)

For an emerging market like Pakistan raising fresh equity capital from investors is

paramount in its importance to attain economic growth Successfully strategies of targeting

investors are likely to bring more money in the market boost investments in the economy

and strengthen investorsrsquo confidence in the country increase market capitalization

maintain sustainability in the market keep the market competitive and eventually help the

Introduction

17

market to move towards efficiency To conclude this research offers a brand new and

novel perspective and adds to the behavioral finance literature by investigating personality

salience bias and LoM as antecedents of short-term and long-term investment decisions

The theoretical models reveal novel and counterintuitive findings and help us understand

not only the what how and why factors contributing to short-term and long-term

investment decisions but also who where and when

15 Organization of the Study

This dissertation is divided into five chapters The first chapter introduces the

discipline of behavioral finance and behavioral factors affecting investorsrsquo investment

decisions This chapter also presents research objectives research questions and

significance and contribution of this research in the context of developing economy

The second chapter examines the relationships between five personality types and

investment decisions It further explores the mediation of risk perception between each

type of personality and investment decisions The results indicate that individuals only with

neuroticism and extrovert personalities show a significant relationship with ST-D

However all personality types except neuroticism and agreeableness show an effect on

long-term investment decision Moreover risk perception is found to mediate relationships

between the four personality types and LT-D only

The third chapter explores the pertinence of salience as a heuristic with respect to

investment decisions This relationship is further explored by examining the group

differences between individual investors and professional investors and between female

investors and male investors Data has been analyzed through partial least square based

structural equation modeling (PLS-SEM) approach measurement invariance test and

Samra Chaudary

18

multi-group analysis Results indicate that salience has a significant positive effect on both

short-term and long-term investment decisions Furthermore the impact of salience on

short-term and long-term investment decisions is significantly different for individual

investors and professional investors as well as for female investors and male investors

The fourth chapter explores the relationship of Love of Money (LoM) with short-

term and long-term investment decisions This relationship is further explored by

examining the moderating effect of current income and the expectation of receiving future

inheritance The study finds that LoM has a significant positive impact on both short-term

and long-term investment decisions Furthermore it is found that current income moderates

the relationship between LoM and ST-D and does not moderate the relationship of LoM

with LT-D Future inheritance moderates the relationship between LoM and both short-

term and long-term investment decisions

The fifth chapter presents a conclusion by elucidating the major research findings

and underscoring theoretical and managerial implications of the results of the research

questions raised in this study Especially this section highlights the contributions to the

growing body of applied behavioral finance area It also emphasizes the contribution to the

literature on personality types heuristics and LoM This chapter also provides a way

forward by identifying limitations and offering future research directions in the field of

behavioral finance

Personality and Investment Decisions

19

2 Paper I The impact of Investorsrsquo Personality and Risk

Perception on Investment Decisions

Abstract

Investigating behavioral psychological influences in the area of finance is relatively

a new phenomenon and the subject is of interest to economists psychologists professional

money managers and individual savers and investors This paper has taken a behavioral

approach to unveil the psychological predictors of long-term and short-term investment

decisions The paper has used the theory of planned behavior (TPB 1991) and Risk as

Feeling (RaF 2001) theory as a conceptual lens to discover the factors influencing

individualsrsquo investment intentions in the Pakistan Stock Exchange The study used partial

least square based structural equation modeling technique on a data gathered from 277

active equity traders that included professional money managers brokers and individual

traders It was found that individuals with relatively higher neuroticism and extraversion

personality traits were found more likely to do short-term investment decision However

investors with relatively higher openness conscientiousness and extraversion personality

traits were found more likely to do long-term investment decision Investorsrsquo risk

perception was found to mediate effect between the relationships of extraversion openness

agreeableness and conscientiousness personality traits and long-term investment

decisions These findings have implications for psychologists economists and finance

executives as it was found that investorsrsquo personality traits influenced their investment

decisions It is recommended that financial managers should include the influence of these

behavioral aspects in their investment plans advice and decisions for their clients These

findings are expected to contribute to the growing body of knowledge in the area of applied

Samra Chaudary

20

behavioral research within the discipline of finance and these findings in the context of a

developing economy also make this study a first in this line of research stream

Keywords personality type risk perception investment decision behavioral finance

21 Introduction

Decision-making is a skill (Hastie amp Dawes 2010) and onersquos life is full of risky

decisions (Satchell et al 2018) ranging from an ordinary matter to matters of life or death

Individuals frequently face circumstances in which they have to decide between actions

whose outcomes are uncertain and that vary in level of risk (Riaz amp Hunjra 2016) The

fact has long been established that all decisions made by business managers (about cash

flows) may not positively affect the performance of companies because managers may not

necessarily work towards shareholdersrsquo wealth maximization the so-called agency

problem (Jensen amp Meckling 1976) Business managers and financial managers are often

confronted with decision-making choices that are risky and based on the risk analysis they

make decisions by taking into account the identified risks levels (Epstein 1994)

Individuals financial (saving) decisions are influenced by construal Construal is described

as an individualrsquos cognitive illustrations of goals and is a way individuals use their minds

A high-level of construal mentality would lead to more willingness to save than a low-level

construal mentality (Rudzinska-Wojciechowska 2017)

Individuals invest in stocks to increase their capital and profits (Keller amp Siegrist

2006a) Another reason for investing in the stock market is the desire to save their earnings

for retirement (Clark-Murphy amp Soutar 2004 Dreman et al 2001) Since investments in

stocks are risky therefore just like professional money managers individual investors also

have to incorporate risk in their decision-making


21

The development of financial markets has offered more varied opportunities to

invest in several financial instruments (Lim et al 2013) Investors look for better

investment alternatives and financial institutions as professional money managers for

investors need to understand the preferences of investors for different financial

instruments and for different time horizons and for different risk perceptions Investment

in financial instruments entails commitment for different time horizons ie short-term

(ST-D) and long-term investment decisions (LT-D) Individualsrsquo attitudes towards either

of these two-time horizons for investments may vary and such variations may be a result

of investors different personality traits and different risk perceptions

According to Pennings et al (2003) financial institutions need information about

clientsrsquo preferences to develop a new financial product or to improve the existing ones

Hence a better understanding of the short-term or long-term investment choice process of

client is crucial for financial institutions and professional money managers Dierkes et al

(2010) analyzed the attractiveness of different investment strategies for different time

horizons They found that the preference of the investment strategy was significantly

determined by the length of the investment horizon A bond strategy was desired for the

short horizon while stocks were preferred for longer horizons

Lakshmi Visalakshmi Thamaraiselvan and Senthilarasu (2013) suggested that

with long-term investment horizon investors are not likely to make frequent withdrawals

and consequently market volatility would tend to decrease if the majority of investors had

long-term investment horizon Investors are likely according to this view to earn extra

profits when they hold their funds in the same instrument for a longer time In this era of

retirement savings employees face challenges to understand how much to save

Samra Chaudary

22

periodically and where to invest such savings for long-term post-retirement benefits

(McKenzie amp Liersch 2011)

The importance to analyze individualsrsquo intentions about investment goals and why

they manage the investment in different ways cannot be over-emphasized If those

investment intents are evident then researchers and financial advisors would find it easier

to adapt their advice accordingly to their clients (Mayfield et al 2008) It has become vital

to realize the spur of decision-making behavior of investors Such knowledge is likely to

be helpful for financial counselors to target investors correctly and communicate more

appropriately to these investors more effectively (Wood amp Zaichkowsky 2004)

Studies on individualsrsquo investment intentions were mostly based on the

assumptions of modern finance theory that operate within the paradigm of rationality

(Black amp Scholes 1973 Markowitz 1952 Modigliani amp Miller 1958) The conventional

theory proposes that investors are rational and want to maximize their profit for a certain

level of risk and have a clear understanding of their risk preferences

Fama (1998) is a strong supporter of an efficient market and his answer is a solid

lsquonorsquo for market inefficiency because he believes that the presence of observed long-term

return anomalies is sensitive to statistical models which used to discover such anomalies

otherwise investors behave rationally Fama (1998) seems to propose that anomalies have

a tendency to show minimal or no effect when exposed to different statistical approaches

to measure expected (normal) returns This line of argument can conclude that most long-

term return anomalies can realistically be recognized as a chance event and therefore in

the long run investors behavior may be viewed as rational


23

Another viewpoint emphasizes the fact that in reality individualsrsquo decision-

making process is significantly shaped by psychological factors such as personality types

emotions and moods (Akerlof amp Schiller 2009 De Bondt amp Thaler 1985 Kahneman

2012 Shleifer amp Summers 1990 Szyszka amp Zielonka 2007) and therefore their decision-

making process cannot be assumed to follow strict rationality presumed in conventional

theories of economics and finance An individualrsquos position between the two extremes of

a continuum ranging from risk aversion to risk-seeking was thought as a function of hisher

personality traits (MacCrimmon amp Wehrung 1990)

There are numerous studies on behavioral factors and decision-making from

developed economies (Brunell amp Buelow 2017 Carnavale et al 2011 Mayfield et al

2008 Nicholson et al 2005 Oehler et al 2018 Oehler amp Wedlich 2018 Satchell et al

2018 Sekścińska et al 2018 Weber amp Milliman 1997 Weber et al 2002) but only

handful studies from the developing economies (Ahmad Hassan Mahmood amp Aslam

2016 Jaiswal amp Kamil 2012 Li amp Liu 2008 Pak amp Mahmood 2015 Riaz amp Hunjra

2016 Tripathi amp Chattopadhyay 2013 Verma 2008)

To the best of our knowledge there are no studies that have examined the impact

of Big-Five personality traits on short and long-term investment decisions with the

mediation of risk perception in both developed and developing economies (see appendix

I) Previous studies have only considered a few personality types (Mayfield et al 2008

Oehler et al 2018 Oehler amp Wedlich 2018) and tested the mediation of risk perception

in relationship between information asymmetry and investment decisions (Riaz amp Hunjra

2016) and between heuristics and investment decisions (Ishfaq Maqbool Akram Tariq

amp Khurshid 2017) This study however aims to cater to the absence of empirical studies

Samra Chaudary

24

in the discipline by modeling the missing link of risk perception as a mediator between

relationships of all Big-Five personality types and investment decisions

This study provides a significant and meaningful theoretical contribution to the

prevailing young and emerging finance paradigm The study has tried to provide the

desired evidence from the developing economy by using a unique data set of professional

money managers and individual investors who have invested in the Pakistan Stock

Exchange It has investigated if the personality traits of these investors have a significant

effect on decision- making and if risk perception mediates the relationship between the

personality trait and horizon of their investment decision

22 Theory and Hypotheses Development

Traditional (standard) financial theories have been disparaged for the lack of their

explanatory power and their grounded assumptions (Takahashi amp Terano 2003) Yalcin et

al (2016) criticized the two main propositions of traditional finance theory The first

proposition supposes that humans behave rationally during the decision-making process as

defined by the expected utility theory (EUT) whereas the second proposition advocates that

financial markets are efficient (rational) in a way that they reflect correct prices and

therefore finance theory incline towards endorsing the efficient market hypothesis (EMH)

221 Prospect Theory (PT 1979)

The idea of bounded rationality was introduced by Simon (1955) and gave birth to the

discipline of behavioral finance as various studies found empirical evidence against the

assumption of rationality in decision-making process (Akerlof amp Schiller 2009 De Bondt

amp Thaler 1985 Kahneman amp Tversky 1979 Shleifer amp Summers 1990) Research in this


25

area aced when Kahneman and Tversky (1979) proposed the prospect theory and received

more appreciation after Kahneman received the Nobel Prize for Economics in 2002

Prospect theory purports that when individuals are offered a gamble containing two or

more outcome lotteries with some probability they make their decisions on the basis of the

potential psychological value of gains and losses rather than on the final outcomes of

lotteries They choose the one with the highest value

This value function is defined based on psychological gains and losses rather than on

levels of wealth The function is concave in the area of gain and thus risk-averse and is a

convex function in the area of loss and risk-takers Moreover the gradient of the value

function is steeper in the area of loss than in the area of gain which infers that investors

are generally risk-averse

A loss would have a larger psychological impact on the decision-maker than a gain

Critical to this value function is the reference point from which gains and losses are

measured (Kahneman amp Tversky 1979) Investors get more distressed by losses than they

are delighted by equal amount of gains The loss of $1 dollar is twice as unpleasant as the

happiness received from a $1 gain (Singh 2010) This happens due to the effect of

cognitive biases that operate on investorsrsquo judgment about expected psychological value

of these gains and losses Many studies have tested prospect theory in the domain of

influence of behavioral factors (so-called irrational biases) on decision-making (Ishfaq et

al 2017 Odean 1998)

Samra Chaudary

26

222 Theory of Planned Behavior (TPB 1991)

Ajzen and Fishbein (1980) asserted that behavioral intentions are cognitive in nature

and act as a representation of an individualrsquos eagerness to involve in a particular behavior

According to the theory of planned behavior (TPB) Individualsrsquo behavior is predicted by

onersquos behavioral intention Behavioral intentions are then determined by favorable attitude

subjective norms and perceived behavioral control These intentions along with

perceptions of behavioral control explain significant variance in real behavior (Ajzen

1991)

Thus the core idea of the theory implies that planned behavioral was driven by

behavioral intentions (Ajzen 2001) The theory of planned behavior predicts human

behavior which can include conflicts between short-term and long-term goals affect

cognition and consequences in several fields (Ajzen 1985 1991) Raut Das and Kumar

(2018) suggested that TPB predicts individualsrsquo behavioral willingness to invest in the

stock market They also revealed that attitude toward behavior subjective norms and

perceived behavioral control are significantly related to behavioral intentions According

to Michaelidou and Hassan (2014) the research work on gain versus loss framing by

Tversky and Kahneman (1981) has been well studied Therein lies a starting point that may

assist in apprehending the process of the theory of planned behavior in several decision-

making situations and contexts

Many researches have utilized TPB in the domain of behavioral studies with investment

decision-making (East 1993 Mayfield et al 2008) with financial decision-making

(Koropp Kellermanns Grichnik amp Stanley 2014) and with entrepreneurial (business

start-up) decision-making (Kautonen 2015)


27

East (1993) investigated the willingness to apply for new issue of shares TPB was

applied to personal investment choices and found support for TPB as a way of identifying

that beliefs are associated with investment choice behavior He reported that investment

decisions are just like consumer decisions and investors do not decide only based on

financial criteria Moreover Koropp et al (2014) investigated financing decisions and TBP

was applied to capital structure decisions of German family firms They also supported

TPB as family attitudes toward debt and equity affected behavioral intention to use the

respective financing decisions which in turn affected financing behavior

Similarly Kautonen (2015) too supported the relevance of TPB in the context of

business start-up intentions He instigated whether intentions were linked to business start-

up activities such as arranging finances approaching financial institutions for funds

financial projections and many other activities related to business start-up Mayfield et al

(2008) used two types of personality traits as behavioral intentions and also supported TBP

that long-term and short-term investment intentions were predicted by personality types

This research however uses Big-Five personality types and extends the applicability of

the well-established TPB in the area of decision-making of the investment horizon

223 Risk as Feeling Theory (RaF 2001)

A few behavioral models overtly sketch that the behavioral actions are the consequence

of ambivalence due to the availability of conflicting information but Risk as feelings (RaF)

hypothesis (Loewenstein Weber Hsee amp Welch 2001) is an exception The RaF

(Loewenstein et al 2001) theory explains a range of behaviors that exhibit deviation

between cognitiverational evaluations and feelings

Samra Chaudary

28

The theory proposed that when there is a risky situation behavior tends to be driven

by emotional reactions or feelings encountered at the time of decision-making rather than

cognitiverational assessments of the situation The RaF theory predicts action selection in

psychological risk-return models (Weber amp Johnson 2008) They found that affective

(non-rational) responses to risky situations had shown a significant role in risk perception

of risky choices

Hsee and Weber (1997) proposed that when individuals made a risky decision their

choice was influenced by their subjective feelings towards risk Moreover Loewenstein

and Lerner (2003) also found that individuals make a decision on the basis of the affect

(feeling) which they encountered at the time of the decision

Kobbeltvedt and Wolff (2009) tested planned and feeling based behavior models

with TPB and RaF theories in their study They argued that TPB and RaF have some shared

variables which are subjective probability anticipated outcome and behavior Both of

these models assume that estimations of a particular behavior will be guided by anticipated

outcomes in combination with subjective probabilities

224 Competing Personality Taxonomies

Aristotle (384-324 BC) struggled to provide a guide for human ldquocharactersrdquo Ever

since others have also attempted to map similar human attributes The 20th century

provided the procedure of sampling human attributes (ie formulation of Lexical

Hypothesis)

The Lexical Hypothesis postulates that most of the socially relevant and prominent

personality characteristics are encrypted in the natural language (Allport 1937) Hence

the personality terminology which was encoded in the dictionaries of a natural language


29

delivers a broad yet limited set of features that individuals speaking that language have

found essential and convenient in their everyday communications (Goldberg 1981) The

lexical hypothesis provided the theoretical foundation for the Five-Factor personality

model (Allport amp Odbert 1936)

The lexical hypothesis led to factor analyses of a wide array of personality

attributes resulting in the development of the Five-Factor model This hypothesis also

suggested that it should be possible to analyze the most significant attributes that have

similar meanings to describe a personality (Saucier amp Goldberg 1996)

Numerous instruments were developed to measure personality traits and this

activity of instrument development has accelerated tremendously overtime (Goldberg

1971) According to John and Srivastava (1999) researchers are confronted with a wide

range of personality scales with pintsize guidance and with no adequate reasoning Scales

with similar titles often measured different concepts and scales with different titles

frequently measured somewhat similar concepts

Therefore a taxonomy of traits was desired which would allow researchers to

investigate specific domain of personality attributes instead of inspecting thousands of

characteristics individually which makes each individual distinct Moreover an

established taxonomy would enable researchers to communicate their research outcomes

in a uniform vocabulary Table 21 provides a summary of broad sets of competing

personality measures that were proposed over last 40 years

Samra Chaudary

30

Table 21 Summary of Personality Taxonomies

Study Factors Personalities

Tupesamp

Christal

(1961)

Five Surgency (Sociability amp Ambition) Agreeableness Dependability

Emotional Stability and Culture

Norman

(1963) Five

Extraversion (Surgency) Conscientiousness Agreeableness Emotional

Stability and Culture

Cattell et al (1970) Sixteen

Warmth Reasoning Emotional Stability Dominance Liveliness Rule-

Consciousness Social Boldness Sensitivity Vigilance Abstractedness

Privateness Apprehension Openness to Change Self-Reliance

Perfectionism and Tension

Myersamp

McCaulley

(1985)

Four

Extraversion vs Introversion Thinking vs Feeling Judging vs Perceiving

and Intuition vs Sensation

Hogan

(1982) Six

Ascendancy Sociability Agreeableness Dependability Emotional Stability

and Intellectance

CostaampMcCrae

(1985) Five

Neuroticism Extraversion Openness Agreeableness and

Conscientiousness

Kampamp Hough

(1986) Seven

Potency Adjustment Agreeableness Dependability Intellectance

affiliation and Miscellaneous

Hogan

(1986) Six

Sociability Ambition (Potency amp Achievement) Prudence Likeability

Adjustment and Intellectance

Digmanamp Inouye

(1986) Five

Extraversion (Surgency) Will to Achieve Agreeableness Anxiety and

Openness

Kampamp Gough

(1986) Five

Ascendency Self -Control Adjustment (Agreeableness amp Anxiety)

Intellection and Masculinity

Goldberg

(1990) Five

Surgency Conscientiousness Agreeableness Emotional Stability and

Intellect

Hough et al

(1990) Nine

Affiliation Potency Achievement (Dependability Conscientiousness ampWill

to achieve) Dependability Adjustment Agreeableness Intellectance

Ruggedness individualism and Locus of Control

Costaamp

McCrae

(1992)

Five

(Revised

NEO

personality

inventory)


Conscientiousness

Cattell

(1996) Five Extraversion Independence Anxiety Self-Control and Tough-mindedness

In addition to multi-factor models of personality types as shown in table 1 a number

of studies have also tried to develop tools for the assessment of a personality eg California

Personality Inventory by Gough (1987) Eysenck Personality Inventory by Eysenck and

Eysenck (1975) Guilford-Zimmerman Temperament Survey by Guilford (1949) and

Myers-Briggs Personality Type Indicator by Mayer and McCaulley (1985) All of these

instruments are believed to be encompassed in the Five-Factor Model (Briggs 1992 Costa


31

Busch amp Zonderman 1986 Johnson Butcher Null amp Johnson 1984 Noller Law amp

Comrey 1987) Moreover the Five-Factor Model developed by Costa and McCrae (1992)

was comparable with Five-Factor model proposed by Goldberg (1990) and Cattell (1996)

as shown in table 22

After many decades researchers have developed a consensus on the Big-Five

personality model as an acceptable taxonomy for labeling the basic dimensions of a

personality Therefore many studies based on meta-analyses of personalities have

converged on using Five-Factor personality model because it describes the most salient

aspects of personality (Barrick amp Mount 1991 Judge Heller amp Mount 2002 Oshio

Taku Hirano amp Saeed 2018 Salgado 1997 Trapmann Hell Hirn amp Schuler 2007)

The Five-Factor Model continues to be the most studied model of personality model based

on the lexical hypothesis (Poropat 2009)

The advantage of using the Five-Factor Model is that it includes most of the

variance in a set of five-factors of personality thus solving the puzzle of the earlier ldquochaotic

plethorardquo of personality measures (Funder 2001 John amp Srivastava 1999) The Five-

Factor model provides a comprehensive and parsimonious theoretical framework (Costa amp

McCrae 1992)

Moreover another important feature of the Five-Factor Model was that it uses

natural language which was not biased to prefer any existing scientific conception (John amp

Srivastava 1999) Hence this research has adopted the most recent and updated Five-

Factor Model by Costa and McCrae (1992) for personality measures as shown in table 23

Samra Chaudary

32

Table 22 Alignment Among the three main Five-Factor Models

Cattell (1996) Costa amp McCrae (1992) Goldberg (1990)

ExtraversionIntroversion Extraversion Surgency

Low AnxietyHigh Anxiety Neuroticism Emotional stability

Tough-MindednessReceptivity Openness Intellect or culture

IndependenceAccommodation Agreeableness Agreeableness

Self-ControlLack of Restraint Conscientiousness Conscientiousness or

dependability

Source (Cattell amp Mead 2008)

225 Personality Type and Investment Decisions

Satchell et al (2018) found that different personalities have varied risk-taking

behaviors Individuals who exhibit more prosocial traits (more extravert) are risk-takers as

compared to those who exhibit antisocial traits (less extravert) Hershey and Mowen (2000)

in one of the initial studies on personality and decision-making found that personality

constructs were significant predictors of pre-retirement financial decisions Filbeck et al

(2005) studied the relationship between risk tolerance and personality types on a sample of

college students They found that respondents with higher score on thinking (objective

decision-making) judging (organization and order) and sensing (concrete and practical)

traits showed relatively higher risk tolerance in their investment decisions They also

reported that extraversion trait showed no effect on risk tolerance However Mayfield et

al (2008) later on conducted research on undergraduate students registered in an

investment course They mainly focused on the effect of two personality traits on both ST-

D and LT-D Results showed that extravert and conscientiousness investors tended to

involve in short-term investments however individuals with neuroticism andor risk

aversion trait avoided to engage in short-term investments Risk-averse investors also did

not take part in long-term investing Investors with the openness trait showed long-term

investing behavior On the other hand openness did not determine short-term investing


33

behavior A negative correlation was reported between openness trait and risk aversion

Moreover extraversion was reported negatively but insignificantly associated with

investment-specific risk aversion For personality measurement the study adopted a

revised NEO personality inventory (NEO-PIR) scale by Costa and McCrae (1992) and

NEO five-factor inventory (NEO FFI) by Salgado (1997) The Big-Five personality

classification was predominantly recognized in applied research (Barrick amp Mount 1991

Hogan amp Hogan 1991) Table 23 explains the traits of five types of personalities

Table 23 Descriptions of the Big-Five Personality Traits

Personality Trait Description

Neuroticism (N) High scores show insecure self-conscious vulnerability anxious depressed tenseness

and moodiness

Extraversion (E) High scores show gregarious assertiveness sociability talkativeness optimism positive

emotion being upbeat and energetic

Openness (O) High scores show creativity active imagination trust a preference for variety curios and

cultural interest

Agreeableness (A) High scores show altruism warmth sympathetic helpful modest compliance tender

mindedness and cooperation

Conscientiousness (C) High scores show hard-working organized purposefulness self-discipline

achievement striving determination reliability and punctuality

Source (Costa amp McCrae 1992 Salgado 1997)

The meta-analysis studies on Big-Five personality types found that extraversion

and conscientiousness had an influence on concrete problem solving and cognitive

structuring as coping strategies (Connor- Smith amp Falchsbart 2007) An entrepreneurial

(risky) behavior was determined by the traits of conscientiousness and openness to

experience (Zhao amp Seibert 2006) Verma (2008) in an Indian sample found that

personality and demographics have shown an association with the investment choice

However the study poorly measured personality traits on a five-point likert scale from

conservative to aggressive and chose to report the results with basic and simple statistical

techniques Many studies have investigated investment decisions in the form of investment

Samra Chaudary

34

horizon ie long-term vs short-term (Dierkes et al 2010 Riaz amp Hunjra 2016 Wood amp

Zaichkowsky 2004)

Oehler et al (2018) examined the impact of extraversion and neuroticism on

investment decisions in an experimental financial market The authors found that more

extravert persons paid a high price for their assets purchases and they bought more financial

securities when securities were overpriced as compared to less extravert persons The

influence of the extravert trait was found to be insignificant when it comes to holding an

asset However more neurotic individuals keep less volatile financial securities in their

portfolios than less neurotic individuals Similarly Oehler and Wedlich (2018) also

investigated the impact of extraversion and neuroticism on risk-taking behavior in

investment decisions The authors identified that more extravert subjects were less risk-

averse and more neurotic subjects were more risk-averse This research had again focused

only on two personality traits and used a student sample Both of the above-mentioned

studies ignored the remaining three personality traits ie openness agreeableness and

conscientiousness

Moreover the above-cited research findings were based on samples of

undergraduate students of a German university which means their findings were not

coming from a sample of practitioners working in the financial industry This research

however investigates relationships of all Big-Five personality traits with investment

decisions The study also investigates the relationships from a sample of individuals

working in the financial industry of a developing economy by using a sample of practicing

investors The following hypotheses are tested about the behavioral intentions of stock

investors


35

H1a The greater the level of individuals neuroticism the more likely will be their

intentions to engage in short-term investing

H1b The greater the level of individuals neuroticism the less likely will be their intentions

to engage in long-term investing

H2a The more extravert individuals would show stronger intentions to engage in short-

term investing

H2b The more extravert individuals would show stronger intentions to engage in long-term

investing

H3a The greater the level of individuals openness the less likely will be their intentions to

engage in short-term investing

H3b The greater the level of openness the more likely will be their intentions to engage in

long-term investing

H4a The greater the level of individuals agreeableness the more likely will be their


H4b The greater the level of individuals agreeableness the more likely will be their

intentions to engage in long-term investing

H5a The more conscientious individuals would show weaker intentions to engage in short-

term investing

H5b The more conscientious individuals would show stronger intentions to engage in long-

term investing

226 Risk Perception and Investment Decisions

Perception is described as the psychological interpretation of physical sensations

shaped by stimuli from the external environment (Fischhoff 1994) Therefore the way

Samra Chaudary

36

individuals subjectively perceive risk of an investment is likely to influence their actions

(Riaz amp Hunjra 2016) Zeisberger (2018) using an experimental design found that the

ldquoprobability of losingrdquo was the key variable that their subjects perceived as ldquoriskrdquo Lim et

al (2013) defined risk perception as an assumption or evaluation of risk related to a specific

behavior Loewenstein et al (2001) proposed a theory termed ldquorisk as feelingrdquo hypothesis

and highlighted that behaviors are driven by feelings An affect must mediate at least to

some extent the relationships of cognitive evaluations

Risk perceptions are likely to vary across individuals and contexts For instance

many individuals assume that the risk in driving a car is more dangerous than the risk in

sports and show relatively less intention to take risks of driving a car (Dohmen et al

2011) Huber Palan and Zeisberger (2017) through an experiment found that active asset

trading and asset prices are strongly driven by average risk perception Numerous studies

have inspected how investorsrsquo perceptions affect hypothetical investment decisions or self-

reported investment intentions (Bateman et al 2010 Keller amp Siegrist 2006a Nosic amp

Weber 2010 Weber Weber amp Nosic 2013 Weber amp Milliman 1997)

Hoffman Post and Pennings (2015) used a sample of Dutch investors and studied

the association between perceptions and behavior in an actual decision setting They found

that change in investor perceptions was a significant determinant of real trading and risk-

taking behavior They also found that stock traders who perceived higher risk tended to

trade more frequently had higher volume had lower buy-sell ratios (lower buy-sell ratios

demonstrate a low exposure to the financial market) and held riskier portfolios It means

stock traders with higher levels of risk perception lowered their exposure to the stock

market Lim et al (2013) reported that risk perceptions about investing in the capital market


37

were found likely to have a negative impact on investorsrsquo willingness to invest in the

financial market

Duxbury Hudson Keasey amp Summers (2005) in their study asked subjects to

distribute money among risk-free assets risky shares and bonds and studied how this

allocation varied if they were investing for someone who was lessmore willing to take risk

than themselves The study was repeated on different ranges of age and wealth They then

investigated how subjectsrsquo perceptions of investment patterns were different from their

actual investment behavior Subjects believed that the ratio of bonds to shares should differ

with risk attitude with a higher ratio of stocks held by those participants who were willing

to take more risks Despite having such beliefs subjectsrsquo actual investment behaviors

showed the amount of shares and bonds held did not change with their risk attitude In other

words participantsrsquo beliefs did not match the recommendations of standard portfolio

theory but their actual investment behavior matched the theoretical expectations of the

portfolio theory Weber et al (2002) investigated the individualrsquos risk perception and risk

behavior in five domains (financial risk-taking healthsafety risk-taking ethical risk-

taking recreational risk-taking and social risk-taking) They reported divergences in risk

perception of participants accounted for observed variations in their risk behavior

Financial risk-taking behavior and risk perception were found negatively correlated They

found perceived higher risks decreased the chances of the risk-taking behavior most for

financial risks and least for health or safety risks The effect of perceived risk on the risk-

taking behavior was negative but statistically insignificant Brandstatter (2011) in a study

of meta-analysis reported the results of the relationship between risk propensity and the

Big-Five dimensions of personality Risk propensity was assessed by asking individuals

Samra Chaudary

38

how frequent they have exhibited risky behavior in six domains (recreation health career

finance safety and social risk-taking) leading to a risk measure He reported a positive

beta-estimates for extraversion and openness and negative beta-estimates for neuroticism

agreeableness and conscientiousness

Lim et al (2013) found in a sample of Singaporean investors a significant negative

relationship between risk perception and risky investment decisions They reported that the

sample for this research was collected right after the global financial crisis and that could

have an influence on investorsrsquo risk perception They suggested collecting similar data

again during a time of financial stability Many scholars have agreed about the presence of

an association between perceived risk and decision-making (Krueger amp Dickson 1994

Sutcliffe 1994) A small number of researches have tested the mediating role of risk

perception For example risk perception was reported to be mediating the relationship

between information asymmetry and risky investment decisions (Riaz amp Hunjra 2016) and

between heuristics and investment decisions (Ishfaq et al 2017) Wang Shi and Fan

(2006) also reported that risk perception mediated the relationship between various types

of information and investment performance They also stated risk perception led to higher

investment performance Weber et al (2002) found that personality variables (eg

sensation seeking tolerance for ambiguity and gender) had an influence on risk perception

Person-centered characteristics (age gender and culture) together with personality traits

were reported to impact risk-taking These variables were reported to affect risk-taking

often by altering onersquos perception of risk and perception of benefits of alternative decision-

making rather than by affecting their desire to take more or less risk Hence the risk

perception of an individual is responsible for onersquos actual behavior or decision-making It


39

is expected that risk perception would mediate the relationships between personality types

and LT-D Figure 21 and 22 illustrates the structural model about relationships of five

personality types with ST-D and LT-D with mediation by risk perception

H6a Risk perception mediates the relationship between Neuroticism and short-term

investment decisions

H6b Risk perception mediates the relationship between extraversion and short-term


H6c Risk perception mediates the relationship between openness and short-term investment

decisions

H6d Risk perception mediates the relationship between agreeableness and short-term


H6e Risk perception mediates the relationship between conscientiousness and short-term


H6f Risk perception mediates the relationship between neuroticism and long-term


H6g Risk perception mediates the relationship between extraversion and long-term


H6h Risk perception mediates the relationship between openness and long-term investment

decisions

H6i Risk perception mediates the relationship between agreeableness types and long-term


H6j Risk perception mediates the relationship between conscientiousness and long-term


Samra Chaudary

40

Figure 21 Structural model about the relationships of five personality types with short-

term investment decisions with mediation by risk perception

Figure 22 Structural model about the relationships of five personality types with long-


Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness

S-T Investment Decisions

Risk Perception

H1a

H2a

H3a

H4a

H5a

H6a

H6b

H6c

H6d

H6e

Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness

L-T Investment Decisions

Risk Perception

H1b

H2b

H3b

H4b

H5b

H6f

H6g

H6h

H6i

H6j


41

23 Data and Methodology

231 Measures

The study has adopted developed instruments from the existing literature in order

to measure the latent variables Short-term investment decisions and long-term investment

decisions were measured by adopting items from Mayfield et al (2008) Big-Five

personality scale was adopted from Costa and McCrae (1992) to measure five types of

personality traits on a five-point likert scale Items for risk perception were adopted from

Weber et al (2002) To measure risk perception (RP) respondents were asked to indicate

their gut-level assessment of how risky each situation was on a five-point unipolar rating

scale The complete questionnaire is attached in appendix VI

232 Methods

2321 Sample and Data Collection

This study has adopted a positivist research philosophy with a deductive research

approach as mentioned in Saunders Lewis and Thornhill (2007) research onion The

positivist philosophy reflects the natural scientistsrsquo philosophical approach Researcher

prefers to deal with a social reality that is measurable and the findings of such study are

presumed to be generalizable similar to law produced by natural scientists (Remenyi

Williams Money amp Swartz 1998) The deductive approach could therefore be

considered particularly suitable for the positivist approach Hence this study uses existing

theory to form hypotheses that were empirically tested leading to theoretical advancement

which can then be tested by future researchers (Saunders et al 2007)

Primary data were collected through a snowball sampling technique for this study

The respondents for this survey were investors in the local stock market Therefore the

Samra Chaudary

42

sample consisted of portfolio managers working in the financial industry (eg mutual fund

companies asset management companies brokerage houses or treasury departments of

banks) and individual investors who have invested in Pakistan Stock Exchange (PSX)

previously known as Karachi Stock Exchange (KSE) Individual stock investors were from

different backgrounds as the purpose of the research was to analyze the behavior of stock

investors be it at an individual level investor or a person working with an institution The

data were collected through a survey using a structured questionnaire from two major

metropolitan cities of Pakistan Lahore and Karachi Out of total investorsrsquo population

(corporate and individual combined) of the country Karachi has 74 percent investors and

Lahore has 18 percent investors (Central Depository Company 2018) Hence the data

were collected from the investment hubs of the country where 92 percent stock investors

in listed traded companies were located A total of 800 questionnaires were sent out to

collect data Five hundred and seventeen questionnaires were returned and only 277 were

found useable for this study thus response rate was almost 35 percent

The sample consisted of 80 percent males and 20 percent females as the investment

industry of Pakistan is highly male-dominated The sample consisted of 59 percent of

money managers and 41 percent individual investors Eighty-seven percent of respondents

were employed 12 percent were business owners and 1 percent of the sample was not

employed Furthermore 60 percent respondents were married 37 percent were single and

3 percent were either separated or divorced

Fifty-eight percent of respondents perceived that they were from the middle social

class 36 percent perceived themselves in upper-middle-class 3 percent perceived

themselves to belong to the upper class and 3 percent perceived themselves from a lower


43

middle class Only 33 percent of the respondents had an expectation to receive inheritance

or transfer of assets from the family and 67 percent respondents did not expect any future

inheritance Eighty-six percent respondents had responded their upbringing was in the

urban areas and 14 percent respondents had their upbringing in rural areas

The average age of respondents was 32 years and the average monthly income was

Pak Rupee (PKR) 018 million The average formal years of education were 16 years The

average amount invested by the investors in stocks was PKR 10 million and the average

investment experience in the stock market was 4 years

2322 Data Analyses

Blanthorne Jones-Farmer and Almer (2015) proposed guidelines on the key

elements of structural equation modeling in behavioral accounting research Most

textbooks on this matter propose a sample of between two hundred and fifty and five

hundred (Kline 2005 Loehlin 2004 Schumacker amp Lomax 1996) Blanthorne et al

(2015) have argued that large sample size requirement leaves researchers of this discipline

in a difficult situation of requiring permission and support from more subjectsrespondents

who are mostly professionals They also claimed that five of the thirteen potential SEM

studies published in Advances in Accounting Behavioral Research had less than hundred

participants and only four articles contained more than two hundred and fifty participants

A sample of greater than 200 was considered sufficient for the use of structural equation

modeling (SEM) (Iacobucci 2010 Kline 2015)

This paper has made use of partial least square based structural equation modeling

(PLS-SEM) approach instead of covariance-based structural equation modeling (CB-SEM)

due to a number of reasons Firstly PLS-SEM does not require data to be normally

Samra Chaudary

44

distributed (Hair Sarstedt Ringle amp Mena 2012) and shows higher statistical power than

CB-SEM for complex models with small sample sizes (Reinartz et al 2009) Moreover

the data had an adequate sample size (Kline 2015) with no missing values Collinearity

was also tested and was found acceptable Secondly this approach focuses on predictive

analysis The goal of PLS-SEM estimation was to maximize the variance of the

endogenous variables explained by the exogenous variables (Hair Hult Ringle amp Sarstedt

2014) Thirdly it has a minimum demand for sample size and residual distribution (Wold

1985) Fourthly to compute the statistical significance of the parameter estimates PLS-

SEM method reports percentile bootstrap confidence intervals (Hair Ringle amp Sarstedt

2011 Preacher amp Hayes 2008) Bootstrap sampling method provides robust results by

taking subsamples from the original sample of observations and estimates the model

parameters of each subsample and then report the significance of the estimated coefficients

(Hair et al 2012) This sample then tests the significance of the estimated coefficients

(Henseler Ringle amp Sinkovics 2009) Lastly PLS approach can be utilized for theory

validation as well as to propose where relationships may or may not exist (Chin 1998)

PLS is also beneficial for exploratory research and for initial phases of theory development

(Fornell amp Bookstein 1982)

PLS-SEM approach is as worthy (and conservative) as CB-SEM method (Hair et

al 2014) While PLS-SEM has some shortcomings eg results tend to inflate the factor

loadings and underestimate structural relationship and coefficient of determination

Similarly CB-SEM also has some weaknesses for instance results tend to overestimate

the structural path coefficients and underestimate factor loadings Bolander Satornino

Hughes and Ferris (2015) have recommended that PLS-SEM is a more conservative


45

approach than CB-SEM Table 24 depicts the correlations descriptive statistics and

square root of Average Variance Extracted (AVE) of the latent constructs

The short-term investment decision was found to be positively correlated with long-

term investment decision risk perception and four personality types which were

neuroticism extraversion openness and conscientiousness The Pearsonrsquos correlation

value was found to be 0551 (p=0000) between short-term investment decision and long-

term investment decision 0213 (p=0000) with risk perception 0206 (p=000) with

neuroticism 0458 (p=0000) with extraversion 0385 (p=0000) with openness and 0253

(p=0000) with conscientiousness

Similarly long-term investment decision also showed a positive correlation with

risk perception and four personality types The Pearsonrsquos correlation value was found to

be 0308 (p=0000) between long-term investment decision and risk perception 0140

(p=0019) with neuroticism 0581 (p=0000) with extraversion 0539 (p=0000) with

openness and 0415 (p=0000) with conscientiousness

The agreeableness personality type showed a significant negative correlation with

all other variables The highest correlation was found between extraversion and openness

personality traits with Pearsonrsquos correlation of 0635 (p=0000) and the lowest correlation

was found between extraversion and neuroticism with an insignificant negative Pearsonrsquos

correlation of -0020 (p=0736)

Samra Chaudary

46

Table 24 Inter factor Correlations and Square root of Average Variance Extracted

Note SD=Standard Deviation ST-D=Short-term Investment Decision LT-D=Long-term Investment Decision

N=Neuroticism E=Extraversion O=Openness A=Agreeableness C=Conscientiousness and RP=Risk Perception

Diagonal values in parentheses are values of square root of AVEs

p lt 1 p lt 05 p lt 01

24 Results

241 Measurement Model

Table 25 reports the result of the measurement model Factor loadings for each

item were 06 or above except one item of Conscientiousness which had a loading of 04

but Anderson and Gerbing (1988) Wille (1996) and Velicer amp Fava (1998) lend support

to using loadings lower than 06 Bootstrapping was done on a subsample of 5000

subsamples to compute t-statistics of each factor loading (Henseler et al 2009) All the

factor loadings were statistically significant as t-statistics for each factor loading were

above 196 (Anderson amp Gerbing 1988 Hulland 1999) For each latent factor a minimum

of three items significantly loaded on each factor in a multidimensional scale as

recommended by Velicer amp Fava (1998) and Raubenheimer (2004) and all factors were

reflective The estimates of standardized factor loadings ranged from 0600 to 0764

(tgt196) for short-term investment decision 0659-0750 (tgt196) for long-term investment

decision 0656-0864 (tgt196) for neuroticism 0788-0859 (tgt196) for extraversion

0642-0804 (tgt196) for openness 0722-0783 (tgt196) for agreeableness 0406-0855

(tgt196) for conscientiousness and 0729-0888 (tgt196) for risk perception

Factors Mean SD ST-D LT-D N E O A C RP

ST-D 3075 0763 (0681)

LT-D 3279 0810 0551 (0702)

N 2524 0895 0206 0140 (0785)

E 3444 0929 0458 0581 -0020 (0878)

O 3298 0783 0385 0539 0099 0635 (0739)

A 2984 0880 -0229 -0273 -0358 -0199 -0189 (0760)

C 3228 0751 0253 0415 0074 0427 0432 -0345 (0707)

RP 2261 0921 0213 0308 0094 0220 0193 -0238 0169 (0812)


47

Convergent validity was computed through average variance extracted (AVE)

which met the benchmark of 050 or higher for each latent construct (Hair et al 2012)

The values for AVE were 0466 for short-term investment decision 0493 for long-term

investment decision 0617 for neuroticism 07771 for extraversion 0546 for openness

0579 for agreeableness 0500 for conscientiousness and 0660 for risk perception

Internal consistency of latent constructs was computed through composite

reliability (CR) which was higher than 07 for all latent constructs as suggested by Hair et

al (2012) The values of composite reliability were 077 for short-term investment

decision 0829 for long-term investment decision 0889 for neuroticism 0881 for

extraversion 0827 for openness 0804 for agreeableness 0733 for conscientiousness and

0852 for risk perception Please see table 26

Discriminant validity of each latent construct was computed through two

approaches and met the Fornell-Larcker criteria (1981) and Heterotrait-Monotrait (HTMT)

ratio of correlations (Henseler Ringle amp Sarstedt 2015) Fornell-Larcker criteria were

met as the square root of AVE of each latent construct was greater than its inter-factor

correlations with all other latent constructs (Hair et al 2012) Moreover HTMT ratio

criteria for discriminant validity was met as the ratio was less than one for each latent

construct as reported in table 27 Common method bias and collinearity among exogenous

latent constructs were checked through the variance inflation factor (VIF) test at the factor

level The test was carried out twice with both dependent variables once with short-term

investment decision and once with long-term investment decision We found no common

method bias in both the tests as the Variance Inflation Factor (VIF) values of all the factors

were less than 33 (Kock 2015)

Samra Chaudary

48

Table 25 Results of Measurement Model

Constructs Sources Items Statements Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)

I intend to put at least half of my investment money into

the stock market

0600 8579

I intend to engage in portfolio management activities at

least twice per week

0764 17620

I intend to perform my own investment research instead

of using outside advice

0685 14911

I intend to compare my portfolio performance to that of

professional managers

0665 11816

Long-term

Investment

Decision

(Mayfield

et al

2008)

I intend to save at least 10 of my gross earnings for

investingsavingretirement purposes

0750 23657

I intend to have a portfolio that focuses on multiple asset

classes (ie stocks bonds cash real estate etc)

0716 17223

I intend to take an investment course 0723 22937

I intend to manage my portfolio for maximum gross

return rather than tax and cost efficiency

0663 14376

I intend to invest some money in long-term assets where

my money will be tied up and inaccessible for years

0659 13952

Neuroticism (Costa amp

McCrae

1992)

I often feel inferior to others 0656 8712

When I am under a great deal of stress sometimes I feel

like I am going to pieces

0864 26438

I often feel tense and jittery 0844 20541

Sometimes I feel completely worthless 0776 11760

Too often when things go wrong I get discouraged and

feel like giving up

0770 13300

Extraversion (Costa amp

McCrae

1992)

I really enjoy talking to people 0859 48079

I am a cheerful high-spirited person 0876 53353

I am a very active person 0788 22761

Openness (Costa amp

McCrae

1992)

I am intrigued by the patterns I find in art and nature 0765 22515

I often try new and foreign foods 0642 11363

I have a lot of intellectual curiosity 0804 30217

I often enjoy playing with theories or abstract ideas 0734 19581

Agreeableness (Costa amp

McCrae

1992)

I often get into arguments with my family and co-

workers

0722 10789

Some people think I am selfish and egotistical 0775 15435

Some people think of me as cold and calculating 0783 13761

Conscientious

ness

(Costa amp

McCrae

1992)

I keep my belongings neat and clean 0784 14094

I am pretty good about pacing myself so as to get things

done on time

0855 22739

I waste a lot of time before settling down to work 0406 3623

Risk

Perception

(Weber et

al 2002)

Investing 10 of your annual income in a moderate

growth mutual fund

0812 20781

Investing 5 of your annual income in a very speculative

stock

0888 31293

Investing 5 of your annual income in a conservative

stock

0729 12008

Note p lt 1 p lt 05 p lt 01

reverse coded items


49

Table 26 Convergent Validity and Construct Reliability of Constructs

Constructs Composite Reliability

(CR)

Average Variance Extracted (AVE)

Short-term Investment Decision 0775 0466

Long-term Investment Decision 0829 0493

Neuroticism 0889 0617

Extraversion 0881 0711

Openness 0827 0546

Agreeableness 0804 0579

Conscientiousness 0733 0500

Risk Perception 0852 0660

Table 27 Heterotrait-Monotrait (HTMT) Ratio of Correlations

Factors A C E LT-D

N O RP

ST-D

A

C 0634

E 0281 0706

LT-D 04 0711 0752

N 049 0352 0093 0214

O 0282 0747 0837 074 0133

RP 0343 0281 0267 0401 0127 0253

ST-D 0392 0485 065 0809 0283 0573 0303

Note ST-D= Short-term Investment Decision LT-D= Long-term Investment Decision N= Neuroticism E=

Extraversion O= Openness A= Agreeableness C= Conscientiousness and RP= Risk Perception

242 Structural Model

The following section presents the findings of the direct effects of Big-Five

personality traits on short-term investment decisions and long-term investment decisions

It also presents the mediating effect of risk perception between personality type and both

types of investment decisions The standardized parameter estimates (path coefficients) of

structural model were estimated along with their significance The significance of

coefficients was computed using a bootstrap approach with 5000 subsamples (Henseler et

al 2009) The effect size was reported for each direct effect through f- square test (Cohen

1988) The f2 values of 002 015 and 035 represent a small medium and large effect

Samra Chaudary

50

size of the independent variable (Henseler et al 2009) Moreover the coefficient of

determination (R2) for each of the latent dependent (endogenous) variables were not below

010 (Falk amp Miller 1992) The predictive relevance of the model was computed by

calculating Q2 coefficients (Geisser 1975 Stone 1974) using the blindfold test (Hair et al

2014) A power test was also conducted to estimate the probability that a statistically

significant relationship would be found when the relationship is actually present (Goodhue

Lewis amp Thompson 2012) A value of 08 or higher was recommended sufficient in

behavioral studies for the power test (Cohen 1988)

Table 28 summarizes the results of direct effects (without mediator) The

hypothesized relationships between personality trait of neuroticism was found to be

positive and highly significant with ST-D (H1a) (β= 0200 p= 0002 f2= 0062) and was

found insignificantly positive with low effect size (H1b) (β= 0079 p= 0159 f2= 0017)

with LT-D Similarly positive and significant relationships between extraversion

personality and ST-D (H2a) and LT-D (H2b) were found and showed moderate effect size

(β =0405 p= 0000 f2= 0129 β= 0537 p= 0000 f2= 0102) respectively The association

between openness personality trait with ST-D (H3a) was found insignificant with low

effect (β= 0084 p= 0275 f2= 0010) but with LT-D (H3b) it was found statistically

significant and positive with low effect (β=0515 p= 000 f2= 0069) No association of

agreeableness personality trait was found between ST-D (H4a) (β= -0060 p= 0419 f2=

0011) and with LT-D (H4b) (β= -0084 p= 0119 f2= 0017) The relationship of

conscientiousness personality trait with ST-D (H5a) was insignificant and showed almost

no effect (β= -0027 p= 0682 f2=0005) but with LT-D (H5b) the relationship was

significantly positive with small effect (β= 0373 p= 0000 f2= 0021)


51

The coefficient of determination of five types of personality traits and risk

perception with LT-D is higher (R2= 0493) than the coefficient of determination of the

same variables with ST-D (R2=0352) Hence a larger portion of the variance in LT-D was

explained by the set of five independent variables than in ST-D Only extraversion

personality traits were found as a common trait that impacted both ST-D and LT-D The

values of Q2 were considerably above zero representing that each exogenous construct in

the model has predictive relevance for both endogenous latent variables All the hypotheses

have shown very strong statistical power ie 0999 or above which shows a very high

probability of the presence of the relationships between all exogenous latent variables and

endogenous latent variables A high value of power test also reaffirms the appropriateness

of the sample size

We have included age gender income and expect to receive the inheritance as

control variables in our model These variables have relevance in the model of personality

type risk perception and investment decisions Studies have shown that males have shown

a greater inclination towards both ST-D and LT-D than females (Bajtelsmit Bernasek amp

Jianakoplos 1999 Hariharan Chapman amp Domian 2000 Mayfield et al 2008 Olsen amp

Cox 2001) Age also affects risk perception (Weber et al 2002) and financial decisions

(Agarwal Driscoll Gabaix amp Laibson 2007) Embrey and Fox (1997) investigated the

relationship between expected inheritances and income with financial investment

Samra Chaudary

52

Table 28 Results of Total Effects of Personality Traits on ST-D and LT-D

Hypotheses Relationships Path

Estimates

p

value f2 R2 Q2

Statistical

Power

H1a N-gtST-D 0200 0002 0062

0352 0127 1

H2a E-gtST-D 0405 0000 0129

H3a O-gtST-D 0084 0318 0010

H4a A-gtST-D -0060 0314 0011

H5a C-gtST-D 0027 0829 0005

H1b N-gtLT-D 0073 0110 0017

0493 0209 1

H2b E-gtLT-D 0537 0000 0102

H3b O-gtLT-D 0515 0000 0069

H4b A-gtLT-D -0084 0119 0017

H5b C-gtLT-D 0373 0003 0021


Extraversion O= Openness A= Agreeableness and C= Conscientiousness


Mediation Effects with Risk Perception

The mediating effects were tested using bootstrap method (Preacher and Hayes

2008 Zhao Lynch amp Chen 2010a) instead of Baron and Kenny (1986) approach because

bootstrapping corrects the non-normality problem and increases the statistical power to

detect mediation effects (Wood Goodman Beckmann amp Cook 2008) Bootstrap

sampling was done to estimate the distribution of the indirect effect (Hair et al 2014)

Bootstrap technique is a powerful test of mediation and Baron and Kenny (1986) test yields

high Type-I error (Krause et al 2010) Another major flaw of Baron and Kenny (1986) is

that it requires a mandatory presence of direct relationship of predictor and outcome

variable which is not necessary for the alternate approach (Hayes 2009 Krause et al

2010)

A mediator variable is expected to influence the relationship between a predictive

variable and an outcome variable (Baron amp Kenny 1986) Hence the mediator explains


53

the relationship oftentimes ldquohowrdquo and ldquowhyrdquo The mediation analysis supposed to

denotes a causal chain as it is concerned with the mechanism of a story or a series of effects

(Kenny 2008) and the definition of mediation is mostly expressed in causal terms (Baron

amp Kenny 1986)

In order to run a mediation analysis it is not necessary to get a significant

relationship between an independent and outcome variable (Kenny Kashy amp Bolger

1998 Zhao et al 2010a) Shrout and Bolger (2002) endorsed to omit the test of

significance of direct effects In this paper risk perception was tested as a mediator between

personality type and investment decision We compared the significance level (plt 005) of

direct effects and indirect effects and concluded the results

For H6a and H6b the direct effects of neuroticism and extraversion personality trait

on short-term investment decision in the presence of mediator (risk perception) were found

to be significant (β= 0202 p=0002) and (β= 0392 p= 0000) However the indirect effect

of neuroticism and extraversion on short-term investment decision through risk perception

was insignificant (β= -0002 p= 0817) and (β= -0013 p= 0309) Therefore these

hypotheses were labeled as direct only nonmediation (Zhao at al 2010a) For H6c H6d

H6e and H6f the standardized direct (mediated) effects and indirect effects were

insignificant Hence these hypotheses were categorized as no effect-nonmediation The

direct effects of extraversion and openness (H6g and H6h) on long-term investment

decision were found to be significant (β= 0493 p= 0000) (β= 0472 p= 0000) and

indirect effects of extraversion and openness on long-term investment decision were also

significant (β= 0044 p= 0005) (β= 0043 p= 0006) respectively Therefore these

hypotheses were labeled as complimentary mediation For H6i the (mediated) direct effect

Samra Chaudary

54

of agreeableness on long-term investment decision was insignificant (β= -0056 p= 0276)

however the indirect effect was significant (β= -0028 p= 0034) As a result this was

labeled as indirect-only mediation The direct effect and indirect effect of

conscientiousness on long-term investment decision in the presence of mediator (risk

perception) were both found to be significant (β= 0333 p=0000) and (β= 0040 p=0030)

Therefore H6j was labeled as complimentary mediation Among control variables only

males showed a significant impact on short-term investment decision and those who expect

to receive inheritance in the future showed a significant impact on long-term investment

decision

It was found that risk perception did not mediate the relationship between any of

the five personality types and short-term investment decisions (H6a-H6e) However four

personality traits (except neuroticism H6f) were found to show a significant indirect effect

on long-term investment decision through the perceived risk of the investment (H6g-H6j)

Moreover we found that agreeable personality (H6i) showed a negative indirect effect on

long-term investment decision through perceived risk of the investment

An indirect only-mediation effect is present when the direct effect of an

independent variable on dependent variable in the presence of mediator is insignificant and

indirect effect is significant This is also known as full mediation Complimentary

mediation is present when both direct and indirect effects are significant and point to the

same direction Direct-only non-mediation effect is present when only direct effect of

independent variable on dependent variable is significant in the presence of mediator but

indirect effect is not significant This is also a case of no mediation No-effect non-

mediation is declared when there is neither a significant direct effect is present nor a


55

significant indirect effect is present This is also declared as no-mediation situation These

mediation types also overlap with Baron and Kennyrsquos approach Complementary

mediation is similar to Baron and Kennyrsquos partial mediation and indirect-only mediation

is similar to full mediation Direct-only non-mediation and no-effect non-mediation

overlaps with no mediation of Baron and Kennyrsquos approach (Zhao et al 2010a) The

results of mediation analysis are reported in table 29 Detailed results of mediation analysis

are illustrated in figure 23 - 212 in appendix V

Table 29 Mediation Results of Risk Perception

Hypotheses Bootstrapping

Direct Effect

Indirect Effect

Decision Rule

Independent

Variables

Mediator Dependent

Variables

β

p β

p

H6a Neuroticism

Risk

Perception ST-D

0202 0002 -0002 0817 Direct-only

Non-Mediation

H6b Extraversion

0392 0000 0013 0309 Direct-only

Non-Mediation

H6c Openness

0075 0331 0009 0453

No effect

Non-Mediation

H6d Agreeableness

-0040 0606 -0020 0116 No effect

Non-Mediation

H6e Conscientiousness

0025 0708 0002 0849 No effect

Non-Mediation

H6f Neuroticism

Risk

Perception LT-D

0076 0140 -0003 0802 No effect

Non-Mediation

H6g Extraversion

0493 0000 0044 0005 Complimentary

Mediation

H6h Openness

0472 0000 0043 0006 Complimentary

Mediation

H6i Agreeableness

-0056 0276 0028 0034 Indirect-only

Mediation

H6j Conscientiousness

0333 0000 0040 0030 Complimentary

Mediation

Note ST-D= Short-term Investment Decision and LT-D= Long-term Investment Decision


Control variables Age-gtST-D (β= -0082 p=0155) Gender-gtST-D (β= 0118 p=0012) Income-gtST-D (β=0077

p=0328) Expect to receive inheritance-gtST-D (β= -0014 p=0820) Age-gtLT-D (β=0038 p=0438) Gender-gtLT-D

(β= -0018 p=0688) Income-gtLT-D (β= -0025 p=0569) Expect to receive inheritance -gtLT-D (β=0165 p=0001)

and Age-gtRisk Perception (β= -0069 p=0265)

Samra Chaudary

56

25 Discussion and Implications

Behavioral finance is a recent and emerging focal area in finance research Unlike

many other studies in this discipline (Li amp Liu 2008 Mayfield et al 2008 Oehler et al

2018 Oehler amp Wedlich 2018) which have used students as a proxy of potential investors

this study has empirically examined relatively a large number of individual equity investors

as well as professional investors The study investigated the effect of five personality traits

on investment decisions in short-term and in long-term It was found that not all personality

types had a significant effect on investment decisions Contrary to the findings of Mayfield

et al (2008) who reported that individuals who are high on neuroticism were likely to avoid

short-term investment decisions This study found a significant positive impact of

neuroticism on short-term investment decision than on long-term investment decision (H1a

and H1b) as shown in table 7 These findings get support from Brandstatter (2011) who

found that neurotic individuals were anxious low on risk propensity (Brandstatter 2011)

more risk-averse (Borghans Heckman Golsteyn amp Meijers 2009) less risk-tolerant (Pak

amp Memood 2015) and lacked entrepreneurship behavior (Zhao amp Seibert 2006 Zhao

Seibert amp Lumpkin 2010b) Therefore neurotic investors were found in this study to

invest in short-term investment horizon as short-term investment entails relatively lower

risk Some other plausible reasons of H1a findings could be that neurotic individuals are

reported to be impulsive (Rosler et al 2004) insecure tense (Costa amp McCrae 1992

Salgado 1997) and were found to exhibit compulsive buying behavior (Muller amp de

Zwaan 2010) Therefore neurotic individuals prefer to invest in short-term investments

than in long-term investments


57

For extravert personality (H2a) this study reaffirms the findings of Mayfield et al

(2008) that investors with extravert personality were more likely to take immediate

decisions and preferred to invest in short-term investment as they are more optimistic and

energetic Extravert individuals were reported to be more confident about their investment

decisions (Pompain amp Longo 2004) and were found likely to trade more frequently (Tauni

et al 2016) However positive relationship between extraversion and LT-D found in this

study (H2b) support previous findings that extravert individuals are also risk-takers

(Becker Deckers Dohmen Falk amp Kosse 2012a Pan amp Statman 2013) and optimist

(Costa amp McCrae 1992 Salgado 1997) therefore these factors may have led them to

invest in long-term investments

For openness personality (H3a and H3b) our findings are in support of (Zhao amp

Seibert 2006 Zhao et al 2010b) who found that individuals with openness to experience

show entrepreneurial (risk-taking) behavior They show high-risk propensity in many areas

of decision-making of their life including financial decisions (Brandstatter 2011) Hence

there is no association between openness with short-term investments and show a

significant relationship with long-term investment decisions Individuals with openness

personality are less risk-averse in financial decision-making (Prinz Gruumlnder Hilgers

Holtemoumlller amp Vernaleken 2014) tough-minded and with active imagination (Costa amp

McCrae 1992 Salgado 1997) as a result they showed a relationship with long-term

investments

The relationship of agreeable personality (H4a and H4b) with ST-D and LT-D was

found to be insignificant Agreeable personality had shown a negative relationship with the

willingness to take a risk (Brandstatter 2011) Empirical pieces of evidence have also

Samra Chaudary

58

shown that agreeable individuals are risk-averse (Borghans et al 2009) have low risk-

tolerance (Kubilay amp Bayrakdaroglu 2016) and have also shown extreme risk avoidance

behavior (Wang Xu Zhang amp Chen 2016) These individuals sometimes also show

juvenile and immature behavior (McCrae amp Costa 2008) they lack the skill for assessing

a better investment (Ivkoviacutec amp Weisbenner 2007) and showed lower return expectations

from their investments (Oehler amp Wedlich 2018) Therefore due to extreme risk

avoidance behavior and their lack of ability for assessing a better investment they probably

did not show association with short-term and long-term investment

The relationship of conscientiousness personality trait was not found significant

with short-term investment (H5a) but it was significant with long-term investment

decisions (H5b) The possible reason could be that conscientiousness individuals think

before acting (Brandstatter 2011) that gives them a long-term perspective As the stock

market was giving losses in the period of data collection due to some political uncertainty

therefore it is conjectured that it could be a possible reason for not investing in short-term

at that time Oehler and Wedlich (2018) found that conscientiousness individuals perceive

investments in stocks very risky and are very careful well organized and conscious about

their decision-making The authors also posited that individuals with conscientiousness and

agreeableness personality traits tended to have lower return expectations It may imply that

conscientiousness type would not like to invest in short-term as such investments offer

lower yields However on the other hand conscientiousness individuals are calculating

and show entrepreneurial (risky) behavior (Zhao amp Seibert 2006) and these aspects were

reinforced the significant relationship of conscientiousness with long-term investments

decision in this study


59

Based on the standardized path coefficients shown in table 7 extravert personality was

the strongest predictor of short-term investment decision followed by neuroticism

Similarly extravert personality was the strongest predictor of long-term investment

decision followed by openness conscientiousness and neuroticism (at a low significance)

respectively Moreover it was found that two out of five personality traits showed an

impact on short-term investment decision and four out of five showed associations with

the long-term investment decision One of the plausible reasons for this phenomenon could

be the bear market condition at the time of data collection which supports Prospect Theory

As investors are generally risk averse and therefore were not willing to invest in short-term

horizon (at the time of data collection) particularly Another possible reason could be that

long-term investment decisions have low transaction costs (Della Croce Stewart amp

Yermo 2011 Gray 2006 Warren 2014) and carry higher risk as well as higher returns

(Dimson Marsh amp Staunton 2017 Von Thadden 1995) Long-term investors are reported

to be rewarded by higher returns (Bansal amp Yaron 2004 Harrison amp Zhang 1999) As the

respondents of this study are stock investors and stocks have outperformed in longer time

horizons (Dierkes et al 2010)

Our results support TPB which proposes individualsrsquo behavioral willingness to invest

in the stock market as predicted by (East 1993 Mayfield et al 2008 Raut et al 2018)

The central idea of TPB is that planned behavior is determined by behavioral intentions

(Ajzen 2001) and that behavior can include conflicts between short-term and long-term

goals (Ajzen 1985 1991)

Furthermore this study linked personality traits and investment decisions through

risk perception in order to explore the relationship between five types of personality traits

Samra Chaudary

60

and investment decisions both short-term and long-term As shown in table 8 no

mediating effect of investorsrsquo risk perception between any personality type and short-term

investment decisions (H6a-H6e) However we found risk perception showed (different

types of) mediating effects between four personality types (except neuroticism- H6f) and

long-term investment decisions (H6g-H6j)

Precisely we found no direct effect of agreeableness (H6i) on long-term investment

decisions however the negative indirect effects of agreeableness on long-term investment

decision through risk perception were significant confirming indirect-only mediation This

implies that risk perception is the cause or in other words fully explains the relationship

between agreeable personality type and long-term investment decisions It seems agreeable

personality type has a higher risk perception that leads to a lower likelihood of investing in

long-term investment Moreover risk perception showed a complimentary mediating

effect for H6g H6h and H6j relationships These relationships already had significant

direct effects and now significant indirect effects too One potential reason of

complimentary mediation of risk perception is that there could be some other omitted

variables too that may mediate the relationship between extraversion openness and

conscientiousness personality types and long-term investment decision for example risk

tolerance or risk attitude etc Zhao et al (2010a) pointed out that complementary mediation

indicates to a theoretically interesting indirect effect It implies the possibility of presence

of more mediators and guides future researchers to explore more mediators that result in

an indirect only mediation model Another possible reason for complimentary mediation

could be the way risk perception was measured with subjective questions rather than

measuring it through an experimental design ie hypothetical lottery However Nosic and


61

Weber (2010) contended that asking onersquos risk attitude through the intuitive and

comprehensible question is a precise method than giving him a complex imaginary lottery

task Many studies have relied on asking subjective questions (Becker et al 2012a Josef

et al 2016 Pan amp Statman 2013) and the findings were more understandable when using

a subjective question than an experimental task (Becker et al 2012a)

Loewenstein et al (2001) had proposed a theoretical perspective termed ldquorisk as

feelingrdquo emphasizing that risk is a feeling which often affects individualsrsquo decisions

especially when such decisions involve risk and uncertainty They also posited that ldquorisk

as feelingrdquo mediates at least partially the relationship between an individuals cognitive

evaluation of risk and their behavioral response The findings showed support for RaF

theory related to the mediating role of risk perception As our result showed support for

hypotheses related to the mediating role of risk perception by emphasizing the mediating

role of risk perception in the relationship between three personality types and long-term

investment decisions Risk perception was not found to mediate relationships between

personality types and ST-D It is probably because short-term investment decisions are not

perceived relatively as risky as the long-term investment decisions are

The results of the relationship of personality types with ST-D and LT-D is imperative

for the financial planners to ensure that financial planners give to their customers are

obtaining best guidance This knowledge of the relationship between personality type and

investment decisions can also help professionals in recognizing the presence of behaviors

that may prevent their clients from attaining their short-term and long-term financial goals

(Baker et al 2017)

Samra Chaudary

62

It is recommended that money managers identify specific individualsrsquo personality types

with the aim to cater to investorsrsquo financial needs For example neurotic individuals can

be targeted for short-term investment and extroverts for both ST-D and LT-D The

importance of risk perception should also be considered while advising a specific

personality type with their investment decisions Moreover for an emerging economy like

Pakistan most personality types showed an association with long-term investments It may

be taken as a signal for the firms who want to raise capital from the market to issue long-

term securities Financial regulators such as Securities Exchange Commission of Pakistan

(SECP) should encourage investors to invest in short-term investments too by providing

them confidence and protection The findings of this research provide a meaningful picture

to the money managers of the developing economies where markets are vulnerable

26 Conclusion and Future Research

This paper investigated the influence of Big-Five personality types on short-term and

long-term investment decisions Moreover the mediating role of risk perception was also

tested between all five types of personalities and two types of investment decisions ie

short term and long-term It was found that investors with higher neuroticism and

extraversion personality traits were found more likely to take short-term investment

decisions Nonetheless investors with higher openness conscientiousness and

extraversion personality traits were found more likely to take long-term investment

decisions Risk perception was found to mediate effect between the relationships of

extraversion openness agreeableness and conscientiousness personality traits and long-

term investment decisions With the growth of the economy peoplersquos wealth increases

Hence there is a growing need that wealth management function is performed by


63

professional money managers This function involves understanding clientsrsquo requirements

and delivering financial services accordingly Gathering data from real equity investors

(especially from professionals ie brokers and the institutional fund managers) was quite

challenging task in this study These professionals were not willing to leave their trading

screens during the market hours (930 am -330 pm) even for a short time They filled the

survey questionnaire either after the market timings (late in the evening) or on weekends

A major contribution of this study is the fact that this is very first research of this kind in

the context of a developing economy Unlike other studies this study has utilized Big-Five

personality traits for investigating their impact on investment behavior for short-term and

long-term investments However this line of investigation needs more empirical evidence

especially from developing countries This study extended the general model of planned

behavior (Ajzen 1991) and risk as feeling model (Loewenstein et al 2001) to another

domain of social behavior that is financial investment with two separate components

(short-term and long-term) Given the importance of these theories in the field of social

behavior this is a rich paradigm for interdisciplinary contributions

It should be admitted that other than Big-Five Personality types there are various other

psychological factors that might affect individualsrsquo investment decisions these were not

accounted for in this study In this study the focus was only on equity traders and future

studies can opt to select other types of instruments to investigate if investors exhibit similar

behavior as found in this study Future studies could test the impact of emotions moods

and weather on investment decisions These constructs can be measured in different ways

for example the impact of live weather on the investors while trading their stocks can be

captured through an experiment But again such research design might be challenging as

Samra Chaudary

64

theses professional traders might not be willing to participate because of the responsibility

of peoplersquos money that they carry on their shoulders Leaving their trading screens during

market hours even for a short bit is immoral for them Future studies can also explore

other mediators (eg risk attitude risk appetite etc) that may result in an indirect only

mediation model Future researchers can also opt to classify investment decision in a

different way than classifying into long and short time horizons Another aspect that can

be investigated in the future studies is managersrsquo experience differences in experience may

result in different investing behavior

Salience and Investment Decisions

65

3 Paper II The Role of Salience in Investment Decisions

Differences Between Individual Investors and

Professional Investors

Abstract

The paper took a behavioral approach by making use of the prospect theory to

investigate the impact of salience on short-term and long-term investment decisions The

study also investigated the group differences for two types of investorsrsquo groups ie

individual investors and professional investors It further explored group differences

between female investors and male investors The study used partial least square based

structural equation modeling technique measurement invariance test and multi-group

analysis test on a unique data set of 277 active equity traders which included professional

money managers and individual investors It was found that salience has a significant

positive impact on both short-term and long-term investment decisions The impact was

almost 15 times higher for long-term investment decision as compared to the short-term

decision Furthermore multi-group analysis revealed that the two groups ie individual

investors and professional investors were significantly different from each other such that

the impact of salience on short-term and long-term investment decision was higher for

individual investors than for professional investors Moreover the parametric tests of

difference between two groups also showed that path coefficients of female investors were

significantly different from the path coefficient of male investors both for the short-term

decisions as well as for the long-term decisions The study has implications for financial

regulators money managers and individual investors as it was found that individual

investors and female investors suffer more with salience heuristic and may end up with

sub-optimal portfolios due to inefficient diversification Thus individual investors and

Samra Chaudary

66

female investors should be cautious in fully relying on salience and avoid such bias to

improve their investment returns The study concludes with a discussion of policy and

regulatory implications of the results and suggests how to minimize salience bias in order

to build optimum and diversified portfolios The study has contributed to the growing body

of applied behavioral research in the discipline of finance especially to the literature on

heuristics used by individuals while making investment decisions

Keywords heuristics salience familiarity bias investment decision behavioral finance

31 Introduction

Investment decisions are not merely driven by the fundamentals of a firm as advocated

by traditional finance theories but are also based on the attitudes (positive or negative) they

have developed for a specific corporation or a brand (De Vries et al 2017) Traditional

(standard) finance theories have been condemned in terms of their explanatory power and

the validity of their assumptions (Takahashi amp Terano 2003) Yalcin et al (2016) criticized

the two main propositions of traditional finance theory The first proposition postulates that

individuals behave rationally during the decision-making process as defined by the

expected utility theory (EUT) whereas the second proposition advocates that asset markets

are efficient (rational) in a way that they reflect correct prices and therefore endorsing the

efficient market hypothesis (EMH) International Capital Asset Pricing Model (ICAPM)

based on traditional portfolio theory proposed by Sharpe (1964) and Lintner (1965)

theorized that investors should invest in the world market portfolio of risky securities for

maximum risk-adjusted returns However investors behave irrationally and assign more

weight to domestic investments in their portfolios They ignore the potential benefits of

diversification (Ahearne et al 2004 Chan Covrig amp Ng 2005) Refraining from


67

investing in the world market portfolio could be due to salience bias or from familiarity

effect Investors tend to experience a strong bias towards holding stocks of their home

country or local area (Hirshleifer 2001) The idea of bounded rationality led to many

researches to discuss various types of behavioral heuristics eg familiarity (home) bias

(Ahearne et al 2004 French amp Poterba 1991) disposition effect (Barberis amp Xiong

2009 Odean 1998) representativeness (De Bondt amp Thaler 1985 Tversky amp Kahneman

1974) herding (Wermers 1999) overconfidence (Barber amp Odean 2001 Statman

Thorley amp Vorkink 2006) anchoring (Furnham amp Boo 2011 Tversky amp Kahneman

1974) framing (Choi Laibson Madrian amp Metrick 2004 Thaler amp Sunstein 2008)

This study investigates the impact of salience heuristic on investorsrsquo short-term and

long-term investment decisions It further examins the impact of salience on decision-

making between two groups of investors (individual investors and professional investors)

in the context of a developing economy Salience effect is one of the most robust cognitive

heuristics Salience was the most important heuristic among all as it showed the strongest

impact on decision-making (Yalcin et al 2016) Investors suffer most from salience than

other types of heuristics (Hirshleifer 2001)

Kumar and Goyal (2015) emphasized on the scarcity of studies on heuristics in

developing economies Developing countries have higher growth possibilities and

investors (individual and institutional) are more prone to invest in the stock market They

also highlighted that empirical studies based on the secondary data dominate the field and

there is a dearth of studies based on primary data in this area A handful of studies have

shown evidences that heuristics cause inevitable behavioral biases in investment decisions

from developed economies (Coval amp Moskowitz 1999 Hirshleifer 2001 Tversky amp

Samra Chaudary

68

Kahneman 1986 Wang et al 2011 Yalcin et al 2016) and from developing economies

(De Vries et al 2017 Jaiyeoba amp Haron 2016 Metawa et al 2019) The findings of

various studies were inconclusive in explaining these heuristic biases Therefore this study

has tried to provide the desired empirical evidence from the developing economy by using

a unique primary data set of professional money managers and individual investors who

have invested in the capital market

To the best of our knowledge the salience heuristic has never been systematically

studied with investment horizons (ie short-term and long-term) nor has its predictive

power been examined in both developed and developing economies (see appendix II) The

present study is the first one to contribute empirically by investigating salience which is a

critical factor in determining ST-D and LT-D The primary reason for this research is to

investigate if salience matters in investment decision-making for stock investors This

research also contributes to the understanding of the psychology of choices made by

investors in an emerging market Moreover understanding investorsrsquo behavior can help

investors to avoid familiarity bias and can improve their investment decisions in choosing

investment services products and plans The study provides a significant and meaningful

contribution to the prevailing young and emerging finance paradigm


321 Prospect Theory

The notion of heuristics was introduced by Simon (1955) who suggested a behavioral

model of rational choice He contended that individuals have bounded rationality and their

decisions are constrained by both external (environmental) and internal (mental) factors

The bounded rationality models are also called models of heuristic cognition The idea of


69

bounded rationality gave birth to the discipline of behavioral finance as many researchers

revealed pieces of evidence against the validity of rational decisions (De Bondt amp Thaler

1985 Kahneman amp Tversky 1979) This line of research picked up pace when Kahneman

and Tversky (1979) proposed the prospect theory and got further recognition after

Kahneman received the Nobel Prize for Economics in 2002 Prospect theory proposes that

when offered a gamble involving two or three outcome lotteries with some probability

investors make their decisions on the basis of the potential value of gains and losses rather

than on the final outcomes of lotteries They choose the one with the highest value This

value function is based on gains and losses rather than on levels of wealth The function is

concave in the area of gain indicating risk-aversion and is a convex in the area of loss

indicating risk-taking Moreover the gradient of the value function is generally steeper in

the area of loss than in the area of gain which indicates that investors are generally risk-

averse A loss would have a larger psychological impact on the decision-maker than a gain


measured (Kahneman amp Tversky 1979) Investors are more unpleasant by losses than they

are delighted by equivalent profits This phenomenon arises due to cognitive biases

(heuristics) that affect investorsrsquo assessment about expected value of these gains and losses

Many researches have successfully tested prospect theory in the domain of psychological

biases and decision-making (De Bondt amp Thaler 1985 Hirshleifer 2001 Ishfaq et al

2017 Metawa et al 2019 Odean 1998 Thaler amp Sunstein 2008)

322 Heuristics and Investment Decisions

Heuristics are described as lsquointuitive rapid and automatic systems (Shiloh Salton

amp Sharabi 2002) which decrease the complication of calculating possibilities and

Samra Chaudary

70

predicting the values to simple judgemental operations (Tversky amp Kahneman 1974)

Heuristics are also described as ldquorule of thumbrdquo which are developed for quick and efficient

decision-making (Mishra 2014) and have gained the attention of researchers (Yalcin et al

2016) Investors use these shortcuts due to inadequate time and information (Aronson

1999) Tversky amp Kahneman (1974) pointed out that cognitive biases arise as people use

heuristics These heuristics are generally effective but they argued that the use of heuristics

lead to biases under some circumstances and result in irrational decisions Similarly De

Bondt (1998) pointed out that heuristic cues can result in poor investment selections

because they usually do not relate to the firmrsquos profitability

323 Salience and Investment Decision

Salience is also known as familiarity bias (Yalcin at al 2016) and familiarity was

reported to breed investment (Huberman 2001) The notions of salience familiarity

availability cues and home bias are largely used interchangeably in the literature and

these notions are categorized under salience heuristics (Yalcin et al 2016) The idea of

availability heuristic was introduced by Tversky and Kahneman (1973) suggesting that

selective triggering provides grounds for salience and availability effects The key

behavioral assumption of Merton (1987) model was that investors invest in familiar stocks

due to the fear of an unknown Investors believe that the riskiness of an unknown stock

was very high Furthermore Heath and Tversky (1991) laid down behavioral foundation

of the familiarity bias They showed that individuals would like to gamble in a situation

where they think themselves well-informed or capable as compared to a situation where

they consider themselves unfamiliar or unacquainted They also reported that investors at

times are ready to sacrifice the benefits of diversification and focus on few corporations


71

with which they are ostensibly familiar Similarly when people encounter with two risky

choices they feel more pleasant picking the acquainted (salient) one particularly in fast

decision-making situations (Fox amp Tversky 1995) The panic of making an error was the

key reason when investors select the unfamiliar choice People recall and locate these

salient cues from their memory in order to choose without assessing whether they are

correct or not (Huberman 2001) It is unavoidable to observe similar biases because

investment decisions involve choosing the one right choice from several options that

require a vigilant evaluation The assessment process needs effort and time Hence in order

to address the challenge of the decision-making process investors make use of salient

knowledge (Yalcin et al 2016) Numerous researches reported that investors prefer to

invest in corporations with which they are more familiar because doing so tends to escalate

their level of assurance and hopefulness (Barber Odean amp Zheng 2005 Huberman 2001

Jain amp Wu 2000 Sirri amp Tufano 1998) Generally it was seen that people are inclined

towards investment in local firms (home bias) employees tend to purchase their own

companyrsquos stocks and fans prefer to invest in the stocks of their favorite teamrsquos irrationally

(Nofsinger 2005) Swiss respondents perceived those products less risky which were easier

to understand and this behavior was likely to be driven by the familiarity bias (Wang et

al 2011) Similarly investors from Finland tended to invest in those companies which

share the investorsrsquo native language and socio-economic background For instance Finnish

investors speaking Swedish language prefer to trade stocks of firms that have financial

statements in Swedish and have Swedish-speaking CEOs than those who speak Finnish

language (Grinblatt amp Keloharju 2001) In addition Jaiyeoba and Haron (2016) also found

that the investment decisions of Malaysian retail investors were influenced by

Samra Chaudary

72

psychological biases Malaysian investors were found patriotic and their investment

decisions were dependent on the comfortable feeling rather than quantitative investigation

These findings imply that investors were influenced by psychological biases Antoniou

Olusi and Paudyal (2010) reported that investors do not earn extra profits by investing in

international stocks Investors can earn similar profits by investing in a portfolio of local

securities

Baker and Ricciardi (2014) documented that familiarity bias prevails when

investors prefer acquainted investments though they know the evident gains from

diversification Investors exhibit a fondness for native securities (local bias) with which

they are more comfortable and are also skewed towards the portfolios of local assets (home

bias) Home bias denotes to the condition when investors favor to invest in local assets as

compared to international securities in their portfolio The potential reasons behind

investing in local stocks were familiarity investor protection economic development

stock market development capital control (Chan et al 2005) information asymmetry

transaction costs investment obstructions inflation hedging (Kumar amp Goyal 2015)

Likewise Riff and Yagil (2016) confirmed the presence of home bias in ten developed

countries They observed the bias in three different market conditions (bull bear and

normal) It was found that home bias increased during the bear market period This study

collected data in the bear market conditions Hence it is expected that salience determines


H1 Salience has a positive effect on short-term investment decision

H2 Salience has a positive effect on long-term investment decision


73

The outcome of familiarity bias could result in the suboptimal composition of

portfolios To mitigate familiarity bias investors should spread out a wider net and expand

asset allocation in their portfolio to reduce risk and increase diversification benefits

Investing globally assists to circumvent familiarity bias (Norden 2010 Baker amp Ricciardi

2014) Sizemore (2012) has suggested that to avoid familiarity bias investors who admire

a firmrsquos product should try to invest in one of the rivals because taking too accurate

investment decisions will be a mistake Giannetti and Koskinen (2010) investigated the

influence of investorsrsquo protection on portfolio returns and asset allocation Investors choose

to invest more in foreign stocks in countries where investorsrsquo protection was fragile In

addition investor protection showed a positive impact on shareholder returns It implies

that salience bias can be reduced and portfolio returns can be improved by increasing

investor protection

Kumar and Goetzmann (2003) found that investors who desire for skewness in

returns have relatively greater familiarity bias and are overconfident and hold a less

diversified portfolio Such bias was found to affect the returns ie investors with the least

diversified portfolio earned 240 lower return annually than the investors with the most

diversified portfolio on a risk-adjusted basis Investors who demonstrate overconfident

behavior generally face severe consequences (Baker amp Ricciardi 2014) and end up with

little investment returns as they fail to diversify their portfolios appropriately (Baker amp

Ricciardi 2015) One does not need to develop feelings towards any stock Loving a stock

will not respond back with love and developing hate for a stock will also not provide

contentment lsquoInvest in what you know which was also known as lsquoPeter Lynch biasrsquo will

make investors see only what they want to see in the stock (Sizemore 2012) If investors

Samra Chaudary

74

like a firm it did not essentially mean that it was a good investment and will yield a high

profit on investment This action may lead to investment in suboptimal portfolios which

can lead to lower returns or even losses (De Vries et al 2017) Less familiarity and high

information costs hinder investors from investing across the globe (Chan et al 2005)

Weber Siebenmorgen and Weber (2005) provides evidence that investing in a familiar

stock decreases risk perception of holding it Certainly this miscalculation of the risk of

familiar stock could possibly preserve home bias in investorrsquos portfolios

324 Institutional Investors and Salience

Coval and Moskowitz (1999) reported that professional money managers within

the US prefer to invest in small-sized domestic corporations whose headquarters are near

to their home town Likewise Strong and Xu (2003) documented that money managers are

likely to trade in familiar stocks and are prone to home bias Chan et al (2005) investigated

the investment of mutual funds from twenty-six developed and developing economies

They found that managers of these mutual funds collectively assign a bigger portion to

domestic stocks Results show that local investors give more importance to domestic

markets and the presence of home bias was significantly influenced by familiarity and

stock market development Foreign investors more or less give importance to the foreign

markets and international bias was significantly affected by capital controls economic

development and withholding tax Professional investment managers from the US and

Taiwan (Olsen 1997) and retail investors from Malaysia (Jaiyeoba amp Haron 2016) have

also exhibited a desirability bias and patriotic (home bias) behavior respectively Money

managers were reported not to invest in foreign stocks due to high transaction costs

currency risk asymmetric information and implicit risk which was embedded in


75

international markets Nonetheless behavioral reason for this phenomenon could be that

these institutional managers are overconfident and high on nationalism repentance and

social identification (Schwartz 2010)

Borges Goldstein Ortmann and Gigerenzer (1999) constructed portfolios on the

basis of the stocks recognition by German and American finance students (experts) and

laymen (people walking in the streets) The authors purchased the most identified stocks

and compared their returns against large mutual funds and stock markets in the US and

Germany They found that recognized stocks performed better than unrecognized stocks

Additionally the portfolio performance based on the ability of laymen to identify stocks

beats that of a portfolio based on recognition by finance students (experts) who should at

least have some passing interest in investing Individuals with less investment knowledge

can rely on recognition heuristic A professional investor who was familiar with most of

the stocks in the stock market cannot practice this heuristic According to Goldstein and

Gigerenzer (2002) recognition heuristic was a strong instrument and perhaps the only

strategy that works best in the situation of lack of knowledge It seemed that the lack of

information was perhaps a delightful thing for investors The evidence about experts who

made a bad investment portfolio on the basis of their identification of the stock proposed

that lack of knowledge was perhaps not too bad for investors (Forbes Hudson Skerratt amp

Soufian 2015)

325 Individual Investors and Salience

Individual investors in particular are unwise who hold stocks of their company

state or country instead of investing in an unknown or less familiar one (Baxter 1994

French amp Poterba 1991) Individual investors are less sophisticated and tend to take poorer

Samra Chaudary

76

investment decisions than financial advisors because individual investors are overconfident

and suffer from various biases (Baker et al 2017) De Vries et al (2017) investigated a

sample of students and found that when selecting between different companies these

potential shareholders in South Africa showed familiarity bias in their investing behavior

Tesar and Werner (1995) found that because of high transaction costs shareholders are

convinced to choose domestic equity instead of putting their money in international stocks

that yield higher returns Ahearne et al (2004) investigated the direct and indirect barriers

to foreign investment for US investors The direct barriers were the intensity of capital

controls high transaction costs (implicit and explicit) regulations on the institutions by the

country (restrictions on foreign ownership of equities) and the indirect barrier was

information cost Information cost was found to be the most important barrier which can

be reduced if the international company sets up its plant in the US It will make US

investors more familiar with its commodities US investors might invest in international

stocks of those firms with whose products they are most familiar Foreign companies that

do not minimize information costs by choosing not to list in the US regulatory system

have less weight in US investorsrsquo portfolios Kang and Stulz (1997) also reaffirmed that

investors from US tended to invest only in familiar international firms in Japan Likewise

Seasholes and Zhu (2010) found that investors are more likely to invest in domestic stocks

due to the existence of information asymmetry among investors Information asymmetry

is an unexpected obstacle to international investment in the home bias puzzle Karlsson

and Norden (2007) reported that individuals invest in their home country because they are

overconfident and they want to hedge against inflation Cooper and Kaplanis (1994) found

a negative association between earnings and inflation Moreover they elucidated that


77

investors hedge risk and get shield against inflation through local stocks and are vulnerable

to home bias This study investigates if the effect of salience on short-term investment is

different for individual investors and institutional investors Furthermore this research also

investigates if the effect of salience on long-term investment is different for individual

investors and institutional investors

H3 Salience has a stronger positive effect on short-term investment decision for individual

investors than for professional investors

H4 Salience has a stronger positive effect on long-term investment decision for individual


326 Gender and Salience

Numerous studies in the discipline of psychology and sociology showed that females

were more risk-averse than males (Arch 1993 Bollen amp Posavac 2018 Byrnes Miller

amp Schafer 1999 Hinz McCarthy amp Turner 1997) In making financial decisions

Bajtelsmit et al (1999) also posited that women showed higher risk aversion in the wealth

allocation into the defined contribution pension plan Olsen and Cox (2001) focused on

male and female investment professionals and found that men and women perceived and

responded to risk differently They suggested that cultural factors might be accountable for

this risk related gender effect

Gender had shown a significant effect on investment decision in the Egyptian financial

market (Metawa et al 2019) More men than women indicated that they found investment

exciting Men tended to be actively engaged in investments and change their assets in the

portfolio with time (Hira amp Loibl 2008) Many research studies found that males tended

to have a greater inclination towards both ST-D and LT-D than females (Mayfield et al

Samra Chaudary

78

2008 Bajtelsmit et al 1999 Hariharan et al 2000 Olsen amp Cox 2001) Tekce Yılmaz

and Bildik (2016) reported that young male Turkish investors suffered more from

familiarity bias Moreover familiarity bias showed a significant impact on the investment

performance of the Amman stock exchange However the impact was not found to be

statistically significantly different for female and male investors (Alrabadi Al-Abdallah

amp Aljarayesh 2018)

Anderson Fedenia Hirschey and Skiba (2011) conducted a survey in more than sixty

countries to determine the international diversification of professionally managed

portfolios It was found that portfolios from countries characterized by higher levels of

masculinity showed lower levels of familiarity bias and displayed more diversified

portfolios with foreign holdings Cao Han Hirshleifer and Zhang (2009) concluded that

higher familiarity leads to lower risk judgment Mohammadi and Shafi (2018) investigated

differences in the behavior of male and female investors using equity data of Swedish

firms They found a greater risk-averse behavior in female investors as opposed to male

investors Women were found less likely to invest in the stocks of younger firms and high-

tech companies Similarly in an investment decision realm women invest less and are

more risk-averse than men (Charness amp Gneezy 2007) In a sample from Switzerland

Wang et al (2011) also observed gender differences and argued that in general both

genders were impacted by the familiarity bias The asset classes that were easier to

understand were also considered less risky and vice versa Females considered equity more

difficult to understand and also perceived equity riskier than males did However there

was an exception that male respondents were not influenced by familiarity bias for blue-

chip stocks Even though males perceived that blue-chip shares were considerably easier


79

to understand than females did they still considered blue-chip shares were risky

investment which suggested that the males were not biased by their self-perceived

understanding about blue-chip stocks Karlsson and Norden (2007) reported that gender

and familiarity with risky assets are significant factors for the choice of home investment

for Swedish investors Moreover older males tended to be more home biased However

this result was not found for females Feng and Seasholes (2008) found that females and

males suffered equally from home bias in Chinese financial markets Home bias and

portfolio performance were not found statistically significantly different between males

and females Prast Rossi Torricelli and Sansone (2015) conducted a study in Netherlands

in which they constructed a ldquopinkrdquo portfolio (with shares that were thought to be more

familiar to women) and a ldquobluerdquo portfolio (with shares that were more familiar to men)

Respondents were asked to distribute pension wealth between a Treasury bond and a

pinkblue portfolio It was tested if familiarity with the portfolio increases femalesrsquo

participation in the stock market and risk-taking It was found that familiarity affects the

choice between bonds and stocks favoring bonds only for women above 60 years

Seiler Seiler Harrison and Lane (2013) examined familiarity bias in the real estate

context The authors investigated the impact of familiarity bias on perceived future home

price movements The respondents of the study perceived house as the largest investment

(and consumption good) The survey was conducted in 20 US states to examine

homeownersrsquo perception of future home price movements of the house in which they lived

They found that gender derived familiarity bias differences Women were found to

consistently suffer more from familiarity bias as compared to men The study also

suggested that the longer one lives in a house the greater is hisher affection to it and the

Samra Chaudary

80

more one is expected to ignore its bad features and emphasize on the good ones Hence

longer home lease resulted in the overestimation of future price movements as compared

to the other houses (with which respondents were less acquainted) In another real estate

study by Seiler Seiler Traub and Harrison (2008) familiarity bias was more significantly

prominent for females of North America The Asian women exhibited familiarity bias to a

lesser extent Ang de Jong and van der Poel (2014) also found that longer tenancy resulted

in greater familiarity bias Hence based on these arguments it can be proposed that for

women the impact of salience on investment decision would be higher as compared to men

Similarly salience bias would have a stronger impact on LT-D than ST-D Figure 31

illustrates the structural model about the relationship of salience with short-term and long-

term investment decisions across different groups

H5 Salience has a stronger positive effect on short-term investment decision for female

investors than for male investors

H6 Salience has a stronger positive effect on long-term investment decision for female


Figure 31 Structural model about the relationship of Salience with short-term and long-

term investment decisions


81


331 Measures

The study has adopted instruments from the existing literature for the in order to

measure the latent variables Three items of short-term investment decisions (ST-D) and

four items of long-term investment decision (LT-D) were adopted from Mayfield et al

(2008) The scale of salience had five items and was adopted from Yalcin et al (2016) All

the constructs were measured on a likert scale of 1 (strongly disagree) to 5 (strongly agree)

332 Methods


The data were gathered through a survey using a structured questionnaire from two

major metropolitan cities of Pakistan Lahore and Karachi The respondents for this survey

were those who have invested in Pakistan Stock Exchange The sample included

professional money managers working in financial institutions and individual investors

who have invested in the Pakistan Stock Exchange Professional money managers were

working in financial institutions like mutual fund companies (asset management

companies) brokerage houses or treasury departments of banks whereas individual stock

investors were from varying backgrounds Out of the total investorsrsquo population (corporate

and individual combined) of the country Karachi has 74 percent of investors and Lahore

has 18 percent of investors (Central Depository Company 2018) Hence by collecting data

from these two cities the aim was ensured that the data is coming from the investment hubs

of the country where 92 percent investors were located A total of 800 questionnaires were

rotated to collect data Five hundred and seventeen questionnaires were received and only

277 were found useable thus almost 35 percent was the response rate

Samra Chaudary

82

The investment industry of Pakistan is highly male-dominated hence our sample

consisted of almost 80 percent males and 20 percent females The sample had 59 percent

professional money managers and 41 percent individual investors Moreover 60 percent

respondents were married 37 percent were single and 3 percent were either separated or

divorced Eighty-seven percent respondents were employed 12 percent were business

owners and 1 percent of the sample was not employed Only 33 percent of the respondents

had expectation to receive inheritance or transfer of assets from the family and 67 percent

respondents did not expect any future inheritance Fifty-eight percent respondents

perceived that they were from the middle social class 36 percent perceived themselves in

upper middle class and only 3 percent perceived themselves to belong to the upper class

and 3 percent perceived themselves from a lower middle class Eighty-six percent

respondents responded their upbringing was in the urban areas and 14 percent respondents

had their upbringing in rural areas The average age of respondents was 32 years and

monthly income was Pak Rupee (PKR) 018 million per month respectively The average

education was 16 years On average respondents had 4 years of investment experience in

the Pakistan Stock Exchange and the average amount invested by them in stocks was PKR

10 million

3322 Data Analyses

This paper has opted to use partial least square based structural equation modeling


due to several reasons Firstly it does not require data to be normally distributed (Hair et

al 2012) and shows higher statistical power than CB-SEM for complex models with small

sample sizes (Reinartz Haenlein amp Henseler 2009) Secondly PLS-SEM has minimum


83

demand for measurement scales sample size and residual distribution (Wold 1985)

Thirdly this approach focuses on predictive analysis The goal of PLS-SEM estimation is

to maximize the variance of the endogenous variables explained by the exogenous

variables (Hair et al 2014) Fourthly to evaluate the statistical significance of the

parameter estimates Smart PLS3 software reports percentile bootstrap confidence intervals

(Hair et al 2011 Preacher amp Hayes 2008) Bootstrap sampling procedure takes

subsamples from the original sample of observation and estimates the model parameters of

each subsample and then report significance of the estimated coefficients thereby

substantiating the robustness of the results (Hair et al 2012) This sample then tests the

significance of the estimated coefficients (Henseler et al 2009) Lastly PLS can be used

for theory confirmation as well as to propose where relationships may or may not present

(Chin 1998) PLS is also beneficial for exploratory research and for initial phases of theory

development (Fornell amp Bookstein 1982)

Results from PLS-SEM method are as worthy (and conservative) as from CB-SEM

approach (Hair et al 2014) Although PLS-SEM has some weaknesses for example

results tend to overestimate the factor loadings and underestimate structural relationship

and R-square Similarly CB-SEM also has some shortcomings ie results tend to inflate

the structural path coefficients and underestimate factor loadings Bolander et al (2015)

have proposed that PLS-SEM is a conservative approach Table 31 depicts the

correlations descriptive statistics and square root of Average Variance Extracted (AVE)

of the latent constructs


term investment decision and salience Pearsonrsquos correlation value between short-term

Samra Chaudary

84

investment decision and long-term investment decision was 0518 (p=0000) and between

short-term investment decision and salience was 0359 (p=0000) Similarly long-term

investment decision also showed positive correlation with salience with Pearsonrsquos

correlation value of 0515 (p=0000) Salience was found to be more positively correlated

with long-term investment decision than with short-term investment decision


Factors Mean Standard

Deviation

Short-term

Investment

Decision

Long-term

Investment

Decision

Salience

Short-term

Investment

Decision

3113 0779 (0742)

Long-term

Investment

Decision

3311 0846 0518 (0728)

Salience 3039 0827 0359 0515 (0728)

Note Diagonal values in parentheses are values of square root of AVEs


34 Results


Factor loadings for each indicator of the latent construct were 065 or above and

were found to be statistically significant as the values for t-statistics were above 196

(Anderson amp Gerbing 1988 Hulland 1999) Bootstrapping with 2000 subsamples was

done to compute t-statistics of each factor loading (Henseler et al 2009) A minimum of

three items must load significantly on each factor in a multidimensional scale

(Raubenheimer 2004 Velicer amp Fava 1998) and that was the case here The estimates of

standardized factor loadings for short-term investment decision ranged from 0675 to 0775

(tgt196) for long-term investment decision the range was 0713-0758 (tgt196) and for

salience the range of items loading was found to be 0651-0798 (tgt196)


85

Internal consistency of latent constructs was measured through composite

reliability (CR) which should be higher than 07 (Hair et al 2012) and that was the case

for all latent constructs in this research The estimates of composite reliability were 0786

for short-term investment decision 0819 for long-term investment decision and 0889 for

salience Convergent validity was computed through average variance extracted (AVE)

which met the benchmark of 050 or higher (Hair et al 2012) for each latent construct


investment decision and 0531 for salience

Discriminant validity of each latent construct was measured through two


ratio of correlations criteria (Henseler et al 2015) According to Fornell-Larcker criteria

the square root of AVE of each latent construct should be greater than its inter-factor

correlations with all other latent constructs (Hair et al 2012) Moreover the Heterotrait-

Monotrait (HTMT) ratio should be less than one as shown in table 33 Common method

bias and collinearity among constructs were checked for each construct through variance

inflation factor (VIF) test at the factor level The test was carried out twice with both

dependent variables once with short-term investment decision and once with the long-term

investment decision No common method bias was found in both the tests as the VIF values

for all the factors were less than 33 (Kock 2015) The results of the measurement model

are reported in table 32

Samra Chaudary

86


Constructs Sources Items Statements

Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)

I intend to put at least half of my investment

money into the stock market 0675 10544

I intend to engage in portfolio management

activities at least twice per week 0775 18354

I intend to compare my portfolio performance to

that of professional managers 0772 16482

Long-term

Investment

Decision

(Mayfield

et al

2008)

I intend to save at least 10 of my gross earnings

for investingsavingretirement purposes 0758 21972

I intend to have a portfolio that focuses on multiple

asset classes (ie stocks bonds cash real estate

etc)

0713 15358


I intend to manage my portfolio for maximum

gross return rather than tax and cost efficiency 0714 18643

Salience (Yalcin et

al 2016)

Expert opinions in written and visual media should

be taken into consideration when investing 0744 20780

A companyrsquos stock which is often in the media

with favorable news coverage should be preferred

when investing

0668 15584

To invest in companies that have a good brand

name is important to me 0798 32446

It is risky to invest in relatively unknown public

companies rather than known ones 0770 20525

I believe that investors should purchase the stock

of the company they work for if it is well run 0651 13806




(CR)




Salience 0849 0531


Factors Long-term Investment Decision Salience Short-term Investment

Decision

Long-term Investment Decision

Salience 0691



87


The following section reports the direct effects of salience on short-term investment

decision and long-term investment decisions The parameter estimates (path coefficients)

of the structural model were estimated along with their significance The significance of

coefficients was calculated using a bootstrapping with 5000 subsamples (Henseler et al

2009) The coefficient of determination (R2) for each of the latent dependent (endogenous)

variables were not below 010 (Falk amp Miller 1992) Moreover the effect size was

reported for each direct effect through F- square test (Cohen 1988) with a cut-off at 002

015 and 035 for a small medium and large effect size of the independent variable

(Henseler et al 2009) The predictive relevance of the model was also estimated by




et al 2012) A value of 08 or higher is recommended as sufficient in behavioral studies

for the power test (Cohen 1988)

Table 35 summarizes the results of the direct effects The hypothesized relationship

between salience and ST-D (H1) was found significantly positive with large effect size (β=

03295 p= 0000 f2= 0150) Similarly the association between salience and LT-D (H2)

was also found significantly positive with almost 15 times higher beta magnitude and with

a large effect (β= 05017 p= 0000 f2= 0363) The coefficient of determination of salience

with LT-D is higher (R2= 0340) than the coefficient of determination with ST-D

(R2=0224) Hence relationships with LT-D have shown more explanatory power than the

relationships with ST-D The values of Q2 were above zero representing that each

Samra Chaudary

88

exogenous construct (salience) in the model has predictive relevance for both endogenous

latent variables (ST-D and LT-D) All the hypotheses have shown very strong statistical

power ie 0999 or above which shows a very high probability of the presence of the

relationships between all exogenous latent variables and endogenous latent variables A

high value of power test also reaffirms the appropriateness of the sample size

We have included age gender income education size of the investment portfolio

and investment experience as control variables in our model These variables have

relevance in the model of salience (heuristic) and investment decisions (Yalcin et al

2016) Agarwal et al (2007) also reported that age had an effect on financial decision In

addition to that other studies have also stated that males were more inclined towards both

short-term and long-term investments than females (Bajtelsmit et al 1999 Hariharan et

al 2000 Mayfield et al 2008 Olsen amp Cox 2001)

Results of control variables showed that only age and investment experience

showed a significant impact on ST-D and LT-D Age showed a significant inverse

relationship with both types of investment decisions Older investors tended to take less

short-term investment decisions than long-term investment decisions Moreover the more

investment experience one has the more short-term investment decision heshe takes

Table 35 Results of Direct Effects of Salience on ST-D and LT-D


Coefficient p-values f2 R2 Q2

Statistical

Power

H1 Salience -gt ST-D 03295 0000 0150 0224 0091 0999

H2 Salience -gt LT-D 05017 0000 0363 0340 0146 1000

Note ST-D= Short-term Investment Decision LT-D= Long-term Investment Decision


Control variables Age-gtST-D (β= -0245 p=0004) Income-gtST-D (β= -00021 p=0979) Education-gtST-D (β=

00237 p=0728) Investment Experience-gtST-D (β= 0240 p=0001) size of investment portfolio -gtST-D (β= -00257

p=0703) Age-gtLT-D (β= -0147 p=0024) Income-gtLT-D (β= -0041 p=0809) Education-gtLT-D (β= 0636

p=0308) Investment Experience-gtLT-D (β= 0148 p=0047) and size of investment portfolio -gtLT-D (β= 0014

p=0736)


89

343 Measurement Invariance Assessment

In order to conduct multi-group analysis (MGA) one fundamental condition is to

establish the measurement invariance between the groups (Steenkamp amp Baumgartner

1998) ie the measurement model is not statistically different between two groups

Measurement invariance inquires the vital question if the measurement of latent variables

differs between groups (Xu amp Tracey 2017) Therefore any moderations that we may

observe should be due to the differences in the type of investors rather than measurement

differences For this purpose measurement invariance of composite models (MICOM) test

was performed in order to establish that the measurement of the (outer) model is same

between 2 groups (Henseler Ringle amp Sarstedt 2016)

The MICOM method comprises of three steps (1) to establish configural invariance

(ie equal parameterization and model estimation) (2) to establish compositional

invariance (ie equal indicator weights) and (3) to establish the equality of composite

mean values and variances If configural and compositional invariance (step1 and step2)

are confirmed partial measurement invariance is supported which permits one to compare

the path coefficients between the groups Additionally if partial measurement invariance

holds and the composite means and variances are equal between the groups (step 3) full

measurement invariance is established

Running MICOM in SmartPLS automatically establishes configural invariance

(step1) (Garson 2016) The statistical output does not apply to this step and is not shown

The composite or measured invariance (step 2) is examined The correlation (c) should not

be significantly different from one As shown in table 36 all the correlation (c) in our

original data are within the confidence interval hence the null hypothesis cannot be

Samra Chaudary

90

rejected and therefore no c is significantly different from 1 (p gt 005) supporting the

compositional invariance of our model The term c value denotes the correlation between

composite scores using the weights attained from the first group (professional investor)

and composite scores using the weights attained from the second group (individual

investor) Step 3 evaluates the means differences (step 3a) and variances differences (step

3b) between the groups The null hypothesis is that the differences between the means and

the variances of the variables are 0 The results showed that in both cases (steps 3a and 3b)

all the composite means and variances were equal between the 2 groups namely individual

investors and professional investors

The MICOM test was performed in smart PLS with 5000 permutations (Ringle

Wende amp Becker 2015) The results of MICOM test are presented in table 36 confirmed

the partial measurement invariance for both the groups (individual investors and

professional investors) supporting the pertinence of the multi-group test (Henseler et al

2016 Keller amp Siegrist 2006a)

Similarly MICOM test was executed to establish that the measurement model is

same between 2 groups namely female investors and male investors The correlation (c)

were not significantly different from one (step 2) The results also showed that in both

cases (steps 3a and 3b) all the composite means and variances were equal between the 2

groups namely female investors and male investors To sum up the statistical outcome of

the MICOM test is shown in table 37 confirmed the partial measurement invariance for

both the groups (ie female investors and male investors) supporting the appropriateness

of the multi-group analysis test (Henseler et al 2016 Keller amp Siegrist 2006a)


91

Table 36 Measurement Invariance of Composite Model of Individual Investors and Professional

Investors

Step 2 Correlation c value (=1) 95 confidence

interval

Permutation

p-value

Compositional

invariance

ST-D 0965 [0941 1000] 0254 Yes

LT-D 0985 [0968 1000] 0097 Yes

Salience 0992 [0980 1000] 0235 Yes

Step 3a Mean Difference (=0)

(Individual Investors -

Professional Investors)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -0287 [-0237 0243] 0022 No

LT-D -0119 [-0247 0233] 0327 Yes

Salience -0077 [-0244 0217] 0534 Yes

Step 3b Variance Difference (=0)



95 confidence

interval

Permutation

p-value

Equal variances

ST-D -0006 [-0350 0308] 0796 Yes

LT-D -0166 [-0305 0263] 0249 Yes

Salience -0099 [-0292 0302] 0494 Yes


5000 permutations two-tailed 005 significance level

Table 37 Measurement Invariance of Composite Model of Female Investors and Male Investors


interval

Permutation

p-value

Compositional

invariance

ST-D 0946 [0826 1000] 0017 No

LT-D 0986 [0961 1000] 0934 Yes

Salience 0989 [0970 1000] 0235 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -00006 [-0300 0313] 0693 Yes

LT-D -00007 [-0296 0296] 0100 Yes

Salience -00009 [-0308 0300] 0186 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal variances

ST-D 0025 [-0357 0443] 0330 Yes

LT-D 0030 [-0337 0419] 0402 Yes

Salience 0019 [-0341 0387] 0699 Yes



Samra Chaudary

92

344 Multi-group Analysis

Once the measurement invariance model was established a multi-group analysis

was then executed Multi-group analysis (MGA) has numerous benefits a) It permits to

analyze whether parameters of the measurement model andor path model are alike

(invariant) between 2 groups namely individual investors and professional investors

(Chin Mills Steel amp Schwarz 2016) b) It predominantly delivers a robust check of the

validity of the measurement model and replicability of the structural model in different

contexts (Calvo-Mora Navarro-Garciacutea Rey-Moreno amp Perianez-Cristobal 2016) c) It is

also useful to draw analogy within a research whether to evaluate theoretical differences

between subgroups of the same population or across populations in the instance of

culturally diverse study (Fawcett Wallin Allred Fawcett amp Magnan 2011) Two groups

of investors (individual investors and professional investors) were used for multi-group

analysis It was found that both groups were statistically significantly different from each

other such that the impact of salience on short-term decisions and for long-term decisions

was higher in case of individual investors than in case of professional investors

Furthermore it was found that the path coefficient difference for short-term investment

decisions is almost 15 times higher than the path coefficient difference for long-term

investment decisions The difference in path coefficients implies that individual investors

suffer more from salience bias than professional investors especially for short-term

investment decisions in case of both groups The direct effect of salience on the short-term

and long-term investment decision for both groups are shown in table 37 The parametric

tests of difference between the two groups are reported in table 38 show that path

coefficients of individual investors were significantly different from path coefficient of


93

professional investors both for ST-D and LT-D Though path coefficient difference was

large in case of short-term decision being influenced by salience

Table 38 Direct Effects for Professional Investors and Individual Investors

(Professional Investors) (Individual Investors)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0236 0000 2519 0097 0078 0477 0000 7502 0337 0242

Salience -gt

LT-D 0454 0000 8148 0315 0229 0609 0012 1065 0655 0384



Table 39 MGA Results of Professional Investors and Individual Investors

Hypotheses Relationship

Path

coefficient

diff

Individual

-

Professional

p-value

Individual

vs

Professional

t-value

Individual

vs

Professional

f2 diff

Individual

-

Professional

R2 diff

Individual

- Professional

H3 Salience -gt

ST-D 0241 0023 2291 0235 0175

H4 Salience -gt

LT-D 0155 0048 1986 033 0168


Bootstrapping based on n=5000 subsamples


In addition to individual and professional investors two groups of investors (ie

female and male investors) were used for multi-group analysis It was found that both

groups (female and male) were significantly different from each other such that the impact

of salience on short-term decisions and for long-term decisions was higher in the case of

female investors than in the case of male investors Furthermore it was found that path

coefficient difference for short-term investment decisions is almost 2 times higher than the

Samra Chaudary

94

path coefficient difference for long-term investment decisions The difference in path

coefficients implies that female investors suffer more from salience bias than male

investors for both short-term and long-term investment decisions The direct effect of

salience on the short-term and long-term investment decision for both groups (ie female

and male) are shown in table 310 The parametric tests of difference between two groups

are reported in table 311 show that path coefficients of female investors were significantly

different from path coefficient of male investors both for ST-D and LT-D Though path

coefficient difference was large in case of short-term decision being influenced by salience

Table 310 Direct Effects for Males and Females

(Females) (Males)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0642 0000 8032 0775 0419 0316 0000 4496 0120 0104

Salience -gt

LT-D 0692 0000 1051 0992 0483 0516 0000 1086 0374 0269



Table 311 MGA Results of Males and Females


Path

coefficient

diff

Female

-

Male

p-value

Female

vs

Male

t-value

Female

vs

Male

f2 diff

Female

-

Male

R2 diff

Female

-

Male

H3 Salience -gt

ST-D 0326 0001 3222 0655 0315

H4 Salience -gt

LT-D 0176 0024 2013 0618 0214





95


The results show that salience had shown a significant positive impact on both

short-term and long-term investment decisions This finding got support from Mousavi and

Gigerenzer (2014) who stated that besides the availability of plenty of information which

is often available individuals make their decisions which are based on gut feelings This

result was also consistent with Wang et al (2011) who posited that individuals who have

a better knowledge of an asset class perceive it to have a lower risk and a higher expected

return That could be one of the reasons for having a significant positive sign of salience

with both ST-D and LT-D Giannetti and Koskinen (2010) reported that stronger investor

protection leads to higher domestic investments Correspondingly Securities Exchange

Commission of Pakistan is fully determined to ensure investor protection to provide

maximum information and to promote investor confidence in order to boost financial

planning and decision-making (SECP 2016) Another plausible reason for this

phenomenon could be due to the bear market condition at the time of data collection as

suggested by Riff and Yagil (2016) Therefore investors have shown an impact of salience

heuristic on domestic stock market investments in short-term as well as in the long-term

Furthermore it was found that beta coefficient for long-term investment was one and a half

times higher and effect size was almost two and a half times higher than the beta coefficient

and the effect size for short-term investment The possible reason for this result could be

that investing in a familiar stock in the long-term would increase investorsrsquo trust and

confidence about higher returns Investors were also found to invest in familiar short-term

investments but the impact was seen higher for long run as long-term investment yields

higher return Familiarity breeds trust and trust establishes long-term commitment (Gulati

Samra Chaudary

96

1995 Wilson McNellis amp Latham 2018) Moreover familiarity knowledge and

confidence are positively associated (Shawahna et al 2017) Familiarity influences

confidence which in turn affects buying decisions (Laroche Kim amp Zhou 1996) and long-

term commitments (Ganesan1994) In addition evidence have shown that markets are

expected to be in equilibrium in the long run (Hopenhayn 1992 Marshall 1961 Shachat

amp Zhang 2017) But in short run higher volatility of small-capitalization stocks is reported

to result in significant capital losses (Roll 1983)

Investors like to hedge their losses (Odean 1998) so they do not repent later

Therefore investing in familiar long-term securities is likely to make them feel relatively

safe in terms of risk and return Healthier long-run growth prospects are reported to reward

long-term investors (Bansal amp Yaron 2004 Harrison amp Zhang 1999) and stocks have

outperformed in longer time horizons (Dierkes et al 2010) Baker and Ricciardi (2014)

have also recommended investing in long-term for superior performance than short-term

investments They suggested that investors should invest in the long-term rather than

investing in short-term portfolios A better performance of short-term investment may be

found due only to good luck than stock selection skill or market timing expertise

In the multi-group analysis this study found that individual investors and money

managers were influenced positively by the impact of salience in their short-term and long-

term investment decisions Moreover both groups were significantly different from each

other such that professional money managers were less influenced by salience to invest in

familiar stocks as compared to individual investors in short-term as well as in long-term

The effect of salience was seen higher for long-term investment than for short-term

investment decision The findings are aligned with (Baxter 1994 French amp Poterba 1991)


97

who found that individual investors especially invest in more familiar stocks Gigerenzer

(2014) also found that managers acknowledge that almost half of their professional

decisions are intuitive decisions These decisions are based on their familiarity after

acknowledging all the available information Sternad and Kennelly (2017) also report that

managers have a long-term orientation in their decisions which is determined by

institutional factors Managerial long-run orientation can also generate and sustain higher

returns for their clients The findings also gave an indication that professional money

managers were more likely to strive for diversified and optimal portfolio construction for

their clients in the long run as they were found to relying less on salience heuristic Long-

term securities possess higher risk as well as a higher return (Dimson et al 2017 Von

Thadden 1995) It was also found that the path coefficient difference between individual

investors and professional investors for short-term investment decisions was almost 15

times higher than the path coefficient difference for long-term investment decisions These

findings get support from (Fox amp Tversky 1995 Mishra 2014) that heuristics are used for

quick and efficient decision-making

Professional money managers should rely less on salience heuristic in order to

achieve a diversified and optimal portfolio An optimal portfolio provides maximum

returns (wealth) at a given level of risk (Markovitz 1952) More wealth increases

household consumption The high consumption should strengthen the overall economy

(Poterba 2000) Moreover high returns from optimal portfolios would allow individuals

for early retirement as they have higher savings which enhances the welfare of the society

(Chai Horneff Maurer amp Mitchell 2011) Higher yields would also encourage investors

to invest more in the stock market (Daniel amp Hirshleifer 2015) which could lead to higher

Samra Chaudary

98

productivity and growth of capital markets (Pagano 1993) and result in economic growth

(Paramati Ummalla amp Apergis 2016)

The study also investigated the group difference between female investors and male

investors It was found that female and male investors were significantly different from

each other The impact of salience was found to be higher for females than for males for

both short-term and long-term investment This supports the work of Seiler et al (2013)

and Seiler et al (2008) who also found that women consistently suffered more from

familiarity bias when they were asked to value their homes (in which they resided) in the

future Females tended to be more risk-averse then men (Arch 1993 Bollen amp Posavac

2018 Byrnes et al 1999 Hinz et al 1997) and were found with lower level of comfort

with maths (Hayes amp Kelly 1998) could be another reason of them investing in familiar

investments only in both short-term and long-term Moreover Estes and Hosseini (1988)

reported that women had substantially less confidence in their investment decisions than

men This may be one of the reasons for the observed difference in higher salience for

women towards their investment decision for both long-term and short-term In addition to

that men tended to be over-confident in stock trading (Barber amp Odean 2001) and female

investors were likely to assign more weight to probability of loss and uncertainty than

male investors do (Olsen amp Cox 2001) could be other plausible cause of this phenomenon

The beta coefficients of LT-D were found higher than the beta coefficients for ST-D for

both men and women This outcome was also consistent with the explanation by Ang et al

(2014) who posited that lengthier tenure leads to greater familiarity bias

Investors should be mindful that salience investment strategy could also give rise

to the mispricing of the familiar companiesrsquo stocks High demand for familiar firmsrsquo stocks


99

would lead to an upsurge in stock price resulting in the overvaluation of those shares This

price rise will only withstand if familiar firms provide ample returns to support higher stock

prices However if familiar firms are not able to provide adequate returns their stock price

would ultimately settle downwards If investors successfully recognize the mispriced

equity triggered by familiarity bias they might realize profits from subsequent arbitrage

opportunities (De Vries et al 2017)

To sum up findings of this research conform with the Prospect theory (De Bondt

amp Thaler 1985 Hirshleifer 2001 Ishfaq et al 2017 Kahneman amp Tversky 1979

Metawa et al 2019 Odean 1998) The results of this study will help money managers to

improve their investment decisions by relying less on salience and investing their clientsrsquo

wealth globally for better diversification Moreover investment professionals can also

advise their clients how to avoid familiarity bias during the investment decision-making

process Salience is a critical heuristic to understand and to improve the quality of

investorsrsquo investment decision An effective financial adviser would require an

understanding of investorsrsquo psychological biases to implement well-planned investment

strategies The findings will also help regulatory authorities such as SECP to improve

investor protection rights and to enhance the functioning of stock market Professional

money managers from brokerage houses mutual funds and other financial institutions may

also deliver superior service and provide sound guidance to their customers once they are

aware of salience heuristic which can hamper their investment decisions Domestic firms

should publicly list their stocks in international stock exchanges to increase the familiarity

and decrease the information cost and such actions may encourage foreigners to invest in

stocks of such companies (Ahearne et al 2004)

Samra Chaudary

100

Women prefer less risk and are less confident than men when it comes to

investment decision so it is important to identify areas of their concerns related to money

matters An investment literacy program for women is needed especially in a developing

country like Pakistan This investment understanding could shape womenrsquos confidence and

influence their money matters and investment decision Moreover females represent a tiny

sample in the financial industry Therefore there is an immense need to target more females

in the investment industry to boost savings in the economy

Lastly the findings will help both national and international financial regulatory

bodies and supervisory authorities for their better performance in managing financial

anomalies triggered by behavioral heuristics Foreign firms should also work towards

awareness transparency and investor protection so that investors can have confidence in

an international firm and they can diversify their portfolios internationally to enjoy higher

returns


This study has made an attempt to investigate the influence of salience on long-

term and short-term investment decisions of the individual investor and professional

investors The study presented robust findings indicating the presence of the salience bias

for an emerging stock market It was found that salience has a significant positive impact

on both short-term and long-term investment decisions Furthermore the impact of salience

on short-term and long-term investment decision was significantly higher for individual

investors than for professional investors In addition to that the impact of salience on short-

term and long-term investment decision was significantly higher for females than for male

investors


101

The outcomes of this study are likely to assist in understanding the decision-making

perspectives of local investors The findings of this groundwork will aid to understand the

decision-making perspectives of local investors The instruments used in this study were

found to be valid and reliable and had been used in studies done in developed economies

It is critical that the same instrument should be used to generalize results across different

emerging economies as well especially As there were only 20 percent females in the

sample due to male-dominated industry the results need generalization from other

countries Future studies can investigate the impact of other heuristics on investment

horizons Future researchers can also pursue the inquiry if gender interacted with other

demographic variables such as marital status age and income have different investment

decisions The sample for this study was collected in the time of bearsrsquo market conditions

Upcoming research can collect data in bulls market and investigate if salience bias still

persists This study has relied on self-reported and perceptual data to measure heuristics

Future studies can make use of objective measures of heuristics However developing such

a measure for investors could be tremendously challenging Future research can also

investigate the influence of salience bias on investments decision by comparing investment

performance results in familiar and unfamiliar firms Market inefficiencies due to the

presence of asymmetric information are likely to lead to selection bias and future

researchers can explore this area Such investigation may help identify the presence of

potential arbitrage profit opportunities

Samra Chaudary

102

4 Paper III Love of Money and Investment Decisions

Interaction of Income and Inheritance

Abstract

The paper takes a behavioral approach by making use of the Prospect theory the

theory of Planned Behavior and Monetary Intelligence theory to investigate the impact of

Love of Money (LoM) on short-term and long-term investment decisions It further

investigates the moderating effect of current income and expectation of receiving an

inheritance in the future The study uses partial least square based structural equation

modeling technique on a data set of 277 active equity traders which included professional

money managers and individual investors It was found that LoM has a significant positive

impact on both short-term and long-term investment decisions of respondents

Furthermore it was found that income moderated the relationship between LoM and ST-

D and did not moderate the relationship of LoM with LT-D The expectation of receiving

future inheritance also moderated the relationship between LoM and both short-term and

long-term investment decisions The results offer implications for the marketing of

financial institutions like asset management companies brokerage houses and investment

banks It may be possible to identify potential investors by means of segmentation based

on money attitudes current income and future wealth possession The study has

contributed to the growing body of applied behavioral research in the discipline of finance

especially to the literature on LoM used by stock investors while making investment

decisions

Keywords Love of Money money attitudes income inheritance investment

decision behavioral finance

Love of Money and Investment Decisions

103

41 Introduction

In the recent time period people who were attracted by high profits on their

investments lost their fortune in crises eg US financial crisis- 2008 Europe loan crisis-

2010 and Asian financial crisis- 1997 2012 Consequently people all over the world are

facing more complex financial decisions than in the past (Shih amp Ke 2014) Financial

decision-making is a key factor for long-term financial wellbeing (Imasheva amp Kim 2017

Tang et al 2018a) Some of the important reasons for the upsurge in individualsrsquo

investments are the concern for their retirement earnings (Clark-Murphy amp Soutar 2004

McKenzie amp Liersch 2011) education expenses and health care expenditures (Greenberg

amp Hershfield 2019) Gunnarsson and Wahlund (1997) suggested another cause to

understand individual financial plans They observed that several economies have

encountered with increasing competition as a result of deregulation of the financial

industry social security cuts and tough economic conditions This phenomenon has made

it crucial for finance companies to adjust their advertising plans from supply-side to more

demand-side MacGregor and Slovic (2000) conducted research on a sample from the US

who was presently at or near their earnings peak and thought that retirement planning for

future income is crucial Sixty-seven percent of the sample reported of having a long-term

investment portfolio in marketable certificates they see portfolio returns as retirement

earnings which were essential to complement social security and pensions

Financial decisions are predicted by attitudes (Akhtar amp Das 2019) which are

highly influenced by socioeconomic status (Greenberg amp Hershfield 2019)

Understanding of these attitudes is as financial planners devise effective strategies for their

clientsrsquo wealth management (Britt 2016) Attitudes influence the behavior and intentions

Samra Chaudary

104

to invest (Mahastanti amp Hariady 2013) One important attitude in this context is investorsrsquo

attitude towards money and it is one of the key factors influencing an individualrsquos financial

behavior (Shih amp Ke 2014) Money attitudes have gained attention for their hypothesized

relationship with financial behavior (Klontz amp Britt 2012)

Feldmanrsquos viewpoint of money is still pertinent Individualsrsquo decision process is

affected one way or another by the attitude towards money This includes the

consideration of whether to buy or not (Oezgen amp Bayoglu 2005) Money is the instrument

of commerce and a measure of value (Smith 1776 1937) Money is one of the most

important factors in our lives (Lodder Ong Grasman amp Wicherts 2019 Wernimont amp

Fitzpatrick 1972) The meaning of money lies in the eye of the beholder (McClelland

1967) and can be perceived as a ldquoframe of referencerdquo in everyday lives (Tang 1992)

Individuals use their money attitudes to frame their daily matters (Tang 1993) Money

attitudes are values that individuals associate with money (Keller amp Siegrist 2006a)

People think about money but rarely discuss their financial matters income and stock

investments openly or discuss it with a few people only (Rubenstein 1981) An

individualrsquos money attitudes have roots in hisher childhood and it fairly persists all his

over their life (Tang amp Gilbert 1995)

Stock market investment offers a huge potential for financial returns Yet people

hesitate to invest their money in stocks instead they put their money more often into

savings deposits or real estate (Gunnarsson amp Wahlund 1997) This can be expected

according to prospect theory (Kahneman amp Tversky 1979 Tversky amp Kahneman 1992)

as most individuals behave in a risk-averse way rather than risk-taking way when there is

a probability to make gains The likelihood of making gains is weighed as too risky because


105

of the unpredictable nature of capital markets In a comprehensive study on stock market

psychology Warneryd (2001) posited that investors do not behave according to

conventional models of investment as proposed by the Efficient Market Hypothesis and

by rational models of portfolio choice Instead of rational behavior that can be explained

by traditional finance investors show behavioral biases The understanding of variables

that hinder or stimulate investment in stocks is fairly important (Keller amp Siegrist 2006a)

Investorsrsquo wealth and investment horizon have been reported as determinants of choice

among investment in different asset classes (Butler amp Domian 1991) Economic

psychology divides investors into groups based on financial psychological and

demographic characteristics Finance companies can then create specific marketing plans

to attract different groups of investors more effectively (Warneryd 2001)

Investment decisions have become more perplexed recently Thus in order to

understand which variables impact investorsrsquo financial decisions is of high relevance

(Keller amp Siegrist 2006b) Numerous psychological factors play a significant role in

individual financial decisions eg attitude towards money (Keller amp Siegrist 2006a b)

locus of control (McInish 1982) attitude toward saving (Euwals et al 2004) risk attitudes

(Morse1998 Tigges et al 2000 Warneryd 2001) and behavioral biases (Baker amp

Ricciardi 2014) Money attitudes have been studied in different areas of psychology

previously (Du amp Tang 2005 Gentina et al 2018 Hampson et al 2018 Lemrova et al

2014 Lim amp Teo 1997 Tang 2016 Tang amp Chiu 2003 Tang et al 2018a)

To date little is known about the impact of Love of Money on investment behavior

To the best of our knowledge the impact of Love of Money has never been systematically

tested with investment horizons (ie short-term and long-term) nor has its predictive power

Samra Chaudary

106

been examined in both developed and developing economies (see appendix III) It is fair

to believe that individuals assign a meaning to money that will have an effect on their

inclination towards the purchase of stocks The key goal of the life of people with high

money obsession is to grow their assets Individuals who are obsessed with money and

believe that money means achievement intelligence and power are expected to be more

likely to invest in stocks in order to attain their financial goals Financial returns provided

by stock investments can be viewed as a means of fulfilling their money-related goals

(Keller amp Siegrist 2006a)

There is scant empirical research about the love of money of stock market investors

and none in the emerging economy A handful of research studies have focused on peoplesrsquo

money attitudes in the developed economies (Belk amp Wallendorf 1990 Gentina et al

2018 Hampson et al 2018 Keller amp Siegrist 2006a Lim amp Teo 1997 Tang 2016 Tang

1992 Tung amp Baumannb 2009 Vitell et al 2007) but research in the context of

developing economies is still relatively sparse (Bhardwaj amp Bhattacharjee 2010 Carol amp

Samsinar 2011 Li et al 2009 Modesto Veludo-de-Oliveira et al 2014)

This study fills the void by investigating for the first time the impact of Love of

Money on both short-term and long-term investment decisions of actual stock market

investors from an emerging market The study further investigates if income and

inheritance expectation moderate the relationship of LoM with short-term and long-term

investment decision This study also extends prospect theory theory of planned behavior

and monetary intelligence theory in the domain of behavioral finance and offers

implications to individual investors and professional money managers in the context of a

developing economy


107


421 Prospect Theory

Prospect theory suggests that when an individual is offered a gamble containing

two or more outcome lotteries with some probability they would make their decisions on

the basis of the potential value of gains and losses rather than on the final outcomes of

lotteries They choose the alternative with the highest value The value function is concave

for gains convex for losses and steeper for losses than for gains Critical to this value

function is the reference point from which gains and losses are measured Mostly

individuals display risk-averse behavior rather than risk-seeking behavior when there is a

probability to make profits (Kahneman amp Tversky 1979) Chances of making gains are

calculated as too uncertain because of the apparent uncertainty of future financial market

movements An investorrsquos attitude towards money is a crucial factor in determining the

willingness to invest in shares (Keller amp Siegrist 2006a) Tang et al (2018a) asserted that

individuals differ in their attitude towards money which explains the endowment effect

(also known as status quo bias) and loss-averse behavior Endowment effect comes into

play when individuals place a higher value on assets that they own over those they do not

own because they assign more weight to losses than they do gains Hence they demand a

higher price (return) to give up the asset (they own) than they would be willing to pay to

purchase it (Thaler 1980) The disutility of giving up an asset (they own) is greater than

the utility of acquiring it (Kahneman Knetsch amp Thaler 1990 Kahneman amp Tversky

1984)

A number of studies have made use of prospect theory to investigate profits and

losses of stocks uncertainty skills of the portfolio manager (Jordan amp Riley 2015) and

Samra Chaudary

108

well-being (Frijters Johnston Shields amp Sinha 2015 Gehring amp Willoughby 2002

Ratcliffe amp Taylor 2015) Nonetheless only a few studies have analyzed investorsrsquo

decisions through the lens of their Love of Money (Gentina et al 2018 Keller amp Siegrist

2006a Tang et al 2018a Tang Tillery Lazarevski amp Luna-Arocas 2004)

422 Theory of Planned Behavior

According to the theory of planned behavior (TPB Ajzen 1991) individualsrsquo

behavior is predicted by their behavioral intention Attitudes subjective norms and

perceived behavioral control affect behavioral intentions which then determine actual

behaviors The theory of planned behavior predicts that behavior can include conflicts

between short-term and long-term goals affect cognition and consequences in several

fields (Ajzen 1985 1991) Thus the central idea of the theory is that planned behavior is

determined by behavioral intentions (Ajzen 2001) Cognitive impairment and lack of self-

control are the two key reasons due to which a person falls for the attraction of money

(Chen Tang amp Tang 2014 Tang amp Sutarso 2013) Therefore to understand an

individualrsquos behaviors scholars must study a personrsquos deeply rooted money attitudes

Raut et al (2018) proposed that TPB predicts onesrsquo behavioral intention to invest

in the capital market Similarly several studies have applied TPB on individuals to study

their money attitudes in decision-making (Gentina et al 2018 Lemrova et al 2014

Sardzoska amp Tang 2012 Singhapakdi Vitell Lee Nisius amp Grace 2013 Tang et al

2007 Tang 2016 Tang et al 2018a) However very few researches have been carried

out outside the US and even fewer in developing countries (Prahalad amp Hammond

2002) The contribution of TPB is not as widespread as many scholars once thought

especially in developing countries (Kirkman amp Law 2005) This study extends the


109

applicability of the TPB in the area of investment decision-making in a developing

economy

423 Monetary Intelligence (MI) Theory

Since attitudes determine intentions and behaviors Hence scholars should explore

personsrsquo deeply rooted money attitudes in order to recognize behaviors (Tang 2016)

Following the affective behavioral and cognitive model (ABC-model) of attitudes

(Bagozzi Tybout Craig amp Sternthal 1979) Monetary Intelligence (MI) theory proposed

that individuals monitor their own love of money motive (affect behavior and cognition)

and apply that knowledge to evaluate critical concerns in the proximal (immediate) and

distal (omnibus) contexts and strategically choose the options to achieve financial goals

success and ultimately to maximize their expected utility (Tang et al 2018b 2018c)

Various researchers have studied the concept of Monetary Intelligence in several

researches where individuals apply their monetary and personal values in decision-making

(Chen et al 2014 Gentina et al 2016 Lemrova et al 2014 Sardzoska amp Tang 2015

Tang amp Sutarso 2013 Tang et al 2018b 2018c Tang 2016) The findings of this study

expand the application of theory of MI to a new context of short-term and long-term

investment decisions made by investors in an emerging economy

424 Love of Money and Investment Decisions

Money attitudes are the values and meanings that one relates with money (Keller

amp Siegrist 2006a) Love of Money is defined as (i) attitude towards money including

affective behavioral and cognitive components (Mitchell amp Mickel 1999) (ii) meaning

of money (Tang 1992) (iii) desire (Sloan 2002) and aspirations (Tang 2007) for money

(iv) materialism (Belk 1985) (v) not onersquos need but greed (Sloan 2002) and (vi) the joint

Samra Chaudary

110

concept of numerous sub-constructs (Du amp Tang 2005 Tang 1992 1995 2007 Tang amp

Chen 2008 Tang amp Chiu 2003 Tang Kim amp Shin-Hsiung 2000 Tang Luna-Arocas

amp Sutarso 2005 Tang et al 2007 Vitell Paolillo amp Singh 2006 Vitell et al 2007)

Money Ethic Scale (MES Tang 1992 1993 1995) is one of the most scientifically

used money attitudes measurement instruments in previous studies (Mitchell amp Mickel

1999) Love of money (LoM) is the most well-developed construct of money attitude

(Gentina et al 2018 Tang et al 2018a Tang et al 2004) Love of Money scale has been

validated in more than three dozen studies (Erdener amp Garkavenko 2012 Gbadamosi amp

Joubert 2005 Lim amp Teo 1997 Nkundabanyanga Omagor Mpamizo amp Ntayi 2011

Sardzoska amp Tang 2009 Tang et al 2006 Tang Chen amp Sutarso 2008a Tang et al

2011 Wong 2008) Researchers have cited it in several leading international reviews

(Dittmar Bond Hurst amp Kasser 2014 Kish-Gephart Harrison amp Trevintildeo 2010 Lea amp

Webley 2006 Mitchell amp Mickel 1999 Rose amp Orr 2007 Zhang 2009) and in multiple

textbooks (Colquitt LePine amp Wesson 2011 Furnham 2014 McShane amp Von Glinow

2008 Milkovich Newman amp Gerhart 2014 Newman Gerhart amp Milkovich 2017

Phillips amp Gully 2013 Rynes amp Gerhart 2000 Scandura 2016) The Love of Money

(LoM) construct is a subset of MES (Tang amp Chen 2008 Tang amp Chiu 2003 Tang et al

2006 2011) and is also re-named as monetary intelligence lately (Chen et al 2014

Lemrova et al 2014 Sardzoska amp Tang 2015 Tang 2016 Tang amp Sutarso 2013 Tang

et al 2018b 2018c)

Tang (1992) proposed a Money Ethic Scale (MES) comprising of three factors 1)

an affective factor (money is good money is evil) 2) a cognitive factor (money symbolizes

achievement power and freedom) 3) and a behavioral factor (budget handle money


111

carefully) factor Lim and Teo (1997) proposed a parsimonious instrument on cognitive

and behavioral dimensions using items from Furnham (1984) Tang (1992) and Yamauchi

amp Templer (1982)

Love of money is a multidimensional construct and is measured as a second-order

variable in the literature (Gentina et al 2018 Lemrova et al 2014 Tang 2016) It has

also been reported that LoM as a latent formative construct is superior to latent reflective

construct (Lemrova et al 2014) Theoretically a multidimensional construct means a

single theoretical concept denotes to ldquoa number of interrelated attributes or dimensions

and exists in multidimensional domainsrdquo (Law Wong amp Mobley 1998)

Undoubtedly having money is essential It is reported that money has become more

important with time in materialistic communities (Mitchell amp Mickel 1999) Four decades

ago males ranked salary (income) at fifth place among ten important life goals however

females ranked salary (income) seventh place (Jurgensen 1978) However in 1990 all

respondents agreed that salary was ranked as the most important factor among eleven life

goals The salary was ranked first in importance in Germany and second in Belgium the

UK and the US (Harpaz 1990) Whoever loves money never has enough of it whoever

adores money is certainly not contented with hisher income (Tang et al 2018a) These

empirical findings are aligned with the old wisdom ldquoWhoever loves money never has

enough whoever loves wealth is never satisfied with their incomerdquo (Ecclesiastes 5 10

The Catholic Bible Tang et al 2006) ldquoPoverty consists not in the decrease of onersquos

possessions but in the increase of onersquos greed (Plato 427ndash347 BC)rdquo

Zakaria Jaafar and Marican (2012) suggested that money has an effect on onersquos

financial behavior Money attitudes predict monetary intentions and financial decisions

Samra Chaudary

112

(Tang et al 2018a) High LoM was reported to be associated with high risk-taking

behavior in a reward-related gambling task It was also found that participants with high

LoM were more sensitive to gainslosses that participants with low LoM (Jia Zhang Li

Feng amp Li 2013) People who have high Love of Money motive desire to make more

money (Tang 2016) become rich (Tang amp Chen 2008) and tend to show high tolerance

for investment risk (Tang et al 2008a) Employees in the developing economies are more

obsessed with money and these employees tended to seek any opportunity to make more

money (Tang et al 2005) Those who give importance to money were found keen to take

benefits from circumstances of financial gains (Gentina et al 2018) Such individuals

would likely to invest in the stock market to expect high profits Therefore it is reasonable

to assume that the meaning that people assign to money does affect their intention to invest

in shares (Keller amp Siegrist 2006a)

It was reported that when individuals were asked to recall money they become

unfriendly or less warm and shifted into their business and work mode (Vohs 2015 Vohs

Mead amp Goode 2006) Similarly Tang et al (2004) found that individuals who value

money are keenly involved in their work-related activities so that they can earn more

money and they relish achievements and success

Since the sample of this research was stock investors therefore in the light of

previous literature it was proposed that high LoM motive operated strongly on individuals

working as stock investors In contrast Keller and Siegrist (2006a) conducted a research

on Swiss investors and found that investment in stocks did not matter for those who

perceive money as an achievement and obsession It is possible that for Swiss investors the


113

expected return on the stock market was not a reliable indicator as an expression of

achievement and power

A sample of South African students was reported to treat money as their

achievement and achievement were found significantly associated with their materialism

(Nnedum Egwu Obinna Ntomchukwu amp Chukwukeluo 2011) Lemrova et al (2014)

also found that money was viewed as power in the context of materialism Similarly

according to Lea and Webley (2006) money was viewed as a symbol of power and was

found acting an addictive drugmdash the more you have the more you want It is that some

people tend to make more than they require which may lead to over earning and

accumulating wealth (Hsee Zhang Cai amp Zhang 2013) Feeling powerful also increases

saving (Garbinsky Kless amp Aaker 2014) Thus money a representation of power was

reported to be associated with wealth Money attitudes that reflect high level of power and

achievement tend to be positively related to high-risk current (short-term) and high-risk

future (long-term) financial investments (Shih amp Ke 2014) Hence the following

hypotheses are proposed for this study

H1 Love of Money positively impacts short-term investment decisions

H2 Love of Money positively impacts long-term investment decisions

425 Income Inheritance and Love of Money

Money is one way of expressing social status and it divides people into different

social groups (Tomek Striacuteteskyacute amp Tahal 2013) Some studies have found that money

attitudes are independent of onersquos income (Medina Saegert amp Gresham 1996 Yamauchi

amp Templer 1982) However other studies showed contradictory findings for example

individuals who perceive themselves affluent at times behave in a different way from those

Samra Chaudary

114

who perceive themselves unfortunate (Greenberg amp Hershfield 2019) Wealth perception

may have its roots in early life socioeconomic class Individuals who were raised in a higher

socioeconomic class are likely to show more risk-averse behavior than those who were

raised in a lower socioeconomic class (Griskevicius et al 2013) On the other hand Corter

and Chen (2006) found that wealthier investors tended to take more risks than less wealthy

ones

An individuals reaction to money is a reflection of hisher past life experiences

which influence attitudes towards money People who had faced a financial struggle in

their life were found likely to behave differently towards their Love of Money motive as

compared to those who had not experienced such hardships Those who had experienced

hardship in their lives suffered more from financial anxiety than those who did not because

of the high emotional and psychological pain related to financial deprivation Those

individuals were also probably treated with contempt when they desperately needed

money Thus they tend to see money as a means of comparison or evaluation Reddy

(1987) suggested that rich and poor would have different perspectives in the sense how

they use money Therefore money has a different meaning to different people which

depends on their backgrounds and financial experiences (Wernimont amp Fitzpatrick 1972)

Keller and Siegrist (2006b) also reported that investors having different money

attitudes profiles behave and invest differently They created four types of groups with

different money attitudes Safe players see financial security and savings as essential

Hoarding wealth and accumulating money were vital objectives of their lives Risk seekers

were risk-tolerant and have the most positive attitude towards stocks They were most

obsessed with money and would invest a huge amount of money in stocks Open books


115

showed little affinity with money They had low risk-tolerance and a negative attitude

towards stocks Financial security and savings had medium importance to them Money

dummies also had a low obsession with money They showed less risk tolerance and less

attraction towards money matters They had a more positive attitude towards the stock

market than open books

Earlier researches have studied the effect of income on willingness to invest in

shares (Cicchetti amp Dubin 1994 Grable Lytton amp OrsquoNeill 2004 Hlouskova Fortin amp

Tsigaris 2017) Individuals with income (businessmen) were reported to differ from those

without income (students) with respect to money as a motivator and as a measure of

achievement (Tang et al 2004) Individuals who imagined themselves to be well-off in

the future showed a high risk-seeking behavior than those who imagined themselves to be

deprived in the future (Greenberg 2013) However Concepcion (2016) found when one

starts to earn high-income heshe did not understand the need to save (invest) because the

income was expected to be replaced next month Income and net worth were reported to

have a positive correlation with investments in risky assets (Guiso Jappelli amp Terlizzese

1996) Embrey and Fox (1997) investigated the relationship of expected inheritance

employment status and income with financial investment They found women tended to

invest in stocks if they expected to receive inheritance were employed and had higher net

worth than men However men who expected to receive inheritance were more likely to

invest in business assets and less in housing assets Therefore the aforementioned findings

imply (regardless of gender) more wealth was found likely to lead to risky investments

Individuals with low-income level were seen to be more obsessed with money and

tended to spend money for power as compared to those with high-income level (Furnham

Samra Chaudary

116

1984) According to Prospect Theory (Kahneman amp Tversky 1979) poor people are

constantly in the losses (Kahneman 2011) which reflects their risk-seeking behavior for

losses (Gentina et al 2018) Many researches have reported that risk seekers purchase

shares more frequently than fewer risk avoiders (Tigges et al 2000 Warneryd 2001

Wood amp Zaichkowsky 2004) Poor children significantly overvalue the size of coins as

compared to rich kids (Bruner amp Goodman 1947) An increase in income was found

related to onersquos wellbeing predominantly for the poor After reaching above the poverty

threshold a further increase in income was found to matter little for the feeling of wellbeing

(Diener amp Oishi 2000) For example in a sample from Hong Kong the relationship

between income and LoM was found to be negative for highly paid employees Their

income was greater than the per capita GDP (Tang amp Chiu 2003) The same relationship

between income and LoM was found positive for underpaid African-Americans and for

women in the US who have less income than their counterparts and insignificant for

Caucasians and men in the US who have sufficient income at the market level or their

income was more than their counterparts (Tang et al 2006)

Individuals with low socioeconomic status tend to take high risk and low returns

investment decisions (Haisley Mostafa amp Loewenstein 2008) Consequently economic

disparity predicts high risk-seeking behavior (Krupp amp Cook 2018 Mishra Hing amp

Lalumiere 2015 Payne Brown-Iannuzzi amp Hannay 2017) Individuals with low-income

are likely to have a strong orientation towards LoM because several unmet needs

(Sardzoska amp Tang 2012 Tang et al 2008b) and their unsatisfied desires become

motivators (Kahneman amp Deaton 2010) Money is a motivator because only money can


117

fulfill the desires and improve the (financial) performance (Gomez-Mejia amp Balkin 1992

Jenkins Mitra Gupta amp Shaw 1998 Locke Feren McCaleb Shaw amp Denny 1980)

Therefore investors for whom money is a motivator are likely to take more risk

They constantly react to the stock market index frequently buy andor sell shares alter

shares proportion and try to make quick gains hence their investment behaviors are

controlled by the money-making motive (Tang et al 2018a) and they become a slave of

money (De Charms 1976) Due to the prospects of financial gains in the capital markets

low-income investors tended to strive for assets and do whatever it takes to make more

money than their counterparts (Tang et al 2008b)

Nonetheless normative scholars advise that investors must expect the compromise

between risk and expected return in order to achieve an optimal investment portfolio

(Merton 1973) Figure 41 illustrates the structural model about relationship of Love of

Money with short-term and long-term investment decisions with the moderating effects of

income and expect to receive a future inheritance Based on above discussion of literature

about relationship of income and wealth with LoM the following hypotheses are proposed

H3 Income moderates the relationship between Love of Money and short-term investment

decisions

H4 Income moderates the relationship between Love of Money and long-term investment

decisions

H5 Expectation of receiving future inheritance moderates the relationship between Love

of Money and short-term investment decisions

H6 Expect to receive future inheritance moderates the relationship between Love of

Money and long-term investment decisions

Samra Chaudary

118

Figure 41 Structural model about the relationship of Love of Money with short-term and

long-term investment decisions with the moderating effects of income and expect to

receive the future inheritance


431 Measures

This study has adopted developed instruments from the existing literature in order


decision were measured by adopting items from Mayfield et al (2008) on a five-point likert

scale Love of money is a second-order formative construct (reflective first-order

formative second-order) as proposed by Lemrova et al 2014) and (Tang 2016) Four first-

order latent sub-constructs are reflective 1) achievement 2) power 3) obsession and 4)

budget These dimensions were adopted from Keller and Siegrist (2006a) and have four

five four and two items respectively LoM is a second-order latent construct based on four

dimensions mentioned above Edwards (2011) has explained that a formative construct is

a composite of certain non-deletable dimensions that represent theoretically critical aspect

Achievement

Power

Obsession

Budget


Love of Money


IncomeExpect to receive

Inheritance

H1

H2

H3 H4H5 H6


119

of that latent construct In this study those dimensions are Achievement Power

Obsession and Budget These dimensions themselves are latent constructs that are

reflectively indicated by measurable indicators

432 Methods



major metropolitan cities of Pakistan Lahore and Karachi The sample consisted of money

managers working in financial institutions and individual investors who were active

investors on Pakistan Stock Exchange (PSX previously called KSE Karachi Stock

Exchange) Money managers were working in financial institutions like mutual fund

companies (asset management companies) brokerage houses or treasury departments of

banks However selected individual stock investors could be from any background and

from any industry or profession as the objective of this research was to analyze the behavior

of stock investors regardless of the fact that they were individual investors or they work

for an institution where they investmanage other peoplesrsquo money Out of the total

investorsrsquo population (corporate and individual combined) of the country Karachi has 74

percent investors and Lahore has 18 percent investors (Central Depository Company

2018) Hence it was ensured that the data is coming from the investment hubs of the

country where 92 percent of investors were located A total of 800 questionnaires were

rotated to collect the data from the targeted population of investors We received back 517

questionnaires and only 277 were fully completed Therefore the useable responses were

277 almost 35 percent response rate The response rate deemed satisfactory Many

behavioral studies in the discipline of investment decision had as low response rate as 109

Samra Chaudary

120

percent (Brown Call Clement amp Sharp 2015) 54 percent (Dichev Graham Harvey amp

Rajgopal 2013) and 289 percent (Yalcin et al 2016) The investment industry is highly

male-dominated hence sample consisted of 80 percent males and 20 percent females The

sample had 59 percent money managers and 41 percent individual investors Moreover 60

percent of the respondents were married 37 percent were single and 3 percent were either

separated or divorced The sample comprised of 87 percent employed respondents and 12

percent business owners and 1 percent of the sample was not employed Only 33 percent

of the sample had expectation to receive inheritance or transfer of assets from the family

and 67 percent respondents did not expect any future inheritance In addition to that 58

percent of the sample perceived that they were from the middle social class 36 percent

perceived themselves in upper middle class 3 percent perceived themselves as coming

from upper class and 3 percent perceived themselves from a lower middle class The

sample had 86 percent respondents who had their upbringing in the urban areas and 14

percent respondents had their upbringing in rural areas The data also exhibited that 11

percent of the respondents responded that they were very liberal in terms of religiosity 78

percent reported that they were moderately religious and 11 percent informed that they

were very religious The average age and monthly income of the sample were 32 years and

PKR 018 million respectively The average education was of 16 years The sample had on

average 4 years of investment experience in the Pakistan Stock Exchange and the average

amount invested in stocks was about PKR 10million Pakistanrsquos per capita income has

increased by 05 percent in year 2017-2018 and is at $1641 (PKR 162230) (Economic

Survey of Pakistan 2018) Per capita income crudely measures of the general well-being

in an economy


121

4322 Data Analyses

The research employs partial least square based structural equation modeling (PLS-

SEM) approach instead of covariance-based structural equation modeling (CB-SEM) due

to numerous reasons Firstly PLS-SEM efficiently handles both reflective and formative

measures (Ringle Sarstedt amp Straub 2012) Secondly PLS-SEM does not require data to

be normally distributed (Hair et al 2012) and works well with small sample sizes and

complex models (Cassel Hackl amp Westlund 1999) and involves minimum requirements

on measurement scales and residual distribution (Wold 1985) Thirdly applying PLS-

SEM provides effectiveness in parameter estimates which is established in the methods

higher statistical power than that of CB-SEM A higher statistical power denotes that PLS-

SEM tends to show a specific relationship significant when it is actually significant in the

population (Hair Hult Ringle amp Sarstedt 2016) Fourthly this approach focuses on

predictive estimation Precisely the aim of PLS-SEM is to maximize the variance of the

endogenous variables explained by the exogenous variables (Hair et al 2014) Fifthly to

evaluate the statistical significance of the parameter estimates smart PLS3 software

version 328 provides with percentile bootstrap confidence intervals (Hair et al 2011

Preacher amp Hayes 2008) Bootstrap sampling involves selecting repeated random

subsamples from the original sample (Hair et al 2012) These bootstrapped samples then

test the significance of the estimated coefficients (Henseler et al 2009) Lastly PLS

approach can be utilized for theory validation as well as to propose where relationships

may or may not present (Chin 1998) PLS is beneficial for exploratory research and for

the initial phases of theory development (Fornell amp Bookstein 1982) Table 41 depicts the

correlations of the constructs and square-root of average variance extracted

Samra Chaudary

122


term investment decision Pearsonrsquos correlation value between short-term investment

decision and long-term investment decision was 0490 (p=0000) Similarly short-term

investment decision also showed a positive correlation with all four factors of Love of

Money ie achievement power obsession and budget short-term investment decision had

the highest Pearsonrsquos correlation value of 0342 (p=0000) with budget component and

lowest correlation value of 0240 (p=0000) with obsession component In the same way

long-term investment decision too exhibited a positive correlation with all four factors of

Love of Money with the highest Pearsonrsquos correlation value of 0500 (p=0000) with budget

factor and lowest correlation value of 0209 (p=0000) with obsession factor



Deviation

ST-D LT-D Achievement Power Obsession Budget

ST-D 3074 0836 (0742)

LT-D 3292 0856 0490 (0735)

Achievement 2893 0934 0297 0244 (0808)

Power 2928 0967 0268 0327 0645 (0821)

Obsession 2659 0898 0240 0209 0582 0610 (0744)

Budget 3093 0785 0342 0500 0221 0184 0157 (0771) Note ST-D= Short-term Investment Decision LT-D= Long-term Investment Decision Diagonal values in parentheses are values of square root of AVEs p lt 1 p lt 05 p lt 01

44 Results


For reflective constructs researchers should report factor loadings composite

reliability average variance extracted and discriminant validity The statistical assessment

for reflective model cannot be reassigned to formative models where indicators represent

constructrsquos independent causes and therefore do not necessarily correlate highly (Hair et

al 2016) Evaluating convergent and discriminant validities are not important when


123

formative constructs and their weights entail (Chin 1998) For formative constructs

indicator weights along with their significance multicollinearity of indicators and

constructs must be stated (Cenfetelli amp Bassellier 2009 Chin 1998 Fornell amp Larcker

1981 Hair et al 2012) Therefore the measurement model of first-order reflective

constructs or the reflective dimensions of the second-order construct were evaluated by

analyzing the factor loadings All the loadings were found above 05 (Velicer amp Fava

1998 Wille 1996) and statistically significant (Anderson amp Gerbing 1988 Hulland 1999)

A resampling was done by bootstrapping method with 2000 subsamples which

were used to compute t-statistics (Henseler et al 2009) The estimates of standardized

factor loadings of first-order reflective constructs ranged from 0641 to 0865 (tgt196) for

short-term investment decision 0630-0798 (tgt196) for long-term investment decision

0690-0873 (tgt196) for achievement 0615-0794 (tgt196) for power 0628-0798

(tgt196) for obsession 0722-0783 (tgt196) and 0527-0954 (tgt196) for budget

Composite reliability (CR) of reflective constructs measured the internal

consistency which should be higher than 07 or higher (Hair et al 2012) The values of

composite reliability were 0773 for short-term investment decision 0823 for long-term

investment decision 0882 for achievement 0912 for power 0837 for obsession and

0730 for budget Convergent validity was also computed for reflective constructs through

average variance extracted (AVE) which fulfill the benchmark of 050 or higher (Hair et

al 2012) The values for AVE were 0551 for short-term investment decision 0541 for

long-term investment decision 0653 for achievement 0675 for power 0555 for

obsession and 0595 for budget Discriminant validity of each reflective construct was

measured through two approaches and met the standards by Fornell-Larcker criteria (1981)

Samra Chaudary

124

and Heterotrait-Monotrait (HTMT) ratio of correlations criteria (Henseler et al 2015)

According to Fornell-Larcker criteria the square root of AVE of a latent construct should

be greater than all of the inter-factor correlations of that construct with other constructs

(Hair et al 2012) Moreover HTMT values were less than 1 which is the predefined

threshold by (Henseler et al 2015)

Common method bias and collinearity among constructs were checked for each

reflective construct through variance inflation factor (VIF) test at the factor level The test

was carried out twice with both dependent variables once with short-term investment

decision and once with the long-term investment decision No common method bias was

found in both the tests as the VIF values of all the factors were less than 33 (Kock 2015)

The study used a repeated indicator method to compute the parameters of second-

order (reflective-formative) construct namely Love of Money It is an appropriate

approach in a complicated structural model in which the formative construct has an

endogenous position (Becker Klein amp Wetzels 2012b) The estimation of the formative

construct (LoM) at the dimension level was done by testing for multicollinearity between

its dimensions and by analyzing its weights (Henseler et al 2009)

Weights of formative construct show that power with weight 0458 (tgt196)

represents the most significant dimensions of LoM in the formation of the LoM construct

That was followed by achievement with weight 0350 (tgt196) obsession with weight

0290 (tgt196) and budget with weight 0095 (tgt196) The maximum variance inflation

factor (VIF) value for all dimensions was less than the recommended value of 33 (Kock

2015) The results of the measurement model are presented in table 42 and table 43 44

and 45


125



Factor Loadings

Boot

sample

t-Values

Short-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)


money into the stock market 0669

8112



I intend to compare my portfolio performance

to that of professional managers 0641 7244

Long-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)

I intend to save at least 10 of my gross

earnings for investingsavingretirement

purposes

0798 23438

I intend to have a portfolio that focuses on

multiple asset classes (stocks bonds cash

real estate etc)

0715 12630


I intend to invest some money in long-term

assets where my money will be tied up and

inaccessible for years

0630 8323

Love of

Money

(second order-

formative

construct)

(Kelleramp

Siegrist

2006a)

Achievement

(reflective dimension)

I believe that the amount of money that a

person earns is closely related to hisher

ability and effort

0690 17818

Money represents ones achievement 0837 37628

Money is a symbol of success 0873 58397

I believe that a persons salary is very

revealing in assessing their intelligence 0812 34412

Power


Money can give you the opportunity to be

what you want to be 0794 67856

Money gives you autonomy or freedom 0784 39807

Money means power 0742 39244

Money will help you express your

competence and abilities 0774 32383

Money can bring you many friends 0615 18517

Obsession


I firmly believe that money can solve all of

my problems 0748 22209

Money can buy everything 0628 6043

I would do practically anything legal for

money if it were enough 0798 26365

I often fantasize about money and what I

could do with it 0791 35126

Budget


I am proud of my ability to save money 0954 27280

I feel compelled to argue or bargain about the

cost of almost everything that I buy 0527 3672


Samra Chaudary

126

Table 43 Weights and Variance Inflation Factor of Constructs

Constructs Weights of

Formative

Components of

Construct LoM

t-values of

Weights

Variance

Inflation Factor

(VIF)

Achievement 0350 21725 2031

Power 0458 26660 2155

Obsession 0290 14361 2029

Budget 0095 5767 1121



(CR)

Average Variance Extracted

(AVE)

Short-Term Investment Decision 0773 0551

Long-Term Investment Decision 0823 0541

Achievement 0882 0653

Power 0912 0675

Obsession 0837 0555

Budget 0730 0595


Factors Achievement Budget Long-Term

Investment

Decision

Obsession Power Short-Term

Investment

Decision

Achievement

Budget 04662

Long-Term

Investment

Decision

03553 07748

Obsession 07911 04764 03102

Power 07591 03561 0432 08125

Short-Term

Investment

Decision

04514 03446 07436 04071 04057


The following section investigates the direct effects of Love of Money on short-

term investment decision and long-term investment decisions The parameter estimates

(path coefficients) were computed along with their significance The significance of


127


2009) The benchmark for the coefficient of determination (R2) is 010 or higher (Falk amp

Miller 1992) The effect size of the impact of LoM on ST-D and LT-D was reported as

suggested by Cohen (1998) The rule about effect size is that the f2 values of 002 015

and 035 showed a small medium and large effect size (Henseler et al 2009) The

predictive relevance of the model was estimated by calculating Q2 coefficients (Geisser

1975 Stone 1974) using the blindfold test (Hair et al 2014) Lastly the power test was

also performed to analyze the probability that a statistically significant relationship is

found when the relationship is actually there (Goodhue et al 2012) A value of 08 or

higher is adequate in behavioral studies for the power test (Cohen 1988)

Table 46 summarizes the results of direct effects The hypothesized relationship

between LoM and ST-D (H1) was found significantly positive with medium effect size (β=

0341 p= 0000 f2= 0160) Similarly the association between LoM and LT-D (H2) was

also found statistically significant with a smaller positive beta coefficient and medium

effect size (β= 0328 p= 0000 f2= 0154) The coefficient of determination of LoM with

LT-D is slightly higher (R2= 0138) than the coefficient of determination with ST-D

(R2=0134) Hence variations in LoM was found likely to explain more variations in LT-

D than in ST-D The values of Q2 were above zero representing that each exogenous

construct in the model has predictive relevance for both endogenous latent variables All

the hypotheses have shown very strong statistical power ie 0999 or above which means

a very high probability of the presence of the relationships between the exogenous latent

variable (LoM) and endogenous latent variables (ST-D and LT-D) A high value of power

test affirmed the appropriateness of the sample size

Samra Chaudary

128

Age gender and religiosity were included as control variables in the model These

variables have relevance in the model of Love of Money and investment decisions Age

had shown an impact on financial decisions (Agarwal et al 2007) Men were more inclined

towards both short-term and long-term investments than women (Bajtelsmit et al 1999

Hariharan et al 2000 Mayfield et al 2008 Olsen amp Cox 2001) Religiosity was found

to have an effect on decision-making (Singhapakdi et al 2013) Hunt and Vitell (1993)

also posited that the strength of religious viewpoints could bring about differences in onersquos

decision-making processes Wong (2008) suggested that individuals with similar religious

beliefs tended to have different love of money profiles However McClure (1984) found

that money attitudes are generally similar irrespective of religion None of the control

variables had shown any impact in our model

Table 46 Results of Direct Effects of LoM on ST-D and LT-D

Hypotheses Relationships Path Coefficients

p

value

f2 R2 Q2 Statistical

Power

H1 Love of Money -gt

Short-term

investment decision

0341 0000 0160 0134 0058 0999


Long-term

investment decision

0328 0000 0154 0138 0059 0999

Note p lt 1 p lt 05 p lt 01 Control variables Age-gtST-D (β= -0101 p=0109) Gender-gtST-D (β= -00437 p=0427) Religiosity -gtST-D (β=

0048 p=0391) Age-gtLT-D (β= -0070 p=0214 Gender-gtLT-D (β= 0093 p=0112) and Religiosity-gtLT-D (β= -

0002 p=0953)

443 Moderation Effects of Current Income and Future Inheritance

A moderator variable explains ldquowhenrdquo the relationship exists between an independent

and dependent variable It can affect the magnitude andor sign of the relationship (Baron

amp Kenny 1986) Current income and expectation of receiving an inheritance in future were

tested as moderators between the relationship of LoM and short-term investment decision

as well as long-term investment decision The moderation was computed through a product


129

indicator method by Chin Marcolin and Newsted (2003) in which each indicator of

independent variable was multiplied with each indicator of the moderator (income) to

create a new variable The product indicator approach provides least biased estimates for

the parameters of an interaction effect and delivers true estimates for the interaction effect

for medium to large sample sizes The product indicator method also yields higher

prediction accuracy of the endogenous latent variable (Henseler amp Chin 2010) We also

investigated the statistical power test to reveal if the model is strong enough to detect a

significant effect that actually does exist (Frazier Tix amp Barron 2004 Goodhue et al

2012) The moderation results are presented in table 47 The interactions effects of H3

H4 H5 and H6 are plotted in figure 42 43 44 and 45 respectively These plots depict

the effects of independent variables on dependent variables in the presence of moderator

It was found income moderated the relationship between LoM and ST-D (H3) (β=

-0173 p= 0050) and did not moderate the relationship of LoM with LT-D (H4) (β= 0037

p= 0514) Additionally it was found that high-income dampens the positive relationship

between LoM and short-term investment decision with a change in R2 from 0134 without

the moderator (income) to R2 0152 with the presence of income as a moderator The

positive impact of LoM on ST-D when moderated with income turned into a negative

moderated relationship between LoM and ST-D So the impact of LoM on ST-D was

found conditional on the level of income The negative coefficient of interaction term with

LoM implies that investors with high-income are less likely to take short-term investment

decisions even though their LoM is high Hence those investors who had high current

income were found less likely to involve in short-term investments

Samra Chaudary

130

In figure 42 it can be seen that the direction of the relationship between Love of

money and short-term investment decision is different for investors with high-income (+1

standard deviation) and investors with low-income (-1 standard deviation) as there was a

significant difference in slopes at mean income at -1 standard deviation (SD) and at +1

standard deviation The slopes of two regression lines are moving in different directions

Figure 43 shows that income did not moderate the relationship between love of money and

long-term investment decision as there was no significant difference in slopes at mean

income at high-income (+1 standard deviation) and at low-income (-1 standard deviation)

Expect to receive inheritance was a dummy variable and coded with the values of

0 and 1 The value of the moderator was 0 if individuals expected to receive future

inheritance and 1 if they did not expect to receive future inheritance It was found that

expectation of receiving future inheritance also moderated the relationship between LoM

and both short-term (H5) (β= 0373 p= 0024) and long-term investment decisions (H6)

(β= 0318 p= 0044) Moreover it was found that the impact of LoM on ST-D was found

slightly higher in the situation when individuals did not expect to receive inheritance as

compared to the impact of LoM on LT-D for the same condition Hence those investors

who did not expect to receive future inheritance were found more likely to participate in

short-term investment activities than in long-term investment activities even though their

LoM was high Similarly those investors who expected to receive future inheritance were

found less likely to involve in short-term investment activities than in long-term investment

activities even though their LoM was high

A change in R2 was observed from 0134 without the moderator (expect to receive

future inheritance) to R2 0165 with the presence of the moderator in the case of ST-D and


131

from 0138 to 0201 in the case of LT-D R2 Δ measures the effect size in moderation

analysis R2Δ demonstrates a unique share of variance explained by an exogenous variable

in the endogenous variable that is not explained by other exogenous variables in the model

(Cohen Cohen West amp Aiken 2003) Cohen (1988) defined small moderate and large

effect sizes of R2Δ as 002 013 and 026 respectively R2Δ was found to be 0018 for H3

0008 for H4 0031 for H5 and 0063 for H6 All moderation hypotheses (H3-H6) showed

a small effect size The statistical power of all the relationships was closer to 1

Figure 44 and 45 depict the significant interaction between Love of Money and

expectation of having a future inheritance on ST-D and LT-D respectively The rate of

change in response to a unit increase in Love of Money differs for investors who expected

to receive inheritance compared to investors who did not expect to receive future

inheritance As can be seen in both figures Love of Money was found to be positively

associated with short-term and long-term investment decisions when investors did not

expect future inheritance The impact of Love of money on both short-term and long-term

investment decisions was positive when investors did not expect future inheritance The

rate of change of the slope is relatively steeper in case of short-term investment decision

Table 47 Moderation Results

Hypotheses Relationships Estimate p

value

R2

without

moderator

R2

with

moderator

R2Δ Power

Result

H3 LoMIncome-gtST-D -0173 0050 0134 0152 0018 0999 Moderation

H4 LoMIncome-gtLT-D 0037 0514 0138 0153 0008 0999 No

Moderation

H5 LoMInheritance-gtST-

D

0373 0024 0134 0165 0031 0999 Moderation

H6 LoMInheritance-gtLT-

D

0318 0044 0138 0201 0063 0999 Moderation

Note ST-D= Short-term Investment Decision LT-D= Long-term Investment Decision and LoM= Love of

Money


Samra Chaudary

132

Figure 42 The moderating effect of income on the relationships between LoM and short-

term investment decision The above illustration shows income at mean one standard

deviation above the mean (ie high-income) and one standard deviation below the mean

(ie low-income)

Figure 43 The no-moderating effect of income on the relationships between LoM and


standard deviation above the mean (ie high-income) and one standard deviation below

the mean (ie low-income)


133


relationships between LoM and short-term investment decision


relationships between LoM and Long-term investment decision

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Short

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Long

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

Samra Chaudary

134


This study extends existing research by focusing on investorsrsquo short-term and long-

term investment decisions through the lens of their money attitudes Findings of the

formative theoretical model demonstrated the new visions for the field of Love of Money

of stock investors in the context of an emerging market This study found that LoM had a

significant positive effect on both short-term and long-term investment decisions (H1 and

H2) Previous studies have also found that employees in developing countries are more

obsessed with money and look for any opportunity to make money (Tang et al 2005)

Similarly other studies have also found that individuals with high LoM motives want to

make money (Tang 2016) become rich (Tang amp Chen 2008) and display investment risk

tolerance behavior (Jia et al 2013 Tang et al 2008a) Those who value money more tend

to get benefit from the circumstances of financial gains (Gentina et al 2018) Our results

also showed that investors with high LoM tended to engage in both types of financial gain

opportunities ie short-term and long-term investments Nonetheless it is critical that

money managers should watch the decision-making of investors because those who want

to get rich also tend to involve in unethical and disordered money behaviors (Britt 2016

Tang et al 2008a 2011 Tang amp Sutarso 2013)

Exploring the same theoretical model with the interaction of income and

expectation of future inheritance revealed more interesting findings It was found that

investors with higher LoM were likely to do less short-term investment and no long-term

investment if their income was high Similarly investors with higher LoM were likely to

do less short-term investment and relatively more long-term investment if they expected to

receive a future inheritance


135

Chen et al (2014) found that the more money rich people have the more money

they want Individuals with low (high) affection for money have low (high) interests in

making money (Tang 2016) Earlier studies have found that wealthier investors were

willing to take more risk (Bernoulli 17381954) and individuals with high-income are less

risk-averse (Cicchetti amp Dubin 1994) and have more positive attitude towards financial

risk tolerance than individuals with low-income (Grable et al 2004) Therefore according

to previous literature and in order to make more wealth a high LoM motive of wealthier

(high current income and expect to receive inheritance) investors should have a positive

effect on long-term investment instead of short-term because long-term securities possess

higher risk as well as higher returns (Dimson et al 2017 Harrison amp Zhang 1999 Von

Thadden 1995) This could be one of the reasons that money attitudes of high-income

investors and those who expected to receive inheritance showed a negative impact on short-

term investments High LoM motive of those who expected to receive future fortune tended

to invest more in long-term investments Warren (2014) also reported that long-term

investments provide growth and assist investors to generate more wealth over time

However on the other hand our findings also showed that LoM (money attitude)

of high-income investors showed no impact on long-term investments Previous studies

have also reported that money attitudes are unrelated to an individualrsquos income (Medina et

al 1996 Yamauchi amp Templer 1982) Moreover another possibility could be that

investors with high-income might be handling their money carefully and avoiding long-

term investment particularly at the time of data collection only

The sample of this study was collected at the bearish time period when PSX-100

annual average return was -710 percent (Economic Survey of Pakistan 2017-2018)

Samra Chaudary

136

Economic contractions also stimulate risk-averse behavior for possible negative returns

(Millet Lamey amp Van den Bergh 2012) Also according to Merton (1973) investors must

consider the trade-off between risk and return in order to achieve the optimal portfolio

returns As it was observed that LoM of wealthier investors (high current income and

expect to receive inheritance) showed negative impact on short-term investments probably

because they might not be expecting maximum return for a given level of risk in that

bearish time period Hence expected returns are so unreliable to assist in achieving more

wealth as one of the essential goals of life (Keller amp Siegrist 2006a)

Wealthy investors showed loss-averse behavior in our research as they their LoM

(money attitudes) showed a negative impact on short-term investment decision (at the time

when market was giving losses) and is aligned with Prospect Theory (Kahneman amp

Tversky 1979 Tversky amp Kahneman 1992) which infers that investors are generally risk-

averse rather than risk-takers whenever there is a probability to make profits Chances of

making profits are estimated as too unreliable because of high instability of PSX-100 in

the time period of data collection

Furthermore our result showed that LoM (money attitude) showed a positive

impact on short-term investment for investors with low current income Similarly LoM

(money attitude) of investors who did not expect to receive future inheritance showed a

stronger positive impact on short-term investment as compared to long-term investment

The plausible reason could be that the investors with low-income have instant unmet needs

which could be one of the reasons that their money attitudes showed a positive impact on

short-term investment decision as short-term investments yield faster returns Our findings

are aligned with the former research studies The desire for immediate gratification


137

determined onersquos short-term investment decision (Warren 2016) Moreover individuals

with low-income are likely to have a strong orientation towards LoM because several

unmet needs (Sardzoska amp Tang 2012 Tang et al 2008b) and unsatisfied desires become

motivators (Kahneman amp Deaton 2010) Money is a motivator for poor people because

only money can fulfill the desires and improve the financial condition (Gomez-Mejia amp

Balkin 1992 Jenkins et al 1998 Locke et al 1980) Such individuals are more obsessed

with money (Furnham 1984) Hence we can say money attitudes of investors whose

current and future financial circumstances were weak (ie low current income and did not

expect to receive future fortune in the form of inheritance) tended to invest in short-term

investments

Results of the LoM typology proposed in this research have practical implications

for individual investors themselves and for professional money managers as they can

improve knowledge of their own preferences (for an individual investor) and of their client

preferences (for professional managers) This might expedite investment decision-making

for example retirement planning etc Money managers can help craft strategies to help

their customers attain their short-term and long-term financial goals of a comfortable

retirement (Concepcion 2016) Therefore investment advisors must understand what is

important to their clientele so that they can guide them and fulfill their requirements

effectively

The results offer implications for the marketing of financial companies like asset

management firms brokerage houses and investment banks It is probable to target

prospect investors through segmentation on the basis of money attitudes current income

and future wealth possession In marketing their services investment companies may target

Samra Chaudary

138

less wealthy investors for short-term investments and wealthy investors for long-term

investments Moreover in light of this researchrsquos findings money attitudes of individuals

with high-income did not show an impact on long-term investment This may be

counterproductive in achieving long-term financial goals of such individuals especially

when ignoring precautionary measures for saving It can also result in later repentance of

not having enough investments for their retirement (OrsquoDonoghue amp Rabin 1998) Money

managers may seem excessively challenged by the need to persuade high-income investors

that their long-term financial goal is secured by selecting risky investments These

investors need to be targeted more efficiently through a targeted marketing plan and various

types of financial instruments

For an emerging market like Pakistan there is a massive need to raise capital in

order to fuel the capital requirements and to ensure the sturdy growth of the market

Successfully targeting high-income investors will bring more money in the market boost

investments and investorsrsquo confidence in the country increase market capitalization

maintain sustainability in the market keep the market competitive and eventually market

would move towards efficiency

As it was found that there was no impact of LoM on long-term investment decision

for investors with high-income This result identified the need for different types of long-

term financial products There is a need for the development of long-term investment

products tailored to the desires of wealthy investors in particular which will motivate them

to invest in capital markets Pakistani financial markets lack in investment alternatives eg

bonds derivative securities and real estate investment trust (REITs) etc The findings of

this study offer financial institutions and regulators to develop new financial products and


139

markets Moreover transmission of knowledge in the field of different investment

alternatives must not be ignored in a country like Pakistan where only 26 percent of

adults are financially knowledgeable (SampP Global Fin Lit Survey 2015) Financial literacy

is a knowledge of risk diversification time value of money compounding and numeracy

(interest) A good level of financial literacy will help people to change their money

attitudes money management and make them achieve their financial goals (Imasheva amp

Kim 2017)

According to the findings of this study investorsrsquo money attitudes predicted their

investment plans (ie short-term and long-term) Therefore it is essential to determine

individual differences in money attitudes if individual investors are well guided by money

managers and financial institutions Financial planners should pay attention to investorsrsquo

money attitudes For that reason there is a need for more frequent surveys about their

money attitudes and feelings about financial products which should be the fundamental

aspects of financial services Moreover financial advisors should also elucidate the choice

of financial product and clarify why a particular product is the best option for the investor

Our novel findings shed new light on the relationships between LoM and

investment decisions and suggest practical implications for the growing area of behavioral

finance To conclude we offer a brand new and novel viewpoint and supplement the

behavioral finance literature by investigating LoM as an antecedent of short-term and long-

term investment decisions The formative theoretical model revealed novel and interesting

findings and helped us understand not only the what (ie LoM) factor contributing to short-

term and long-term investment decisions but also who (ie stock investors) where (ie

developing economy) and when (ie income and inheritance)

Samra Chaudary

140

46 Conclusion and Future Research Direction

This study contributes to an evolving stream of literature that sheds light on the

significance of LoM with short-term and long-term investment decision in the context of

developing economy A positive relationship of LoM was found with short-term and long-

term investment decisions Moreover in moderation analysis it was observed that for high-

income investors the impact of LoM was significantly negative for short-term investment

decision and was insignificant for long-term investment decision Furthermore it was

found that investors with higher LoM were likely to do less short-term investment decision

than long-term investment decision in the case they expected to receive a future

inheritance However investors with higher LoM were likely to do more short-term

investment decision than long-term investment decision in case they did not expect any

future inheritance

Future researchers should consider adding other investment alternatives as

dependent variables to examine the influence of LoM on a particular asset class This

research was cross-sectional in nature and it was not evident if LoM was constant over

time Peoplersquos financial strategies are associated with their different life stages

(Gunnarsson amp Wahlund 1997) Similarly it is likely that investorsrsquo money attitudes vary

in boom periods and hence their investment decisions may also change Therefore further

researches can use longitudinal data in order to elucidate the constancy of LoM over time

to examine whether money attitudes change with different phases of life Data from

multiple regions and cultures (especially from developing countries) can be collected to

generalize the results This study only measured investorsrsquo perception of LoM and not the

actual LoM behavior LoM behavior may be tested in a laboratory experiment in further


141

researches (Greenberg 1993) to see different investment behavior and if they react

differently to probable gains and losses Future studies could also examine the impact of

other moderators such as macro-economic issues eg unemployment education and

religious views could have a significant effect on the outcomes of this research To

conclude behaviorally an investor must become masters (but not slaves) of money (Tang

et al 2018a) Individuals with inheritance should master the necessary money skills or

have a trustworthy financial planner otherwise they will usually end up losing everything

they have (Khoo 2006)

Samra Chaudary

142

5 Conclusion

51 Introduction

This dissertation has examined the sway of selected behavioral factors affecting short-

term and long-term investment decision There were sparse pieces of evidence on

behavioral factors effecting investorsrsquo investment decision especially in the context of

developing economies (Bhardwaj amp Bhattacharjee 2010 Carol amp Samsinar 2011 De

Vries et al 2017 Metawa et al 2019 Riaz amp Hunjra 2016) Researchers have

encouraged to conduct studies in the discipline of behavioral finance as the discipline is

still premature and emerging and needs more empirical evidence from primary data

especially from emerging economies (Huang et al 2016 Kumar amp Goyal 2015) Hence

the primary research questions of this study were 1a) Do five personality types have an

effect on short-term and long-term investment decisions 1b) Does risk perception mediate

the relationship between personality types and short-term and long-term investment

decisions 2a) Does salience has an impact on short-term and long-term investment

decisions 2b) Whether the impact of salience on short-term and long-term investment

decisions differs between individual investors and professional investors 2c) Whether the

impact of salience on short-term and long-term investment decisions differs between

female investors and male investors 3a) Does Love of Money has an effect on short-term

and long-term investment decisions 3b) Whether current income and future inheritance

moderate the relationship of Love of Money and short-term as well as long-term investment

decisions

Data for this research were gathered through a survey using a structured questionnaire

from two metropolitan cities of Pakistan Lahore and Karachi The respondents for this

Conclusion

143

research were individual investors and professional money managers working with

financial institutions who were actively investing in securities listed on Pakistan Stock

Exchange previously known as Karachi Stock Exchange Money managers were working

in financial institutions like mutual fund companies (asset management companies)

brokerage houses or treasury departments of banks However individual stock investors

were from varying backgrounds as the primary objective of this study was to analyze the

behavior of stock investors be it at an individual level investor or a person working with

an institution A list of institutions where respondents were selected to fill the

questionnaire is attached as appendix IV For data analysis and result reporting the

research used partial least square based structural equation modeling (PLS-SEM) approach

was used instead of covariance-based structural equation modeling (CB-SEM) due to

several strengths of PLS-SEM (Chin et al 2003 Hair et al 2012 Henseler et al 2009

Reinartz et al 2009) The findings of research questions are presented and discussed in

chapters two three and four

52 Key Findings

The research questions addressed in chapter two were based on the implications of

the prospect theory theory of planned behavior and Risk as Feeling theory The

relationship between five types of personalities and investment decisions were explored It

was found that individuals with high neuroticism and extroversion personality traits were

likely to indulge in short-term investment decision However individuals with

extraversion openness agreeableness conscientiousness personality traits were likely to

indulge in long-term investment engagement The research also investigated the

significance of risk perception as a mediator between each personality type and investment

Samra Chaudary

144

decisions The risk perception mediated the relationship between four personality types

except neuroticism and long-term investment decisions

Chapter three examined the impact of salience on short-term and long-term

investment decisions Using the lens of prospect theory it was found that salience has a

significant positive impact on both short-term and long-term investment decisions The

impact was almost 15 times higher for long-term investment decision as compared to the

short-term investment decision Furthermore it was found that the two groups ie

individual investors and professional investors were significantly different from each other

such that the impact of salience on short-term and long-term investment decision was

stronger for individual investors than for professional investors Additionally the study

also found that both groups (female and male) were significantly different from each other

such that the impact of salience on short-term decisions and for long-term decisions was

higher in the case of female investors than in the case of male investors

Chapter four made use of the prospect theory theory of planned behavior and

monetary intelligence theory to study the association between Love of Money (LoM) and

investment decisions It was found that LoM was likely to have a positive impact on both

short-term and long-term investment decisions Moreover interaction analysis revealed

that income moderated the relationship between LoM and ST-D and did not moderate the

relationship of LoM with LT-D The expectation of receiving future inheritance also

moderated the relationship between LoM and both short-term and long-term investment

decisions

Investors who had high current income were found less likely to participate in short-

term investments Investors who did not expect to receive future inheritance were found

Conclusion

145

more likely to involve in short-term investment activities than in long-term investment

activities even though their LoM was high Similarly investors who expected to receive

future inheritance were found less likely to involve in short-term investment than in long-

term investment activities even though their LoM was high

Overall the findings of this research study offered noteworthy theoretical and

practical implications in the context of an emerging economy by reporting significant

relationships of personality type salience and LoM with investment decisions These

results highlighted the relevance and significance of behavioral factors for investors

making short-term and long-term investment decisions while trading in listed stocks This

research has also contributed to the knowledge of the psychology of choices made by

investors in an emerging market

53 Theoretical Implications

The importance of behavioral and psychological aspects in the study of finance is

becoming increasingly evident Irrational decision-making has been widely observed in

many empirical studies (De Bondt amp Thaler 1985 Hirshleifer 2001 Ishfaq et al 2017

Metawa et al 2019 Odean 1998 Thaler amp Sunstein 2008) Such irrational decision-

making behavior was explained by the risk-averse nature of individuals and this

phenomenon was better explained with prospect theory Under prospect theory behavioral

biases were key factors for irrational decision-making To the best of our knowledge there

were no studies that have examined 1) the impact of Big-Five personality types on short-

term and long-term investment decisions with the mediation of risk perception 2) the

impact of salience on short-term and long-term investment decisions with the group

differences between professional and individual investor 3) the effect of LoM on short-

Samra Chaudary

146

term and long-term investment decisions with the moderation of current income and future

inheritance

Prospect theory postulated that most individuals show irrational risk-averse

behavior rather than risk-taking whenever there was a probability of making profits

(Kahneman amp Tversky 1979) Findings of this research have provided support to the

prospect theory by indicating the impact of salience (familiarity bias) on both short-term

and long-term investment decisions for individual and professional investors as well as for

both genders (Antoniou et al 2010 Riff amp Yagil 2016 Yalcin et al 2016) indicating risk

aversion of investors

Moreover this research made another significant theoretical advancement by

bringing together the relevance of prospect theory theory of planned behavior and risk as

feeling theory in one place The theory of planned behavior (TPB) by Ajzen (1991)

proposed that individualsrsquo behavior was predicted by hisher behavioral intention

Behavioral intentions were in turn determined by attitudes and perceived behavioral

control Risk as feeling theory (RaF) by Loewenstein et al (2001) proposed that when there

was a risky situation behavior tended to be driven by emotional reactions or feelings at the

time of decision-making rather than cognitiverational assessments Prospect theory also

proposes irrationality in investorsrsquo decisions under risky situations They also posited that

ldquorisk as feelingrdquo mediated at least partially the relationship between an individuals

cognitive evaluation of risk and their behavioral response Kobbeltvedt and Wolff (2009)

argued that TPB and RaF have some shared variables

Mayfield et al (2008) used two types of personality traits as behavioral intentions and

supported TBP that short-term and long-term investment intentions were predicted by

Conclusion

147

personality types This study however used Big-Five types of personality traits as

behavioral intentions and also supported TPB as individuals with neuroticism and extrovert

personalities showed a significant relationship with short-term investment plans

Moreover openness conscientiousness and extraversion personality traits were found

more likely to do long term investment intentions

Our result showed support for RaF theory related to the mediating role of risk

perception It was found that investorsrsquo risk perception mediated the relationship of


term investment decisions but did not mediate relationships between personality types and

ST-D It is probably because the feeling (affect) for ST-D is not perceived as risky as the

LT-D are

In addition to that this research made another noteworthy theoretical development

by interweaving the implications of prospect theory along with the theory of planned

behavior and monetary intelligence theory According to TPB attitudes predicted intentions

and behaviors and prospect theory focuses on behavioral bias therefore scholars should

examine individualsrsquo deeply rooted money attitudes (Tang 2016) in the light of their

behavioral biases Following the affective behavioral and cognitive model (ABC-model)

of attitudes (Bagozzi et al 1979) Monetary Intelligence (MI) theory proposed that people

monitor their own money attitudes and apply the information to evaluate the concerns in

the proximal (immediate) and distal (omnibus) contexts and strategically select the choices

to achieve financial goals (Tang et al 2018b 2018c) Tang et al (2018a) asserted that

individuals vary in their attitude towards money The results once again supported prospect

theory as wealthy investors (high current income and expect to receive inheritance) showed

Samra Chaudary

148

loss-averse behavior in our research as their LoM (money attitudes) showed a negative

impact on short-term investment decision (at the time when market was giving losses) and

was aligned with Prospect Theory (Kahneman amp Tversky 1979 Tversky amp Kahneman

1992) which implied that investors were generally risk-averse rather than risk-taking

whenever there was a probability to make profits The chances of making profits were

estimated as too unreliable due to high instability of PSX-100 in the time period of data

collection

As manifested from the above arguments this research has provided theoretical

contributions by expounding the application of prospect theory for the understanding of

investorsrsquo decision-making for short-term and long-term The study has also made a

methodological contribution by using primary data collected from real-life investors The

findings of this study has extended the general model of prospect theory theory of planned




developing economy hence delivered contextual contribution as well Given the

importance of these theories in the field of social behavior the results of this study have

also provided interdisciplinary contributions

54 Practical Implications

This research offered practical implications for money managers individual

investors and regulatory bodies of the country With the growth of the economy peoplesrsquo

wealth increases Hence there is a growing need for performance of wealth management

Conclusion

149

functions by professional money managers This function involves understanding the

clientrsquos requirements and delivering financial services accordingly

It is critical to examine peoplesrsquo intentions about short-term and long-term

investments and why they manage investment in different ways If those investment

intentions become evident then financial planners would be interested to learn if those

intentions can be adapted in order to advise their clients (Mayfield et al 2008) It is

essential to understand personalities risk perceptions salience attitudes towards money

and other biases to give better investment advice to individual investors Such findings are

likely to help money managers to target investors appropriately and communicate to these

investors more effectively (Wood amp Zaichkowsky 2004)

The results of this research offered practical implications for both individual investors

and for professional money managers as they can have superior knowledge of their own

preferences and biases (for individual investors) and of their client preferences (for money

managers) Such enhanced understanding can facilitate investment decision-making

process Investment advisors help clients in investing money They must understand what

is important to their customers in order to fulfil clientsrsquo expectations accordingly It may

be possible to segment clients based on personality type risk perception familiarity bias

money attitudes current income and future wealth possession etc and develop

investment advisory packages accordingly

Portfolio managers may find useful strategies to exploit numerous behavioral

anomalies present in the financial markets Professional money managers from brokerage

houses mutual funds and other financial institutions may deliver a superior product

Samra Chaudary

150

service and provide sound assistance to their customers once they have knowledge of

clientsrsquo behavioral biases and preferences

Investors should be mindful that behavioral biases sometimes could also lead to

investment in sub-optimal portfolios Therefore understanding investorsrsquo behavior can

help to avoid such biases and can improve investment decisions in choosing short-term or

long-term investment services products and plans Portfolio managers should try to

improve their investment decisions by relying less on biases and investing their clientsrsquo

wealth globally for better diversification To avoid these biases financial counselors must

communicate to their clients about the importance of a long-term diversification plan with

the aim of risk reduction and higher expected return in their investment portfolios (Baker

amp Ricciardi 2015) Females represent a tiny sample in the financial industry of Pakistan

An investment education program is needed especially in a developing country like

Pakistan to target more females in the investment industry to boost savings in the economy

This research also expects to enhance understanding for financial regulators such as

SECP as to why and how markets might be inefficient Short-term investment is also

known as momentum investing (Gray 2006) while long-term investment is known as value

investing (Warren 2014) Generally momentum investment leads to market inefficiencies

including the creation of bubbles crashes and excess volatility in the market (Woolley

2013) as good (bad) outcomes are likely to be followed by further good (bad) outcomes

(Warren 2014) Too much short-term behavior may have adverse effects in the financial

market and shifting the balance towards long-term investment may be beneficial Value

(long-term) investments tend to have a lower turnover ratio than momentum (short-term)

Conclusion

151

investments (Warren 2014) Long-term investors provide a buffer against market panics

(Della Croce et al 2011) and help to smooth out market fluctuations (Ang amp Kjaer 2011)

Individuals with short-term investment horizons behave like traders or perhaps

speculators whereas individuals with long-term investment horizon act like investors A

long- term investment attitude represents the willingness to accept short-term pain for long-

term gain Such attitudes and beliefs are often rooted within the character of an organization

or an individual (Warren 2016)

For an emerging economy like Pakistan there is an enormous need to issue more

capital to ensure the steady growth of the financial market Successfully targeting investors

is likely to bring more funds in the market boost investments and enhance investorsrsquo

confidence in the country and thereby increase market capitalization maintain

sustainability in the market keep the market competitive and eventually market would

move towards efficiency in the long-run

55 Research Limitations and Future Research Directions

Although this research has made noteworthy theoretical contributions to the young

paradigm of behavioral finance and has identified practical implications for investors yet

there are also some limitations that restrict the generalizability of the results Gathering

data from real equity investors (especially from professionals ie brokers and the

institutional fund managers) was quite challenging These professionals were not willing

to leave their trading screens during the market hours (930 am -330 pm) even for a short

time They filled the survey questionnaire either after the market timings (late in the

evening) or on weekends The key contribution of this dissertation is the fact that this is

very first research of this kind in the context of both developed and developing economies

Samra Chaudary

152

However more empirical pieces of evidence are needed hence data from multiple regions

and cultures can be collected in order to get results that are more widely generalizable

Data for this research were collected in the time of bears market condition Upcoming

research can collect data in bulls market and can compare the results This study has relied

on self-reported data to measure personality traits risk perception salience and LoM

Future studies can make use of objective measures of aforementioned behavioral factors

However developing such measures for investors could be tremendously challenging This

research measured investorsrsquo perceptions and not actual behavior Behaviors are better

verified in a laboratory experiment (Greenberg 1993) and further studies can opt to do so

to investigate different behavioral biases and preferences to learn if investors respond

differently

It should be admitted that there were various other psychological factors that might

have affected investment decisions and were not investigated in this study Future studies

could test the impact of differences in investorsrsquo emotions moods and weather and the

resulting impact on investment behaviors These constructs can be measured in with

different methods eg the impact of live weather on the investors while trading their

stocks can be captured through an experiment Such a research design might be challenging

as theses professional traders might be reluctant to participate because of their fiduciary

responsibility of managing other peoplersquos money that they carry on their shoulders

Leaving their trading screens during market hours even for a short bit is immoral for them

Future researchers can also classify investment decision in a different way than classifying

such decisions into long and short time horizons (eg by investigating multiple

instruments) Another aspect that can be further investigated is the likely impact of money

Conclusion

153

managersrsquo experience on their investment decisions Future researchers can also investigate

if gender with different demographic variables (such as marital status age and income)

have different investment decisions

In this study the focus was only on stock investors and future studies can select

investors in other instruments as well to investigate if they behave in a similar manner

This study was cross-sectional in nature and it was not evident if the resulting behavioral

biases were constant over time Peoplersquos financial strategies are likely to be associated with

their life cycle stages (Gunnarsson amp Wahlund 1997) Therefore future researchers can

use longitudinal data in order to elucidate the constancy of impact of personality salience

and LoM over time to examine whether these biases of investors change with different

stages of their cycle This study did not investigate the impact of macro-economic issues

eg unemployment education levels recession and political instability etc which may

have a significant effect on the behavioral biases and preferences of investors

Samra Chaudary

154

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Ahmad M Hassan A Mahmood S amp Aslam S (2016) Impact of Investor Personality

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Ajzen I (1985) From intentions to actions A theory of planned behavior In J K J

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Ajzen I (1991) The Theory of planned behavior Organizational Behavior and Human

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Ajzen I (2001) Nature and operation of attitudes Annual Review of Psychology 52 27ndash

58

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Allport G W (1937) Personality A psychological interpretation New York Holt

Allport G W amp Odbert H S (1936) Trait names A psycho-lexical study Psychological

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Alrabadi D W H Al-Abdallah S Y amp Aljarayesh N I A (2018) Behavioral biases

and investment performance Does gender matter Evidence from Amman Stock

Exchange Jordan Journal of Economic Sciences 5(1) 77-92

Anderson C W Fedenia M Hirschey M amp Skiba H (2011) Cultural influences on

home bias and international diversification by institutional investors Journal of

Banking amp Finance 35(4) 916-934

Anderson J C amp Gerbing DW (1988) Structural equation modeling in practice a

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423

Ang A and Kjaer K N (2011) Investing for the Long Run working paper (November

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Ang J J de Jong A A amp van der Poel M A (2014) Does CEOs familiarity with

business segments affect their divestment decisions Florida State University

working paper Retrieved from httpsssrncomabstract=967359

Antoniou A Olusi O amp Paudyal K (2010) Equity Home‐Bias A Suboptimal Choice

for UK investors European Financial Management 16(3) 449-479

Samra Chaudary

156

Arch E C (1993) Risk-taking a motivational basis for sex differences Psychological

Reports 73(1) 3-11

Aronson E (1999) The Social Animal 8th ed New York Worth Freeman

Bagozzi R P Tybout A M Craig C S amp Sternthal B (1979) The contrast validity

of the tripartite classification of attitudes Journal of Marketing Research 16 88ndash

95

Bajtelsmit V L Bernasek A amp Jianakoplos N A (1999) Gender differences in defined

contribution pension decisions Financial Services Review 8(1) 1-10

Baker H K amp Ricciardi V (2014) How biases affect investor behavior Working paper

ssrncom retrieved from httpwwweuropeanfinancialreviewcomp=512

Baker H K amp Ricciardi V (2015) Understanding behavioral aspects of financial

planning and investing Journal of Financial Planning 28(3) 22-26

Baker H K Filbeck G amp Ricciardi V (2017) How Behavioral Biases Affect Finance

Professionals The European Financial Review 25-29

Bansal R amp Yaron A (2004) Risks for the long run A potential resolution of asset

pricing puzzles The journal of Finance 59(4) 1481-1509

Barber B M amp Odean T (2001) Boys will be boys gender overconfidence and

common stock investment The Quarterly Journal of Economics 116(1) 261-292

Barber B M Odean T amp Zheng L (2005) Out of sight out of mind The effects of

expenses on mutual fund flows The Journal of Business 78(6) 2095-2120

Barberis N amp Thaler R (2003) A survey of behavioral finance Handbook of the

Economics of Finance 1 1053-1128

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Barberis N amp Xiong W (2009) What drives the disposition effect An analysis of a

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784

Baron R M amp Kenny D A (1986) The moderator-mediator variable distinction in

social psychological research Conceptual strategic and statistical considerations

Journal of Personality and Social Psychology 51(6) 1173-1182

Barrick M R amp Mount M K (1991) The Big-Five personality dimensions and job

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Bateman H Ebling C Louviere J J Satchell S E Thorp S amp Geweke J (2010)

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Australian School of Business Research Paper (2011ACTL02)

Baxter M (1994) Real exchange rates and real interest rate differentials Have we missed

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Becker A Deckers T Dohmen T Falk A amp Kosse F (2012a) The relationship

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Becker J M Klein K amp Wetzels M (2012b) Hierarchical latent variable models in

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Planning 45(5-6) 359-394

Belk R W (1985) Materialism Trait aspects of living in the material world Journal of

Consumer Research 12(3) 265-280

Belk R W amp Wallendorf M (1990) The sacred meanings of money Journal of

Economic Psychology 11(1) 35-67

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158

Bernoulli D (17381954) Exposition of a new theory on the measurement of risk

translated by Louise Sommer Econometrica 22 22ndash36

Bhardwaj S amp Bhattacharjee K (2010) Modeling money attitudes to predict loan

default IUP Journal of Bank Management 9(12) 12

Black F (1986) Noise The Journal of Finance 41(3) 528-543

Black F amp Scholes M (1973) The pricing of options and corporate liabilities Journal

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Blanthorne C Jones-Farmer L A amp Almer E D (2015) Why you should consider

SEM a guide to getting started Advances in Accounting Behavioral Research 9

179-207

Bolander W Satornino C B Hughes D E amp Ferris G R (2015) Social networks

within sales organizations Their development and importance for salesperson

performance Journal of Marketing 79(6) 1-16

Bollen N P amp Posavac S (2018) Gender risk tolerance and false consensus in asset

allocation recommendations Journal of Banking amp Finance 87 304-317

Borges B Goldstein DG Ortmann A amp Gigerenzer G (1999) Can ignorance beat

the stock marketrdquo in Gigerenzer G Todd P and The ABC Research Group (Eds)

Simple Heuristics That Make us Smart Oxford University Press New York NY

59-72

Borghans L Heckman J J Golsteyn B H amp Meijers H (2009) Gender differences

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Personality 60 253-293

Britt S L (2016) The intergenerational transference of money attitudes and behaviors

Journal of Consumer Affairs 50(3) 539-556

Brown L D Call A C Clement M B amp Sharp N Y (2015) Inside the ldquoblack boxrdquo

of sell‐side financial analysts Journal of Accounting Research 53(1) 1-47

Brunell A B amp Buelow M T (2017) Narcissism and Performance on Behavioral

Decision‐making Tasks Journal of Behavioral Decision-making 30(1) 3-14

Bruner J S amp Goodman C C (1947) Value and need as organizing factors in

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Butler KC amp Domian DL (1991) Risk diversification and the investment horizon The

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Byrnes J P Miller D C amp Schafer W D (1999) Gender differences in risk taking a

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Calvo-Mora A Navarro-Garciacutea A Rey-Moreno M amp Perianez-Cristobal R (2016)

Excellence management practices knowledge management and key business

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Management Journal 34(6) 661-673

Cao H H Han B Hirshleifer D amp Zhang H H (2009) Fear of the unknown

Familiarity and economic decisions Review of Finance 15(1) 173-206

Samra Chaudary

160

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Individual Differences 51(3) 274-278

Carol T B C amp Samsinar M S (2011) Satisfying Womens Status Desires Role of

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June Cotte and Linda Price Duluth MN Association for Consumer Research

Cassel C Hackl P and Westlund AH (1999) Robustness of partial least squares

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Statistics 26(4) 435-446

Cattell H E (1996) The original Big-Five A historical perspectiversquo European Review of

Applied Psychology 46(1) 5ndash14

Cattell H E amp Mead A D (2008) The sixteen personality factor questionnaire (16PF)

The SAGE Handbook of Personality Theory and Assessment 2 135-178

Cattell R B Eber HW and Tatsuoka M M (1970) Handbook for the Sixteen

Personality Factor Questionnaire Champaign IL Institute for Personality and

Ability Testing

Cenfetelli R T amp Bassellier G (2009) Interpretation of formative measurement in

information systems research MIS Quarterly 33(4) 689-707

Central Depository Company (2018) The Custodian Slate Valuing the Precious Quarterly

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References

161

Chai J Horneff W Maurer R amp Mitchell O S (2011) Optimal portfolio choice over

the life cycle with flexible work endogenous retirement and lifetime payouts

Review of Finance 15(4) 875-907

Chan K Covrig V amp Ng L (2005) What determines the domestic bias and foreign

bias Evidence from mutual fund equity allocations worldwide The Journal of

Finance 60(3) 1495-1534

Charness G amp Gneezy U (2007) Strong evidence for gender differences in investment

Working paper Retrieved from httpsssrncomabstract=648735

Chen J Tang T L P amp Tang N (2014) Temptation monetary intelligence (love of

money) and environmental context on unethical intentions and cheating Journal

of Business Ethics 123(2) 197-219

Chin W W Marcolin B L amp Newsted P R (2003) A partial least squares latent

variable modeling approach for measuring interaction effects Results from a

Monte Carlo simulation study and an electronic-mail emotionadoption study

Information Systems Research 14(2) 189-217

Chin WW (1998) The partial least squares approach to structural equation modeling

In G A Marcoulides (Ed) Modern methods for business research 295-336

Mahwah NJ Lawrence Erlbaum

Chin WW Mills AM Steel DJ Schwarz A (2016) Multi-group Invariance Testing

An Illustrative Comparison of PLS Permutation and Covariance-Based SEM

Invariance Analysis In Abdi H Esposito Vinzi V Russolillo G Saporta G

Trinchera L (eds) The Multiple Facets of Partial Least Squares and Related

Samra Chaudary

162

Methods PLS 2014 Springer Proceedings in Mathematics amp Statistics 173 267-

284

Choi J J Laibson D Madrian B C amp Metrick A (2004) For better or for worse

Default effects and 401 (k) savings behavior In Perspectives on the Economics of

Aging (pp 81-126) University of Chicago Press

Cicchetti C J amp Dubin J A (1994) A micro econometric analysis of risk aversion and

the decision to self- insure The Journal of Political Economy 102(1) 169ndash186

Clark-Murphy M amp Soutar G N (2004) What individual investors value Some

Australian Evidence Journal of Economic Psychology 25(4) 539-555

Cohen J (1988) Statistical power analysis for the behavioral sciences (2nd ed) Hillsdale

NJ Erlbaum

Cohen J Cohen P West S G amp Aiken L S (2003) Applied multiple

regressioncorrelation analysis for the behavioral sciences (3rd ed) Mahwah NJ

Lawrence Earlbaum

Colquitt J A LePine J A amp Wesson M J (2011) Organizational behavior Improving

performance and commitment in the workplace Irwin McGraw-Hill

Concepcion J N (2016) Young and Indebted A Closer Look at the Future of Young

Professionals Journal of Financial Planning 29(9) 24

Connor-Smith J K amp Flachsbart C (2007) Relations between personality and coping

A meta-analysis Journal of Applied Psychology 93 1080-1107

Cooper I amp Kaplanis E (1994) Home bias in equity portfolios inflation hedging and

international capital market equilibrium The Review of Financial Studies 7(1) 45-

60

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Corter J E amp Chen Y J (2006) Do investment risk tolerance attitudes predict portfolio

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Costa P T Jr amp McCrae R R (1985) The NEO Personality Inventory Odessa FL

Psychology Assessment Resources

Costa P T amp McCrae R R (1992) NEO PI-R Professional Manual Odessa FL

Psychological Assessment Resources

Costa P T Busch C M Zonderman A B amp McCrae R R (1986) Correlations of

MMPI factor scales with measures of the five-factor model of personality Journal

of Personality Assessment 50 640-650

Coval J D amp Moskowitz T J (1999) Home bias at home Local equity preference in

domestic portfolios The Journal of Finance 54(6) 2045-2073

Daniel K amp Hirshleifer D (2015) Overconfident investors predictable returns and

excessive trading Journal of Economic Perspectives 29(4) 61-88

De Bondt W F (1998) A portrait of the individual investor European Economic Review

42(3-5) 831-844

De Bondt W F amp Thaler R (1985) Does the stock market overreact The Journal of

Finance 40(3) 793-805

De Charms R (1976) Enhancing Motivation Changes in the Classroom Irvington New

York NY

De Vries A Erasmus P D amp Gerber C (2017) The familiar versus the unfamiliar

Familiarity bias amongst individual investors Acta Commercii 17(1) 1-10

Samra Chaudary

164

Della Croce R Stewart F amp Yermo J (2011) Promoting longer-term investment by

institutional investors selected issues and policies OECD Journal Financial

Market Trends 1 1-20

Dichev I D Graham J R Harvey C R amp Rajgopal S (2013) Earnings quality

Evidence from the field Journal of Accounting and Economics 56(2-3) 1-33

Diener E amp S Oishi S (2000) Money and Happiness Income and Subjective Well-

Being Across Nations In E Dinner amp E M Suh (Eds) Subjective Well-Being

Across Cultures (pp 185-218) Cambridge MA MIT Press

Dierkes M Erner C amp Zeisberger S (2010) Investment horizon and the attractiveness

of investment strategies A behavioral approach Journal of Banking amp Finance

34(5) 1032-1046

Digman J M amp Inouye J (1986) Further specification of the five robust factors of

personality Journal of Personality and Social Psychology 50(1) 116

Dimson E Marsh P amp Staunton M (2017) Factor-based investing the long-term

evidence The Journal of Portfolio Management 43(5) 15-37

Dittmar H Bond R Hurst M amp Kasser T (2014) The relationship between

materialism and personal well-being A meta-analysis Journal of Personality and

Social Psychology 107 (5) 879-924

Dohmen T Falk A Huffman D Sunde U Schupp J amp Wagner G G (2011)

Individual risk attitudes Measurement determinants and behavioral

consequences Journal of the European Economic Association 9(3) 522-550

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Dreman D Johnson S MacGregor D amp Slovic P (2001) A report on the March 2001

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126-134

Du L amp Tang T L P (2005) Measurement invariance across gender and major The

love of money among university students in Peoplersquos Republic of China Journal


Durand R B Newby R amp Sanghani J (2008) An intimate portrait of the individual

investor The Journal of Behavioral Finance 9(4) 193-208

Durand R Newby R Tant K amp Trepongkaruna S (2013) Overconfidence

overreaction and personality Review of Behavioral Finance 5(2) 104-133

Duxbury D Hudson R Keasey K amp Summers B (2005) Should actions speak louder

than words Individuals attitudes and behavior in asset allocation choices

Economics Letters 89(1) 107-111

East R (1993) Investment decisions and the theory of planned behavior Journal of


Economic Survey of Pakistan (2017-2018) Government of Pakistan Finance division

Economic Advisors Wing Islamabad

Edwards J R (2011) The fallacy of formative measurement Organizational Research

Methods 14(2) 370-388

Einhorn H J amp Hogarth R M (1981) Behavioral decision theory Processes of

judgement and choice Annual Review of Psychology 32(1) 53-88

Embrey L L amp Fox J J (1997) Gender differences in the investment decision-making

process Journal of Financial Counseling and Planning 8(2) 33-40

Samra Chaudary

166

Epley N amp Gilovich T (2005) When effortful thinking influences judgmental

anchoring differential effects of forewarning and incentives on self‐generated and

externally provided anchors Journal of Behavioral Decision-making 18(3) 199-

212

Epstein S (1994) Integration of the cognitive and the psychodynamic unconscious

American Psychologist 49(8) 709-724

Erdener C amp Garkavenko V (2012) Money attitudes in Kazakhstan

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Estes R amp Hosseini J (1988) The gender gap on Wall Street an empirical analysis of

confidence in investment decision-making The journal of psychology 122(6) 577-

590

Euwals R Eymann A amp Boumlrsch-Supan A (2004) Who determines household savings

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25(2) 195-211

Eysenck H J amp Eysenck S B G (1975) Manual of the Eysenck Personality

Questionnaire London Hodder and Stoughton

Falk R F amp Miller N B (1992) A primer for soft modeling Akron University of Akron

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Fama E F (1970) Efficient Capital Markets A Review of Theory and Empirical Work

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Fama E F (1998) Market efficiency long-term returns and behavioral finance1 Journal

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Fawcett S E Wallin C Allred C Fawcett A M amp Magnan G M (2011)

Information technology as an enabler of supply chain collaboration A dynamic

capabilities perspective Journal of Supply Chain Management 47(1) 38-59

Feng L amp Seasholes M S (2008) Individual investors and gender similarities in an

emerging stock market Pacific-Basin Finance Journal 16(1-2) 44-60

Filbeck G Hattield P amp Horvarth P (2005) Risk Aversion and Personality Type The

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Firat D amp Fettahoglu S (2011) Investors Purchasing Behavior via a Behavioral Finance

Approach International Journal of Business and Management 6(7) 153-163

Fischhoff B (1994) Acceptable Risk A Conceptual Proposal Risk Health Safety and

Environment 5(1) 1-28

Forbes W Hudson R Skerratt L amp Soufian M (2015) Which heuristics can aid

financial-decision-making International Review of Financial Analysis 42 199-

210

Fornell C amp Bookstein F L (1982) Two structural equation models LISREL and PLS

applied to consumer exit-voice theory Journal of Marketing Research 19(4) 440ndash

452

Fornell C amp Larcker D F (1981) Evaluating structural equation models with

unobservable variables and measurement error Journal of Marketing Research

18(1) 39ndash50

Fox C R amp Tversky A (1995) Ambiguity aversion and comparative ignorance The

Quarterly Journal of Economics 110(3) 585-603

Samra Chaudary

168

Frazier P A Tix A P amp Barron K E (2004) Testing moderator and mediator effects

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French K R amp Poterba J M (1991) Investor diversification and international equity

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Friedman M amp Savage L J (1952) The expected utility hypothesis and the

measurability of utility Journal of Political Economy 60 463-474

Frijters P Johnston D W Shields M A amp Sinha K (2015) A lifecycle perspective

of stock market performance and wellbeing Journal of Economic Behavior amp

Organization 112 237-250

Funder D C (2001) Personality Annual Review of Psychology 52 197-221

Furnham A (1984) Many sides of the coin The psychology of money usage Personality

and Individual Differences 5(5) 501ndash509

Furnham A (2014) The new psychology of money London Routledge

Furnham A amp Boo H C (2011) A literature review of the anchoring effect The Journal

of Socio-Economics 40(1) 35-42

Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships

The Journal of Marketing 58(2) 1-19

Garbinsky E N Kless K amp Aaker J (2014) Money in the bank Feeling powerful

increases saving Journal of Consumer Research 41(3) 610ndash623

Garson G D (2016) Partial least Squares Regression amp structural equation models

David Garson and Statistical Associates Publishing

Gbadamosi G amp Joubert P (2005) Money ethic moral conduct and work related

attitudes Field study from the public sector in Swaziland Journal of Management

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Development 24(8) 754-763

Gehring W J amp Willoughby A R (2002) The medial frontal cortex and the rapid

processing of monetary gains and losses Science 296 2279-2282

Geisser S (1975) The predictive sample reuse method with applications Journal of the

American Statistical Association 70(350) 320ndash328

Gentina E Tang T L P amp Gu Q (2018) Do parents and peers influence adolescentsrsquo

monetary intelligence and consumer ethics French and Chinese adolescents and

behavioral economics Journal of Business Ethics 151(1) 115-140

Giannetti M amp Koskinen Y (2010) Investor protection equity returns and financial

globalization Journal of Financial and Quantitative Analysis 45(1) 135-168

Gigerenzer G (2014) Risk savvy How to make good decisions New York Viking

Glaser M Langer T Reynders J amp Weber M (2007) Framing effects in stock market

forecasts The difference between asking for prices and asking for returns Review

of Finance 11(2) 325-357

Goldberg L R (1971) A historical survey of personality scales and inventories In P

McReynolds (Ed) Advances in psychological Assessment2 293- 336 Palo Alto

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Goldberg L R (1981) Language and individual differences The search for universals in

personality lexicons Review of Personality and Social Psychology 2(1) 141-165

Goldberg L R (1990) An alternative description of personality the Big-Five factor

structure Journal of Personality and Social Psychology 59(6) 1216-1229

Goldstein D amp Gigerenzer G (2002) Models of ecological rationality The recognition

heuristic Psychological Review 109 75ndash90

Samra Chaudary

170

Gomez-Mejia L R amp Balkin D B (1992) Determinants of faculty pay An agency

theory perspective Academy of Management Journal 35 921-955

Goodhue D L Lewis W amp Thompson R (2012) Does PLS have advantages for small

sample size or non-normal data MIS Quarterly 36(3) 981-1001

Gough H G (1987) California psychological inventory Administrators Guide

Consulting Psychologists Press

Grable J Lytton R amp OrsquoNeill B (2004) Projection bias and financial risk tolerance

The Journal of Behavioral Finance 5(3) 142ndash147

Gray J (2006) Avoiding short-termism in investment decision-making CFA Institute

December

Greenberg A E (2013) When imagining future wealth influences risky decision-making

Judgment and Decision-making 8(3) 268ndash277

Greenberg A E amp Hershfield H E (2019) Financial decision-making Consumer

Psychology Review 2(1) 17-29

Greenberg J (1993) Stealing in the name of justice Informational and interpersonal

moderators of theft reactions to underpayment inequity Organizational behavior

and human decision processes 54(1) 81-103

Grinblatt M amp Han B (2005) Prospect theory mental accounting and momentum

Journal of Financial Economics 78(2) 311-339

Grinblatt M amp Keloharju M (2001) How distance language and culture influence

stockholdings and trades The Journal of Finance 56(3) 1053-1073

Griskevicius V Ackerman J M Cantuacute S M Delton A W Robertson T E Simpson

J A Tybur J M (2013) When the economy falters do people spend or save

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Science 24(2) 197ndash205

Guilford J P (1949) The Guilford-Zimmerman Temperament Survey Beverly Hills

Calif Sheridan

Guiso L Jappelli T amp Terlizzese D (1996) Income risk borrowing constraints and

portfolio choice American Economic Review 86(1) 158-172

Gulati R (1995) Does familiarity breed trust The implications of repeated ties for

contractual choice in alliances Academy of Management Journal 38(1) 85-112

Gunnarsson J amp Wahlund R (1997) Household financial strategies in Sweden An

exploratory study Journal of Economic Psychology 18(2ndash3) 201ndash233

Hair Jr J F Hult G T M Ringle C amp Sarstedt M (2014) A Primer on Partial Least

Squares Structural Equation Modeling (PLS-SEM) Thousand Oaks CA Sage

Publications

Hair Jr J F Hult G T M Ringle C amp Sarstedt M (2016) A primer on partial least

squares structural equation modeling (PLS-SEM) (2nd ed) Sage Publications

Thousand Oaks CA USA

Hair J F Ringle C M amp Sarstedt M (2011) PLS-SEM Indeed a silver bullet Journal

of Marketing Theory and Practice 19(2) 139 ndash 151

Hair J F Sarstedt M Ringle C M amp Mena J A (2012) An assessment of the use of

partial least squares structural equation modeling in marketing research Journal of

the Academy of Marketing Science 40(3) 414-433

Haisley E Mostafa R amp Loewenstein G (2008) Subjective relative income and lottery

ticket purchases Journal of Behavioral Decision-making 21(3) 283ndash295

Samra Chaudary

172

Hampson D P Grimes A Banister E amp McGoldrick P J (2018) A typology of

consumers based on money attitudes after major recession Journal of Business

Research 91 159-168

Hariharan G Chapman K S amp Domian D L (2000) Risk tolerance and asset

allocation for investors nearing retirement Financial Services Review 9(2) 159-

170

Harpaz I (1990) The importance of work goals An international perspective Journal of

International Business Studies 21(1) 75-93

Harrison P amp Zhang H H (1999) An investigation of the risk and return relation at long

horizons Review of Economics and Statistics 81(3) 399-408

Hastie R amp Dawes R M (2010) Rational choice in an uncertain world The psychology

of judgment and decision-making Sage

Hayes A F (2009) Beyond Baron and Kenny Statistical mediation analysis in the new

millennium Communication Monographs 76(4) 408-420

Hayes C L amp Kelly K (1999) Money makeovers How women can control their

financial destiny New York Doubleday

Heath C amp Tversky A (1991) Preference and belief Ambiguity and competence in

choice under uncertainty Journal of Risk and Uncertainty 4(1) 5-28

Heinstroumlm J (2003) Five personality dimensions and their influence on information

behavior Information Research 9(1) 9-1

Henseler J amp Chin W W (2010) A comparison of approaches for the analysis of

interaction effects between latent variables using partial least squares path

modeling Structural Equation Modeling 17(1) 82-109

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Henseler J Ringle C M amp Sarstedt M (2015) A new criterion for assessing

discriminant validity in variance-based structural equation modeling Journal of the

Academy of Marketing Science 43(1) 115-135

Henseler J Ringle C M amp Sarstedt M (2016) Testing measurement invariance of

composites using partial least square International Marketing Review 33(3) 405ndash

431

Henseler J Ringle C M amp Sinkovics R R (2009) The use of partial least squares path

modeling in international marketing In New challenges to international marketing

(pp 277-319) Emerald Group Publishing Limited

Hershey D A amp Mowen J C (2000) Psychological determinants of financial

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Hinz R P McCarthy D D amp Turner J A (1997) Are women conservative investors

Gender differences in participant-directed pension investments Positioning

pensions for the twenty-first century Philadelphia University of Pennsylvania Press

91- 103

Hira T K amp Loibl C (2008) Gender differences in investment behavior In Handbook

of consumer finance research (pp 253-270) Springer New York NY

Hirshleifer D (2001) Investor psychology and asset pricing Journal of Finance 56(4)

1533-1597

Hlouskova J Fortin I amp Tsigaris P (2017) The consumptionndashinvestment decision of a

prospect theory household A two-period model Journal of Mathematical

Economics 70 74-89

Samra Chaudary

174

Hoffmann A O Post T amp Pennings J M (2015) How investor perceptions drive actual

trading and risk-taking behavior Journal of Behavioral Finance 16(1) 94-103

Hogan J (1986) Manual for the Hogan Personnel Selection System Minneapolis MN

National Computer Systems

Hogan R (1982) A socioanalytic theory of personality In Nebraska symposium on

motivation University of Nebraska Press

Hogan R amp Hogan J (1991) Personality and status In D G Gilbert amp J J Connolly

(Eds) Personality Social Skills and Psychopathology An Individual Differences

Approach 137-154 New York Plenum Press

Hopenhayn H A (1992) Entry exit and firm dynamics in long run equilibrium

Econometrica Journal of the Econometric Society 1127-1150

Hopfensitz A amp Wranik T (2009) How to adapt to changing markets experience and

personality in a repeated investment game Discussion Paper No 092009 - 056

Retrieved from httpsssrncomabstract=1578305

Hough L M Eaton N K Dunnette M D Kamp J D amp McCloy R A (1990)

Criterion-related validities of personality constructs and the effect of response

distortion on those validities Journal of Applied Psychology 75(5) 581

Hsee C K amp Weber E U (1997) A fundamental prediction error Selfndashothers

discrepancies in risk preference Journal of experimental psychology general

126(1) 45

Hsee C K Zhang J Cai C F amp Zhang S (2013) Overearning Psychological science

24(6) 852-859

Huang J Y Shieh J C amp Kao Y C (2016) Starting points for a new researcher in

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Huber J Palan S amp Zeisberger S (2017) Does Investor Risk Perception Drive Asset

Prices in Markets Experimental Evidence Working Paper Retrieved from

httpsssrncomabstract=3007878

Huberman G (2001) Familiarity breeds investment Review of Financial Studies 14(3)

659ndash680

Hulland J (1999) Use of partial least squares (PLS) in strategic management research a

review of four recent studies Strategic Management Journal 20(2) 195ndash204

Hunt S D amp Vitell S J (1993) The general theory of marketing ethics A retrospective

and revision in N C Smith and A John (eds) Ethics in Marketing Quelch (Irwin

Inc Homewood IL) pp 775ndash784

Hunter K amp Kemp S (2004) The personality of e-commerce investors Journal of


Iacobucci D (2010) Structural equations modeling Fit indices sample size and advanced

topics Journal of Consumer Psychology 20(1) 90-98

Imasheva A B amp Kim A M (2017) Psychological differences in financial decision-

making by people from different generations KazNU Bulletin Psychology and

sociology series 59(4) 50-56

Ishfaq M Maqbool Z Akram S Tariq S amp Khurshid M K (2017) Mediating Role

of Risk Perception between Cognitive Biases and Risky Investment Decision

Empirical Evidence from Pakistans Equity Market Journal of Managerial

Sciences 11(3) 265-278

Samra Chaudary

176

Ivkoviacutec Z amp Weisbenner S (2007) Information diffusion effects in individual

investorsrsquo common stock purchases covet thy neighborsrsquo investment choices

Review of Financial Studies 20(4) 1327-1357

Jabeen M (2016 June 16) PSX ndash Unfolding future prospects at its best Business

Recorder retrieved from httpsfpbrecordercom2016062016061657187

Jain P C amp Wu J S (2000) Truth in mutual fund advertising Evidence on future

performance and fund flows The Journal of Finance 55(2) 937-958

Jaiswal B amp Kamil N (2012) Gender behavioral finance and the investment decision

IBA Business Review 7(2) 8-22

Jaiyeoba H B amp Haron R (2016) A qualitative inquiry into the investment decision

behavior of the Malaysian stock market investors Qualitative Research in

Financial Markets 8(3) 246-267

Jenkins G D Mitra A Gupta N amp Shaw D (1998) Are financial incentives related

to performance A meta-analytic review of empirical research Journal of Applied

Psychology 83 777-787

Jensen M C amp Meckling W H (1976) Theory of the firm Managerial behavior agency

costs and ownership structure Journal of Financial Economics 3(4) 305-360

Jia S W Zhang W X Li P Feng T Y amp Li H (2013) Attitude toward money

modulates outcome processing An ERP study Social Neuroscience 8 43-51

John O P amp Srivastava S (1999) The Big-Five trait taxonomy History measurement

and theoretical perspectives Handbook of personality Theory and research

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Jordan B D amp Riley T B (2015) Volatility and mutual fund manager skill Journal of

Financial Economics 118 289-298

Josef A K Richter D Samanez-Larkin G R Wagner G G Hertwig R amp Mata R

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Journal of Personality and Social Psychology 111 430ndash450

Judge T A Heller D amp Mount M K (2002) Five-factor model of personality and job

satisfaction A meta-analysis Journal of Applied Psychology 87(3) 530

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Kahneman D (2012) Thinking fast and slow New York NY Penguin Books Ltd

Kahneman D amp Deaton A (2010) High income improves evaluation of life but not

emotional well-being Proceedings of the National Academy of Sciences of the

United States of America 107(38) 16489ndash16493

Kahneman D amp Riepe M W (1998) Aspects of investor psychology Journal of

Portfolio Management 24(1) 52-65

Kahneman D amp Tversky A (1979) Prospect theory an analysis of decision under risk

Econometrica 47(2) 263-292

Kahneman D amp Tversky A (1984) Choices Values and Frames American

Psychologist 39 341ndash35

Samra Chaudary

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Kahneman D Knetsch J L amp Thaler R H (1990) Experimental tests of the

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1325-1348

Kamp J D amp Gough H G (1986) The Big-Five personality factors from an assessment

context In 94th annual convention of the American Psychological Association

Washington DC

Kamp J D amp Hough L M (1986) Utility of personality assessment A review and

integration of the literature Utility of temperament biodata and interest

assessment for predicting job performance A review and integration of the

literature 88-02

Kang J K amp Stulz R (1997) Why is there a home bias An analysis of foreign portfolio

equity ownership in Japan Journal of Financial Economics 46(1) 3-28

Karlsson A amp Nordeacuten L (2007) Home sweet home Home bias and international

diversification among individual investors Journal of Banking amp Finance 31(2)

317-333

Kautonen T van Gelderen M amp Fink M (2015) Robustness of the theory of planned

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Theory and Practice 39(3) 655-674

Keller C amp Siegrist M (2006a) Investing in stocks The influence of financial risk

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Psychology 27(2) 285-303

Keller C amp Siegrist M (2006b) Money attitude typology and stock investment The


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Khwaja A I amp Mian A (2005) Unchecked intermediaries Price manipulation in an

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Kirkman B amp Law K (2005) International management research in AMJ Our past

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Kish-Gephart J J Harrison D A amp Trevintildeo L K (2010) Bad apples bad cases and

bad barrels Meta-analytic evidence about sources of unethical decisions at work

Journal of Applied Psychology 95 1-31

Kiyilar M amp Acar O (2013) Behavioral finance and the study of the irrational financial

choices of credit card users Annales Universitatis Apulensis series Oeconomica

ISSN 1454-9409

Kliger D amp Kudryavtsev A (2010) The availability heuristic and investors reaction to

company-specific events The Journal of Behavioral Finance 11(1) 50-65

Kline R B (2005) Principles and practice of structural equation modeling (2nd ed) New

York The Guildford Press

Kline R B (2015) Principles and practice of structural equation modeling Guilford

publications

Samra Chaudary

180

Klontz B T amp Britt S L (2012) How clientsrsquo money scripts predict their financial

behaviors Journal of Financial Planning 25(11) 33-43

Kobbeltvedt T amp Wolff K (2009) The Risk-as-feelings hypothesis in a Theory of

planned behavior perspective Judgment and Decision-making 4(7) 567

Kock N (2015) Common method bias in PLS-SEM A full collinearity assessment

approach International Journal of e-Collaboration 11(4) 1-10

Koropp C Kellermanns F W Grichnik D amp Stanley L (2014) Financial decision-

making in family firms An adaptation of the theory of planned behavior Family

Business Review 27(4) 307-327

Kourtidis D Šević Ž amp Chatzoglou P (2011) Investorsrsquo trading activity A behavioral

perspective and empirical results The Journal of Socio-Economics 40(5) 548-557

Krause M R Serlin R C Ward S E Rony R Y Z Ezenwa M O amp Naab F

(2010) Testing mediation in nursing research Beyond Baron and Kenny Nursing

Research 59(4) 288-294

Krueger N and Dickson P R (1994) How believing in ourselves increases risk taking

perceived self-efficacy and opportunity recognition Decision Sciences 25 (3) 385-

400

Krupp D B amp Cook T R (2018) Local competition amplifies the corrosive effects of

inequality Psychological Science 29(5) 824ndash833

Kubilay B amp Bayrakdaroglu A (2016) An empirical research on investor biases in

financial decision-making financial risk tolerance and financial personality

International Journal of Financial Research 7(2) 171-182

References

181

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Kumar S amp Goyal N (2015) Behavioral biases in investment decision-makingndasha

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108

Lagarde C (2016) The Role of Emerging Markets in a New Global Partnership for

Growth by IMF Managing Director Christine Lagarde Retrieved from

httpswwwimforgenNewsArticles201509280453sp020416

Lakonishok J Shleifer A amp Vishny R W (1994) Contrarian investment extrapolation

and risk The Journal of Finance 49(5) 1541-1578

Lakshmi P Visalakshmi S Thamaraiselvan N amp Senthilarasu B (2013) Assessing

the Linkage of Behavioral Traits and Investment Decisions Using SEM Approach

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Laroche M Kim C amp Zhou L (1996) Brand familiarity and confidence as determinants

of purchase intention An empirical test in a multiple brand context Journal of

Business Research 37(2) 115-120

Law K S Wong C S amp Mobley W M (1998) Toward a taxonomy of

multidimensional constructs Academy of Management Review 23(4) 741-755

Lea S E G amp Webley P (2006) Money as tool money as drug The biological

psychology of a strong incentive Behavioral and Brain Sciences 29 161-176

Lemrova S Reiterova E Fatenova R Lemr K amp Tang T L P (2014) Money is

power Monetary intelligencemdashlove of money and temptation of materialism

among Czech University students Journal of Business Ethics 125(2) 329-348

Samra Chaudary

182

Lewis K K (1999) Trying to explain home bias in equities and consumption Journal of

Economic Literature 37(2) 571-608

Li D Jiang Y An S Shen Z amp Jin W (2009) The influence of money attitudes on

young Chinese consumers compulsive buying Young Consumers 10(2) 98-109

Li S amp Liu C J (2008) Individual differences in a switch from risk‐averse preferences

for gains to risk‐seeking preferences for losses can personality variables predict

the risk preferences Journal of Risk Research 11(5) 673-686

Lim K L Soutar G N amp Lee J A (2013) Factors affecting investment intentions A

consumer behavior perspective Journal of Financial Services Marketing 18(4)

301-315

Lim V K amp Teo T S (1997) Sex money and financial hardship An empirical study

of attitudes towards money among undergraduates in Singapore Journal of


Lintner J (1965) The valuation of risky assets and the selection of risky investment in

stock portfolio and capital budgets Review of Economics and Statistics 47 103ndash

124

Locke E A Feren D B McCaleb V M Shaw K N amp Denny A T (1980) The

relative effectiveness of four methods of motivating employee performance In K

D Duncan M M Gruneberg amp D Wallis (Eds) Changes in Working Life 363-

388 New York Wiley

Lodder P Ong H H Grasman R P amp Wicherts J (2019) A comprehensive meta-

analysis of money priming Journal of Experimental Psychology General

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analysis (4th ed) Hillsdale NJ Lawrence Erlbaum Associates

Loewenstein G F Weber E U Hsee C K amp Welch N (2001) Risk as feelings

Psychological Bulletin 127(2) 267-286

Loewenstein G amp Lerner J S (2003) The role of affect in decision-making Handbook

of affective science 619(642) 3

MacCrimmon K R amp Wehrung D A (1990) Characteristics of risk taking executives

Management Science 36(4) 422-435

MacGregor D G amp Slovic P (2000) Retirement Plans and Financial Expectations A

Survey of Leading-Edge lsquoBaby Boomersrsquo Retrieved from


Mahastanti L A amp Hariady E (2013) Determining the Factor Affecting Stock

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of the International Conference on Managing the Asian Century 275-282

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Markowitz H (1952) Portfolio Selection The Journal of Finance 7(1) 77-91

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Macmillan

Mayfield C Perdue G amp Wooten K (2008) Investment management and personality

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McClelland D C (1967) Money as a motivator Some research insights The McKinsey

Quarterly 10ndash21

Samra Chaudary

184

McClure R F (1984) The relationship between money attitudes and overall pathology

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McCrae R R amp Costa P T (2008) Empirical and theoretical status of the five-factor

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Handbook of Personality Theory and Assessment Personality Measurement and

Testing Sage London 273-294

McInish T H (1982) Individual investors and risk-taking Journal of Economic


McKenzie C R amp Liersch M J (2011) Misunderstanding savings growth Implications

for retirement savings behavior Journal of Marketing Research 48(SPL) S1-S13

McShane S L amp Von Glinow M A (2008) Organizational behavior (4th ed) Boston

McGraw-Hill Irwin

Medina J F Saegert J amp Gresham A (1996) Comparison of Mexican‐American and

Anglo‐American attitudes toward money Journal of Consumer Affairs 30(1) 124-

145

Merton R C (1973) An intertemporal capital asset pricing model Econometrica Journal

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Merton R C (1987) A simple model of capital market equilibrium with incomplete

information The Journal of Finance 42(3) 483-510

Metawa N Hassan M K Metawa S amp Safa M F (2019) Impact of behavioral factors

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References

185

Michaelidou N amp Hassan L (2014) New advances in attitude and behavioral decision-

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Milkovich G T Newman J M amp Gerhart B (2014) Compensation (11th ed) Boston

IrwinMcGraw-Hill

Millet K Lamey L amp Van den Bergh B (2012) Avoiding negative vs achieving

positive outcomes in hard and prosperous economic times Organizational

Behavior and Human Decision Processes 117(2) 275ndash 284

Mishra S (2014) Decision-making under risk Integrating perspectives from biology

economics and psychology Personality and Social Psychology Review 18(3)

280-307

Mishra S Hing L S S amp Lalumiere M L (2015) Inequality and risk-taking

Evolutionary Psychology 13(3) 1ndash11

Mitchell T R amp Mickel AE (1999) The meaning of money An individual difference

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Modesto Veludo-de-Oliveira T Augusto Falciano M amp Villas Boas Perito R (2014)

Effects of credit card usage on young Braziliansrsquo compulsive buying Young

Consumers 15(2) 111-124

Modigliani F amp Miller M H (1958) The cost of capital corporation finance and the

theory of investment American Economic Review 48(3) 261ndash297

Mohammadi A amp Shafi K (2018) Gender differences in the contribution patterns of

equity-crowdfunding investors Small Business Economics 50(2) 275-287

Morse W C (1998) Risk taking in personal investments Journal of Business and


Samra Chaudary

186

Mousavi S amp Gigerenzer G (2014) Risk uncertainty and heuristics Journal of


Muller A amp de Zwaan M (2010) Pathological buying A review of the current

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Gesundheitsforschung Gesundheitsschutz 53(4) 289-294

Muradoglu G amp Harvey N (2012) Behavioural finance the role of psychological

factors in financial decisions Review of Behavioural Finance 4(2) 68-80

Myers I B amp McCaulley M H (1985) Manual A guide to the development and use of

the Myer-Briggs Type Indicator Palo Alto CA Consulting Psychologists Press

Newman J M Gerhart B amp Milkovich G T (2017) Compensation (12th ed) New

York McGraw-Hill

Nicholson N Soane E Fenton‐OCreevy M amp Willman P (2005) Personality and

domain‐specific risk taking Journal of Risk Research 8(2) 157-176

Nkundabanyanga S K Omagor C Mpamizo B amp Ntayi J M (2011) The love of

money pressure to perform and unethical marketing behavior in the cosmetic

industry in Uganda International Journal of Marketing Studies 3 (4) 40-49

Nnedum O A U Egwu E U Obinna E J Ntomchukwu M S amp Chukwukeluo C

B (2011) Materialism and meaning of money (MOM) Validation of Money

Metaphor Scale (MMS) in South Africa International Research Journal of

Finance amp Economics 76 31ndash46

Nofsinger J (2005) The Psychology of Investing 2nd ed Prentice Hall NJ

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187

Noller P Law H amp Comrey A L (1987) Cattell Comrey and Eysenck personality

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Norden L (2010) Individual home bias portfolio churning and performance The

European Journal of Finance 16(4) 329-351

Norman W T (1963) Toward an adequate taxonomy of personality attributes Replicated

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Social Psychology 66(6) 574

Nosic A amp Weber M (2010) How riskily do I invest The role of risk attitudes risk

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OrsquoDonoghue T amp Rabin M (1998) Procrastination in preparing for retirement in

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Institution and Russell Sage Foundation Washington DC 125-56

Odean T (1998) Are investors reluctant to realize their losses The Journal of Finance

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Odean T (1999) Do investors trade too muchrdquo The American Economic Review 89(5)

1279-1299

Oehler A amp Wedlich F (2018) The relationship of extraversion and neuroticism with

risk attitude risk perception and return expectations Journal of Neuroscience

Psychology and Economics 11(2) 63

Oehler A Wendt S Wedlich F amp Horn M (2018) Investors personality influences

investment decisions Experimental evidence on extraversion and neuroticism


Samra Chaudary

188

Oezgen O amp Bayoğlu A S (2005) Turkish college studentsrsquo attitudes towards money

International Journal of Consumer Studies 29(6) 493-501

Olsen R A (1997) Desirability bias among professional investment managers Some

evidence from experts Journal of Behavioral Decision-making 10(1) 65-72

Olsen R A amp Cox C M (2001) The influence of gender on the perception and response

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Oshio A Taku K Hirano M amp Saeed G (2018) Resilience and Big-Five personality

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Pagano M (1993) Financial markets and growth an overview European Economic

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Pak O amp Mahmood M (2015) Impact of personality on risk tolerance and investment

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Commerce and Management 25(4) 370-384

Pakistan Bureau of Statistics (2017) Population Census Retrieved from

httpwwwpbsgovpkcontentpopulation-census

Pan C H amp Statman M (2013) Investor personality in investor questionnaires The

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Paramati S R Ummalla M amp Apergis N (2016) The effect of foreign direct

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market economies Energy Economics 56 29-41

Payne B K Brown-Iannuzzi J L amp Hannay J W (2017) Economic inequality

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Pennings J M Candel M J amp Egelkraut T M (2003) A behavioral decision-making

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Phillips J M amp Gully S M (2013) Organizational Behavior Tools for success (2nd

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Pompian M M (2012) Behavioral Finance and Wealth Management 2nd ed John

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Pompian M M amp Longo J M (2004) A new paradigm for practical application of

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Poropat A E (2009) A meta-analysis of the five-factor model of personality and

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Poterba J M (2000) Stock market wealth and consumption Journal of Economic

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Prahalad C K amp Hammond A (2002) Serving the worldrsquos poor profitably Harvard

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Prast H Rossi M Torricelli C amp Sansone D (2015) Do women prefer pink The

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Economica 31(3) 377-420

Samra Chaudary

190

Preacher K amp Hayes A (2008) Asymptotic and resampling strategies for assessing and

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Methods 40(3) 879ndash891

Prinz S Gruumlnder G Hilgers R D Holtemoumlller O amp Vernaleken I (2014) Impact of

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Puustinen P Maas P amp Karjaluoto H (2013) Development and validation of the

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54

Ratcliffe A amp Taylor K (2015) Who cares about stock market booms and busts

Evidence from data on mental health Oxford Economic Papers-New Series 67 (3)

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Raubenheimer J (2004) An item selection procedure to maximize scale reliability and

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Raut R K Das N amp Kumar R (2018) Extending the Theory of Planned Behavior

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Reinartz W Haenlein M amp Henseler J (2009) An empirical comparison of the efficacy

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Riff S amp Yagil Y (2016) Behavioral Factors Affecting the Home Bias Phenomenon

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Ringle C M Sarstedt M amp Straub D (2012) A critical look at the use of PLS-SEM in

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Ringle C M Wende S amp Becker J M (2015) SmartPLS 30 (version 323)

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Rose G M amp Orr L M (2007) Measuring and exploring symbolic money meaning

Psychology amp Marketing 24(9) 743ndash761

Rosler M Retz W Retz-Junginger P Thome J Supprian T Nissen T amp Trott G

E (2004) Tools for the diagnosis of attention-deficithyperactivity disorder in

adults Self-rating behavior questionnaire and diagnostic checklist Der Nervenarzt

75(9) 888-895

Rubenstein C (1981) Money and self-esteem relationships secrecy envy satisfaction

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Rynes S L amp Gerhart B (2000) Compensation in organizations Current research and

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SampP Global Fin Lit Survey (2015) Global Financial Literacy Excellence Center Retrieved

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Sahi S K Arora A P amp Dhameja N (2013) An exploratory inquiry into the

psychological biases in financial investment behaviors Journal of Behavioral

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Salgado J F (1997) The five-factor model of personality and job performance in the

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Sardzoska E G amp Tang T L P (2009) Testing a model of behavioral intentions in the

Republic of Macedonia Differences between the private and the public

sectors Journal of Business Ethics 87(4) 495-517

Sardzoska E G amp Tang T L P (2012) Work-related behavioral intentions in

Macedonia Coping strategies work environment love of money job satisfaction

and demographic variables Journal of Business Ethics 108(3) 373-391

Sardzoska E G amp Tang T L P (2015) Monetary intelligence Money attitudes-

unethical intentions intrinsic and extrinsic job satisfaction and coping strategies

across public and private sectors in Macedonia Journal of Business Ethics 130(1)

93ndash115

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Satchell L P Bacon A M Firth J L amp Corr P J (2018) Risk as reward

Reinforcement sensitivity theory and psychopathic personality perspectives on

everyday risk-taking Personality and Individual Differences 128 162-169

Saucier G amp Goldberg L R (1996) The language of personality Lexical perspectives

The five-factor model of personality Theoretical perspectives 21-50

Saunders M Lewis P amp Thornhill A (2007) Research methods Business Students 6th

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Scandura T A (2016) Essentials of organizational behavior An evidence-based

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Schumacker R E amp Lomax R G (1996) A beginnerrsquos guide to structural equation

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Schwartz H (2010) Heuristics or rules of thumb In J Nofsinger amp K Baker (Eds)

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Seasholes M S amp Zhu N (2010) Individual investors and local bias The Journal of

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httpswwwsecpgovpkwp-contentuploads201607July-19-2016-SECP-

determined-to-ensure-investor-protection-and-to-end-market-abusepdf

Seiler M J Seiler V L Harrison D M amp Lane M A (2013) Familiarity bias and

perceived future home price movements Journal of Behavioral Finance 14(1) 9-

24

Samra Chaudary

194

Seiler M Seiler V Traub S amp Harrison D (2008) Familiarity bias and the status quo

alternative Journal of Housing Research 17(2) 139-154

Sekścińska K Rudzinska-Wojciechowska J amp Maison D (2018) Individual

differences in time perspectives and risky financial choices Personality and

Individual Differences 120 118-126

Shachat J amp Zhang Z (2017) The Hayek Hypothesis and Long‐run Competitive

Equilibrium An Experimental Investigation The Economic Journal 127(599)

199-228

Shariff M Z Al-Khasawneh J amp ElSharif A (2012) Future of Neurofinance and

Behavioral Finance in Class Room International Journal of Finance 24(2) 7200-

7207

Sharpe W (1964) Capital asset prices a theory of market equilibrium under the condition

of risk Journal of Finance 19(3) 425ndash 442

Shawahna R Fahed B Qadri D Sharawi L Soroghli M amp Dweik M (2017)

Awareness and knowledge of autism spectrum disorders among pharmacists a

cross-sectional study in Palestinian pharmacy practice Journal of Autism and

Developmental Disorders 47(6) 1618-1627

Shefrin H amp Statman M (1985) The disposition to sell winners too early and ride losers

too long theory and evidence Journal of Finance 40(3) 777-790

Shih T Y amp Ke S C (2014) Determinates of financial behavior insights into consumer

money attitudes and financial literacy Service Business 8(2) 217-238

Shiller R (2003) From efficient markets theory to behavioral finance The Journal of

Economic Perspectives 17(1) 83-104

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and Individual Differences 32(3) 415-429

Shleifer A amp Summers L H (1990) The noise trader approach to finance Journal of


Shrout P E amp Bolger N (2002) Mediation in experimental and non-experimental

studies new procedures and recommendations Psychological Methods 7(4) 422ndash

445

Simon H A (1955) A behavioral model of rational choice The Quarterly Journal of

Economics 69(1) 99-118

Singh R (2010) Behavioral Finance Studies Emergence and Developments Journal of

Contemporary Management Research 4(2) 1-9

Singhapakdi A Vitell S J Lee D J Nisius A M amp Grace B Y (2013) The

influence of love of money and religiosity on ethical decision-making in marketing

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Sirri E R amp Tufano P (1998) Costly search and mutual fund flows Journal of Finance

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Sizemore C (2012 November 20) Investing lessons Avoiding the Peter Lynch Bias

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httpwwwforbescomsitesmoneybuilder20121120investing-lessons-

avoiding-the-peter-lynch-bias

Sloan A (2002) The Jurys In Greed Isnt Good Newsweek 139(25) 37-37

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Slovic P Fischhoff B and Lichtenstein S (1977) lsquoBehavioral Decision Theoryrsquo Annual

Review of Psychology 28(1) 1-39

Smith A (17761937) An inquiry into the nature and causes of the wealth of nations New

York Modern Library

Statman M Thorley S amp Vorkink K (2006) Investor overconfidence and trading

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Steenkamp J B E amp Baumgartner H (1998) Assessing measurement invariance in

cross-national consumer research Journal of Consumer Research 25(1) 78-90

Sternad D amp Kennelly J J (2017) The sustainable executive antecedents of managerial

long-term orientation Journal of Global Responsibility 8(2) 179-195

Stone M (1974) Cross‐validatory choice and assessment of statistical predictions

Journal of the Royal Statistical Society Series B (Methodological) 36(2) 111-133

Strong N amp Xu X (2003) Understanding the equity home bias Evidence from survey

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Subrahmanyam A (2008) Behavioral finance a review and synthesis European

Financial Management 14(1) 12-29

Sutcliffe K M (1994) What executives notice accurate perceptions in top management

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Szyszka A Zielonka P (2007) The Disposition Effect Demonstrated on IPO Trading

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Takahashi H amp Terano T (2003) Agent-based approach to investorrsquos behavior and asset

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Tang N Chen J Zhang K amp Tang T L P (2018a) Monetary wisdom How do

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Tang T L P (1992) The Meaning of money revisited Journal of Organizational

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Tang T L P (1993) The meaning of money Extension and exploration of the money

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Behavior 14(1) 93-99

Tang T L P (1995) The development of a short Money Ethic Scale Attitudes toward

money and pay satisfaction revisited Personality and Individual Differences

19(6) 809ndash817

Tang T L P (2007) lsquoIncome and Quality of Life Does the Love of Money Make a

Differencersquo Journal of Business Ethics 72(4) 375ndash393

Tang T L P (2016) Theory of monetary intelligence Money attitudesmdashreligious values

making money making ethical decisions and making the grade Journal of

Business Ethics 133(3) 583ndash603

Tang T L P amp Chen Y J (2008) Intelligence vs wisdom The love of money

Machiavellianism and unethical behavior across college major and gender Journal

of Business Ethics 82(1) 1ndash26

Tang T L P amp Chiu R K (2003) Income money ethic pay satisfaction commitment

and unethical behavior Is the love of money the root of evil for Hong Kong

Samra Chaudary

198

employees Journal of Business Ethics 46(1) 13ndash30

Tang T L P amp Gilbert P R (1995) Attitudes toward money as related to intrinsic and

extrinsic job satisfaction stress and work-related attitudes Personality and


Tang T L P amp Sutarso T (2013) Falling or not falling into temptation Multiple faces

of temptation monetary intelligence and unethical intentions across gender

Journal of Business Ethics 116(3) 529ndash552

Tang T L P Chen Y J amp Sutarso T (2008a) Bad apples in bad (business) barrels

The love of money Machiavellianism risk tolerance and unethical behavior

Management Decision 46(2) 243-263

Tang T L P Kim J K amp Shin-Hsiung Tang D (2000) Does Attitude Toward Money

Moderate the Relationship Between Intrinsic Job Satisfaction and Voluntary

Turnover Human Relations 53(2) 213ndash245

Tang T L P Luna-Arocas R amp Sutarso T (2005) lsquoFrom Income to Pay Satisfaction

The Love of Money and Pay Equity Comparison as Mediators and Culture (the US

and Spain) and Gender as Moderators Management Research The Journal of the

Iberoamerican Academy of Management 3(1) 7ndash26

Tang T L P Sutarso T Akande A Allen M W Alzubaidi A S Ansari M A et

al (2006) The love of money and pay level satisfaction Measurement and

functional equivalence in 29 geographical entities around the world Management

and Organization Review 2(3) 423ndash452

Tang T L P Sutarso T Ansari M A Lim V K G Teo T S H Arias-Galicia F

amp Vlerick P (2018b) Monetary intelligence and behavioral economics across

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199

32 cultures Good apples enjoy good quality of life in good barrels Journal of

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Tang T L P Sutarso T Ansari M A Lim V K G Teo T S H Arias-Galicai F

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Proceedings of the 2011 Annual Meeting of the Academy of Management DOI

105465AMBPP201165869480

Tang T L P Sutarso T Ansari M A Lim V K Teo T S Arias-Galicia F amp

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(CPI) and dishonesty across 31 geopolitical entities Journal of Business Ethics

148(4) 919-937

Tang T L P Sutarso T Davis G M T Dolinski D Ibrahim A H S amp Wagner S

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Tang T L P T Sutarso A Akande M W Allen A S Alzubaidi M A Ansari F

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Stembridge T L N Tang T S H Teo M Tombolani M Trontelj C Urbain and

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Samra Chaudary

200

Development Make a Difference Paper presented at the Academy of Management

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94-117

Tauni M Z Fang H X amp Yousaf S (2015) The influence of Investor personality traits

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Tekce B Yılmaz N amp Bildik R (2016) What factors affect behavioral biases

Evidence from Turkish individual stock investors Research in International

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Thaler R (1980) Toward a positive theory of consumer choice Journal of Economic

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Thaler R (1999) Mental accounting matters Journal of Behavioral Decision-making

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Thaler R H amp Sunstein C R (2008) Nudge improving decisions about health wealth

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Tigges P Riegert A Jonitz L Brengelmann J amp Engel R R (2000) Risk behavior

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201

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Tomek I Striacuteteskyacute V amp Tahal R (2013) Segmentation of Czech Consumers Based on

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Trapmann S Hell B Hirn J O W amp Schuler H (2007) Meta-analysis of the

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Tripathi M amp Chattopadhyay T (2013) Study of Behavioral Dimensions of Perceived

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Tung R L amp Baumann C (2009) Comparing the attitudes toward money material

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Resource Management 20(11) 2382-2401

Tupes E C amp Christal R E (1961) Recurrent personality factors based on trait ratings

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Tversky A and Kahneman D (1986) Rational choice and the framing of the decision

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Samra Chaudary

202

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probability Cognitive psychology 5(2) 207-232

Tversky A amp Kahneman D (1974) Judgment under uncertainty Heuristics and biases

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Tversky A amp Kahneman D (1981) The framing of decisions and the psychology of

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Van Witteloostuijin A amp Muehlfeld K S (2008) Traders personality and trading

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httpeconpapersrepecorgpaperusetkiwps0828htm

Velicer W F amp Fava J L (1998) Affects of variable and subject sampling on factor

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Verma M (2008) Wealth management and behavioral finance The effect of

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Vitell S J Paolillo J G amp Singh J J (2006) The role of money and religiosity in

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Vitell S J Singh J J amp Paolillo J G (2007) Consumersrsquo ethical beliefs The roles of

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369-379

Vohs K D (2015) Money priming can change peoplersquos thoughts feelings motivation

and behaviors An update on 10 years of experiments Journal of Experimental

References

203

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Vohs K D Mead N C amp Goode M R (2006) The psychological consequences of

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Von Thadden E L (1995) Long-term contracts short-term investment and monitoring

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Wang C M Xu B B Zhang S J amp Chen Y Q (2016) Influence of personality and

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Wang M Keller C amp Siegrist M (2011) The less you know the more you are afraid

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Finance 12(1) 9-19

Wang X L Shi K amp Fan H X (2006) Psychological mechanisms of investors in

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Warren G (2014) Long-Term Investing What Determines Investment Horizon Centre

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Warren G (2016) What does it mean to be a long-term investor (July 2016) Brandes

Institute Research Paper No 2016-04 Retrieved from


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economic and neuroeconomic explanations of risk preference In P Glimcher C

Samra Chaudary

204

Camerer E Fehr amp R Poldrack (Eds) Neuroeconomics Decision-making and

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Weber E U amp Milliman R A (1997) Perceived risk attitudes Relating risk perception

to risky choice Management Science 43(2) 123-144

Weber E U Blais A R amp Betz N E (2002) A domain‐specific risk‐attitude scale

Measuring risk perceptions and risk behaviors Journal of Behavioral Decision-

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Weber E U Siebenmorgen N amp Weber M (2005) Communicating asset risk how

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Weber M Weber E U amp Nosić A (2013) Who takes risks when and why

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Finance 54(2) 581-622

Wernimont PF amp Fitzpatrick S (1972) The meaning of money Journal of Applied


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205

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Wood R E Goodman J S Beckmann N amp Cook A (2008) Mediation testing in

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179

Woolley P (2013) Resilience and the Long-term Rethinking Portfolios for Prosperity

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Xu H amp Tracey T J (2017) Use of Multi-Group Confirmatory Factor Analysis in

Examining Measurement Invariance in Counseling Psychology Research The

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Yalcin K C Tatoglu E amp Zaim S (2016) Developing an instrument for measuring the

effects of heuristics on investment decisions Kybernetes 45(7) 1052-1071

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trading volume A dyad study in the futures market Emerging Markets Finance

and Trade 48(3) 23-34

Samra Chaudary

206

Zakaria R H Jaafar N I M amp Marican S (2012) Financial behavior and financial

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Scientific Research 12(10) 1396-1402

Zeisberger S (2018) What is risk how investors perceive risk in return distributions


Zhang L Q (2009) An exchange theory of money and self-esteem in decision-

making Review of General Psychology 13(1) 66-76

Zhao H Seibert S E amp Lumpkin G T (2010b) The relationship of personality to

entrepreneurial intentions and performance A meta-analytic review Journal of

Management 36(2) 381ndash404-

Zhao X Lynch Jr J G amp Chen Q (2010a) Reconsidering Baron and Kenny Myths

and truths about mediation analysis Journal of Consumer Research 37(2) 197-

206

Zhao H amp Seibert S (2006) The Big-Five personality dimensions and entrepreneurial

status A meta-analytical review Journal of Applied Psychology 91(2) 259-271

Appendix

207

Appendices

Appendix I Supporting Literature for Relationships of Paper 1 Relationships Supporting

Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Personality and

Decision-making

Heinstrom 2003

Nicholson et al

2005 Zhao amp

Seibert 2006

Mayfield et al

2008 Lim at al

2013 Oehler amp

Wedlich 2018

Oehler et al 2018

Heinstrom 2003

Van Witteloostuijin

amp Muehlfeld 2008

Durand et al 2008

Weber amp Milliman

1997 Keller amp

Siegrist 2006ab

Bateman et al

2010 Weber et al

2013 Hoffman et

al 2015 Duxbury

et al 2005 Weber

et al 2002

Hopfensitz amp

Wranik 2009

Borghans et al

2009

Verma 2008 Riaz

amp Hunjra 2016

Tauni et al

20152016 Yang et

al 2012 Wang et

al 2006 Personality and

Investment

Decisions

Oehler et al 2018

Mayfield et al

2008 Oehler amp

Wedlich 2018

Hershey amp Mowen

2000 Hunter amp

Kemp 2004 van

Witteloostuijin amp

Muehlfeld 2008

Durand et al 2008

2013 Tauni et al

2015 2016 Yang

et al 2012

Brandstatter 2011

Hopfensitz amp

Wranik 2009

Personality Short-

term and Long-

term Investment

Decisions

Mayfield et al

2008

Personality and

Risk Taking

Behavior

Nicholson et al

2005 Zhao amp

Seibert 2006

Weber et al 2002

Filbeck et al 2005

Mayfield et al

2008 Brandstatter

2011 Hopfensitz amp

Wranik 2009

Borghans et al

2009

Risk Taking and

Decision-making

Riaz amp Hunjra

2016

MacCrimmon amp

Wehrung 1990

Samra Chaudary

208

Weber amp Milliman

1997 Keller amp

Siegrist 2006a b

Nosic amp Weber

2010 Bateman et

al 2010 Weber et

al 2013 Hoffman

et al 2015 Lim at

al 2013 Duxbury

et al 2005 Weber

et al 2002 Wang

et al 2006

Loewenstein et al

2001 Weber amp

Johnson 2008

Big-Five

Personality Short-

term and Long-

term Investment

Decisions

This Study

Big-Five

Personality Risk

Perception Short-

term and Long-

term Investment

Decisions

This Study

Appendix

209

Appendix II Supporting Literature for Relationships of Paper 2 Relationships Supporting

Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Heuristics and

Decision-making

Tversky amp

Kahneman 1974

Kahneman amp

Tversky 1979

Tversky amp

Kahneman 1981

De Bondt 1998 De

Bondt amp Thaler

1985 Shefrin amp

Statman 1985

Tversky amp

Kahneman 1992

Lakonishok et al

1994 Fox amp

Tversky 1995

Kahneman amp

Riepe 1998

Odean 1998 1999

Thaler 1999 Jain

amp Wu 2000

Hirshleifer 2001

Huberman 2001

Barber et al 2005

Grinblatt amp Han

2005 Nofsinger

2005 Mishra

2014 Yalcin et al

2016 Ahearne et

al 2004 Wang et

al 2011 Lewis

1999 Barberis amp

Xiong 2009

Wermers 1999

Barber amp Odean

2001 Statman et

al 2006 Epley amp

Gilovich 2005

Furnham amp Boo

2011 Glaser et al

2007 Thaler amp

Sunstein 2008

Kahneman amp

Tversky 1979 De

Bondt amp Thaler

1985 Fox amp

Tversky 1995

Tversky amp

Kahneman 1992

De Bondt 1998

Jain amp Wu 2000

Wang et al 2011

Grinblatt amp

Keloharju 2001

Lakonishok et al

1994 Coval amp

Moskowitz 1999

Chan et al 2005

Ahearne et al

2004 Olsen 1997

Borges et al 1999

Barber amp Odean

2001 Kang amp

Stulz 1997 Odean

1998 1999 Lewis

1999 Wermers

1999 Epley amp

Gilovich 2005

Huberman 2001

Barber et al 2005

Statman et al

2006 Glaser et al

2007 Wang et al

2011 Tversky amp

Kahneman 1981

Riff amp Yagil 2016

Yalcin et al 2016

Jaiyeoba amp Haron

2016 De Vries et

al 2017 Chan et

al 2005 Olsen

1997 Metawa et

al 2019

Samra Chaudary

210

Salience and

Investment

Decisions

Yalcin et al 2016

Huberman 2001

Tverskyamp

Kahneman 1973

Merton 1987

Heath amp Tversky

1991 Fox amp

Tversky 1995

Sirri amp Tufano

1998 Jain amp Wu

2000 Barber et al

2005 Nofsinger

2005Wang et al

2011 Grinblatt amp

Keloharju 2001

Jaiyeoba amp Haron

2016 Antoniou et

al 2010 Baker amp

Ricciardi 2014

Chan et al 2005

Riff amp Yagil 2016

Sizemore 2012

Giannetti amp

Koskinen 2010

Kumar amp

Goetzmann 2003

De Vries et al

2017 Chan et al

2005 Weber et al

2005

Institutional

Investors and

Salience

Coval amp

Moskowitz 1999

Strong amp Xu 2003

Chan et al 2005

Olsen 1997

Borges et al 1999

Goldstein amp

Gigerenzer 2002

Forbes et al 2015

Individual

Investors and

Salience

Baxter 1994

French amp Poterba

1991

Baker et al 2017

De Vries et al

2017 Tesar amp

Werner 1995

Appendix

211

Ahearne et al

2004 Kang amp

Stulz 1997

Seasholes amp Zhu

2010 Karlsson amp

Norden 2007

Cooper amp Kaplanis

1994

Gender and

Salience

Anderson et al

2011 Alrabadi et

al 2018 Ang et

al 2014 Cao et al

2009 Feng amp

Seasholes 2008

Karlsson amp Norden

2007

Mohammadi amp

Shafi 2018

Prast et al 2015

Seiler et al 2008

Seiler et al 2013

Tekce et al 2016

Wang et al 2011

Anderson et al

2011 Karlsson amp

Norden 2007

Mohammadi amp

Shafi 2018 Prast et

al 2015

Seiler et al 2008

Seiler et al 2013

Wang et al 2011

Alrabadi et al

2018 Feng amp

Seasholes 2008

Tekce et al 2016

Salience Short-

term and Long-

term Investment

Decisions

This Study

Salience

Institutional

Investors

Individual

Investors Gender

Short-term and

Long-term

Investment

Decisions

This Study

Samra Chaudary

212

Appendix III Supporting Literature for Relationships of Paper 3 Relationships Supporting

Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Attitudes and

Decision-making

Mahastanti amp

Hariady 2013

Akhtar amp Das

2019

Lim amp Teo 1997

Keller amp Siegrist

2006a Tang et al

2006 Vitell et al

2007 Tang et al

2008 Tang amp

Chen 2008 Klontz

amp Britt 2012

Gentina et al 2018

Hampson et al

2018 Tang amp Chiu

2003 Medina et al

1996 Yamauchi amp

Templer 1982

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Tang et al

2006 Li et al

2009 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011 Jia

et al 2013

Sardzoska ampTang

2012 Mahastanti amp

Hariady 2013 Shih

amp Ke 2014 Tang

et al 2018a

Akhtar amp Das 2019

Money Attitudes

and Decision-

making

Tang amp Chiu 2003

Vitell et al 2007

Tang et al

2008ab Tang amp

Chen 2008 Li et

al 2009 Klontz amp

Britt 2012 Shih amp

Ke 2014 Tang

2016 Britt 2016

Tang et al 2018a

Greenberg amp

Hershfield 2019

Money Attitudes

and Investment

Decisions

Keller amp Siegrist

2006a Jia et al

2013 Shih amp Ke

2014 Tang et al

2018a

Demographics and

Money Attitudes

Lim amp Teo 1997

Tang amp Chiu 2003

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011

Hampson et al

2018 Gentina et al

2018 Yamauchi amp

Templer 1982

Medina et al 1996

Tang amp Chiu 2003

Tang et al 2006

Tang et al

2008ab Sardzoska

ampTang 2012

Demographics and

Investment

Decision

Warneryd 2001

Haisley et al 2008

Greenberg amp

Appendix

213

Hershfield 2019

Cicchetti amp Dubin

1994 Grable et al

2004 Hlouskova et

al 2017

Greenberg 2013

Embrey and Fox

1997

Money Attitudes

Short-term and

Long-term

Investment

Decisions

This Study

Money Attitudes

Income

Inheritance Short-

term and Long-

term Investment

Decisions

This Study

Samra Chaudary

214

Appendix IV List of Financial Institutions 1 Aba Ali Securities- Karachi

2 Alfalah Investments- Karachi

3 Allied Bank Limited (ABL)- Asset Management Company- Lahore

4 Arif Habib- Karachi

5 Bank Islami Pakistan Limited Securities (BIPL)- Karachi

6 Central Depository Company (CDC) - Karachi

7 Faysal - Asset Management Company- Lahore


9 Foundation Securities- Karachi

10 IGI Insurance- Lahore

11 Insight Securities- Karachi

12 JS Global Capital- Karachi

13 JS Global Capital- Lahore

14 Meezan - Asset Management Company-Lahore

15 Muslim Commercial Bank (MCB) - Asset Management Company

16 NBP Fullerton Asset Management Limited (NAFA)- Lahore

17 Pakistan Stock Exchange- Lahore

18 Pakistan Stock Exchange-Karachi

19 Shajar Capital- Karachi

20 Silk - Asset Management Company- Lahore

21 Topline Securities- Karachi

22 United Bank Limited (UBL) - Asset Management Company- Karachi

23 United Bank Limited (UBL) - Asset Management Company- Lahore

Appendix

215

Appendix V Paper 1 Structural Models (Mediation)


neuroticism and short-term investment decision


extraversion and short-term investment decision

Samra Chaudary

216

Figure 25 Structural model of the mediating effect of risk perception between openness

and short-term investment decision


agreeableness and short-term investment decision

Appendix

217


conscientiousness and short-term investment decision


neuroticism and long-term investment decision

Samra Chaudary

218


extraversion and long-term investment decision


and long-term investment decision

Appendix

219


agreeableness and long-term investment decision


conscientiousness and long-term investment decision

Samra Chaudary

220

Appendix VI Questionnaire

This questionnaire is aimed at collecting data for PhD thesis in Business Administration

Please fill the questionnaire to the best of your knowledge The information taken is purely

for research purpose and will be kept confidential Thank you for taking the time to assist

me in my educational endeavours

1 2 3 4 5

Strongly Disagree Disagree Neutral Agree Strongly Agree

Short-Term Investment

Decision

(Mayfield et al 2008)

1-I intend to put at least half of my

investment money into the stock market

1 2 3 4 5

2-I intend to engage in portfolio

management activities at least twice per

week

1 2 3 4 5

3-I intend to perform my own investment

research instead of using outside advice

1 2 3 4 5

4-I intend to compare my portfolio

performance to that of professional

managers

1 2 3 4 5

Long-Term Investment

Decision


5-I intend to save at least 10 of my

gross earnings for investing saving

retirement purposes

1 2 3 4 5

6-I intend to have a portfolio that focuses

on multiple asset classes (ie shares

bonds cash real estate etc)

1 2 3 4 5

7-I intend to take an investments course 1 2 3 4 5

8-I intend to manage my portfolio for

maximum gross return rather than tax

and cost efficiency

1 2 3 4 5

9-I intend to invest some money in long-

term assets where my money will be tied

up and inaccessible for years

1 2 3 4 5

Neuroticism

(Costa amp McCrae 1992)

10-I often feel inferior to others 1 2 3 4 5

11-When Im under a great deal of stress

sometimes I feel like Im going to pieces

1 2 3 4 5

12-I often feel tense and jittery 1 2 3 4 5

13-Sometimes I feel completely

worthless

1 2 3 4 5

14-Too often when things go wrong I

get discouraged and feel like giving up

1 2 3 4 5

Appendix

221

Extraversion

(Costa ampMcCrae 1992)

15-I really enjoy talking to people 1 2 3 4 5

16-I am a cheerful high-spirited person 1 2 3 4 5

17-I am a very active person 1 2 3 4 5

Openness


18-I am intrigued by the patterns I find in

art and nature

1 2 3 4 5

19-I often try new and foreign foods 1 2 3 4 5

20-I have a lot of intellectual curiosity 1 2 3 4 5

21-I often enjoy playing with theories or

abstract ideas

1 2 3 4 5

Agreeableness


22-I often get into arguments with my

family and co-workers

1 2 3 4 5

23-Some people think Im selfish and

egotistical

1 2 3 4 5

24-Some people think of me as cold and

calculating

1 2 3 4 5

Conscientiousness

(CostaampMcCrae1992)

25-I keep my belongings neat and clean 1 2 3 4 5

26-I am pretty good about pacing myself

so as to get things done on time

1 2 3 4 5

27-I waste a lot of time before settling

down to work

1 2 3 4 5

Salience

(Yalcin et al 2016)

28-Expert opinions in written and visual

media should be taken into consideration

when investing

1 2 3 4 5

29-A companyrsquos share which is often in

the media with favorable news coverage

should be preferred when investing

1 2 3 4 5

30-To invest in companies that have a

good brand name is important to me

1 2 3 4 5

31-It is risky to invest in relatively

unknown public companies rather than

known ones

1 2 3 4 5

32-I believe that investors should

purchase the share of the company they

work for if it is well run

1 2 3 4 5

Achievement

(Keller amp Siegrist2006a)

33-I believe that the amount of money

that a person earns is closely related to

hisher ability and effort

1 2 3 4 5

34-Money represents ones achievement 1 2 3 4 5

35-Money is a symbol of success 1 2 3 4 5

36-I believe that a persons salary is very

revealing in assessing their intelligence

1 2 3 4 5

Power


37-Money can give you the opportunity

to be what you want to be

1 2 3 4 5

38-Money gives you autonomy or

freedom

1 2 3 4 5

Samra Chaudary

222

39-Money means power 1 2 3 4 5

40-Money will help you express your

competence and abilities

1 2 3 4 5

41-Money can bring you many friends 1 2 3 4 5

Obsession


42-I firmly believe that money can solve

all of my problems

1 2 3 4 5

43-Money can buy everything 1 2 3 4 5

44-I would do practically anything legal

for money if it were enough

1 2 3 4 5

45-I often fantasize about money and

what I could do with it

1 2 3 4 5

Budget


46-I am proud of my ability to save

money

1 2 3 4 5

47-I feel compelled to argue or bargain

about the cost of almost everything that I

buy

1 2 3 4 5

Indicate your gut level assessment of how risky each situation is on a five-point rating

scale

1 2 3 4 5

Not at all risky Slightly

Risky

Moderately

Risky

Relatively more

Risky

Very Risky

Risk Perception

(Weber et al 2002)

48-Investing 10 of your annual income

in a moderate growth mutual fund

1 2 3 4 5


in a very speculative shares

1 2 3 4 5


in a conservative shares

1 2 3 4 5

1-How long have you been investing in the stock market hellipyears andhellipmonths

2-Whats your role in the management of wealth (check only one option)

1048713 I manage my own wealth only 1048713 I manage peoplersquos wealth

3-Do you expect to receive inheritancetransfer of assets from your family

1048713 Yes 1048713 No

4-What is your amount invested in the stockshares portfolio PKR helliphelliphelliphelliphelliphellip

5-How would you rate your religiosity

1048713 Very liberal 1048713Moderately religious 1048713Very religious

6-What is your age helliphelliphelliphelliphelliphellip years

Appendix

223

7-What is your monthly income PKR helliphelliphelliphelliphelliphellip

8-Please circle the highest number of years of school completed

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23+

9-Gender 1048713 Male 1048713 Female

Thank you for your help

ii

iii

iv



|

by

|

Samra Chaudary

|





|

Abstract |

















v

























vi

Acknowledgments |

|





















this milestone

vii

Table of Contents



11 Introduction 1







21 Introduction 20









231 Measures 41

232 Methods 41

24 Results 46







31 Introduction 66

viii









331 Measures 81

332 Methods 81

34 Results 84








Inheritance 102

Abstract 102

41 Introduction 103








431 Measures 118

432 Methods 119

44 Results 122





ix



52 Key Findings 143




References 154







x

List of Tables














xi

List of Figures





























Introduction

1

1 Introduction

11 Introduction






















Samra Chaudary

2







Shih amp Ke 2014)

















Introduction

3
























Samra Chaudary

4
























Introduction

5
























Samra Chaudary

6
























Introduction

7







below







Samra Chaudary

8
























Introduction

9






paradigm

12 Research Context

















Samra Chaudary

10











Source wwwpsxcompk




Introduction

11




economy


















Chattopadhyay 2013)

Samra Chaudary

12






















Introduction

13























Samra Chaudary

14














Riepe 1998)










Introduction

15
























Samra Chaudary

16
























Introduction

17
























Samra Chaudary

18



















behavioral finance


19



Abstract





















Samra Chaudary

20




21 Introduction





















21
























Samra Chaudary

22
























23
























Samra Chaudary

24
























25




















al 2017 Odean 1998)

Samra Chaudary

26








1991)

















27























Samra Chaudary

28






of risky choices














Hypothesis)





29





















Samra Chaudary

30



Tupesamp

Christal

(1961)



Norman

(1963) Five








Myersamp

McCaulley

(1985)

Four



Hogan

(1982) Six


and Intellectance

CostaampMcCrae

(1985) Five


Conscientiousness

Kampamp Hough

(1986) Seven



Hogan

(1986) Six



Digmanamp Inouye

(1986) Five


Openness

Kampamp Gough

(1986) Five



Goldberg

(1990) Five


Intellect

Hough et al

(1990) Nine




Costaamp

McCrae

(1992)

Five

(Revised

NEO

personality

inventory)


Conscientiousness

Cattell









31

















McCrae 1992)





Samra Chaudary

32








dependability





















33











and moodiness




cultural interest















Samra Chaudary

34


Zaichkowsky 2004)













conscientiousness








investors


35






term investing


investing




long-term investing






term investing


term investing




Samra Chaudary

36

























37


financial market






















Samra Chaudary

38

























39









decisions










decisions





Samra Chaudary

40





Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1a

H2a

H3a

H4a

H5a

H6a

H6b

H6c

H6d

H6e

Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1b

H2b

H3b

H4b

H5b

H6f

H6g

H6h

H6i

H6j


41


231 Measures









232 Methods













Samra Chaudary

42

























43









2322 Data Analyses















Samra Chaudary

44

























45




















Samra Chaudary

46






24 Results

















ST-D 3075 0763 (0681)

LT-D 3279 0810 0551 (0702)

N 2524 0895 0206 0140 (0785)

E 3444 0929 0458 0581 -0020 (0878)

O 3298 0783 0385 0539 0099 0635 (0739)

A 2984 0880 -0229 -0273 -0358 -0199 -0189 (0760)

C 3228 0751 0253 0415 0074 0427 0432 -0345 (0707)

RP 2261 0921 0213 0308 0094 0220 0193 -0238 0169 (0812)


47
























Samra Chaudary

48



Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)


the stock market

0600 8579



0764 17620



0685 14911



0665 11816

Long-term

Investment

Decision

(Mayfield

et al

2008)



0750 23657



0716 17223




0663 14376



0659 13952


McCrae

1992)




0864 26438




feel like giving up

0770 13300


McCrae

1992)




Openness (Costa amp

McCrae

1992)






McCrae

1992)


workers

0722 10789



Conscientious

ness

(Costa amp

McCrae

1992)



done on time

0855 22739


Risk

Perception

(Weber et

al 2002)


growth mutual fund

0812 20781


stock

0888 31293


stock

0729 12008


reverse coded items


49



(CR)






Openness 0827 0546





Factors A C E LT-D

N O RP

ST-D

A

C 0634

E 0281 0706

LT-D 04 0711 0752

N 049 0352 0093 0214

O 0282 0747 0837 074 0133

RP 0343 0281 0267 0401 0127 0253

ST-D 0392 0485 065 0809 0283 0573 0303












Samra Chaudary

50

























51











of the sample size









Samra Chaudary

52



Estimates

p

value f2 R2 Q2

Statistical

Power

H1a N-gtST-D 0200 0002 0062

0352 0127 1

H2a E-gtST-D 0405 0000 0129

H3a O-gtST-D 0084 0318 0010

H4a A-gtST-D -0060 0314 0011

H5a C-gtST-D 0027 0829 0005

H1b N-gtLT-D 0073 0110 0017

0493 0209 1

H2b E-gtLT-D 0537 0000 0102

H3b O-gtLT-D 0515 0000 0069

H4b A-gtLT-D -0084 0119 0017

H5b C-gtLT-D 0373 0003 0021














2010)




53




amp Kenny 1986)




















Samra Chaudary

54









decision
















55










Direct Effect

Indirect Effect

Decision Rule

Independent

Variables

Mediator Dependent

Variables

β

p β

p

H6a Neuroticism

Risk

Perception ST-D

0202 0002 -0002 0817 Direct-only

Non-Mediation

H6b Extraversion

0392 0000 0013 0309 Direct-only

Non-Mediation

H6c Openness

0075 0331 0009 0453

No effect

Non-Mediation

H6d Agreeableness

-0040 0606 -0020 0116 No effect

Non-Mediation


0025 0708 0002 0849 No effect

Non-Mediation

H6f Neuroticism

Risk

Perception LT-D

0076 0140 -0003 0802 No effect

Non-Mediation

H6g Extraversion

0493 0000 0044 0005 Complimentary

Mediation

H6h Openness

0472 0000 0043 0006 Complimentary

Mediation

H6i Agreeableness

-0056 0276 0028 0034 Indirect-only

Mediation


0333 0000 0040 0030 Complimentary

Mediation







Samra Chaudary

56
























57




















investments




Samra Chaudary

58

























59
























Samra Chaudary

60

























61






















(Baker et al 2017)

Samra Chaudary

62

























63
























Samra Chaudary

64










65




Abstract





















Samra Chaudary

66








31 Introduction

















67
























Samra Chaudary

68



















321 Prospect Theory






69
























Samra Chaudary

70

























71
























Samra Chaudary

72






securities


















73












investor protection












Samra Chaudary

74

























75



















Soufian 2015)





Samra Chaudary

76

























77
























Samra Chaudary

78

























79
























Samra Chaudary

80



















81


331 Measures






332 Methods
















Samra Chaudary

82

















10 million

3322 Data Analyses







83
























Samra Chaudary

84








Deviation

Short-term

Investment

Decision

Long-term

Investment

Decision

Salience

Short-term

Investment

Decision

3113 0779 (0742)

Long-term

Investment

Decision

3311 0846 0518 (0728)

Salience 3039 0827 0359 0515 (0728)



34 Results












85





















Samra Chaudary

86



Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)







Long-term

Investment

Decision

(Mayfield

et al

2008)





etc)

0713 15358




Salience (Yalcin et

al 2016)





when investing

0668 15584










(CR)




Salience 0849 0531



Decision


Salience 0691



87
























Samra Chaudary

88





















Statistical

Power

H1 Salience -gt ST-D 03295 0000 0150 0224 0091 0999

H2 Salience -gt LT-D 05017 0000 0363 0340 0146 1000







p=0736)


89
























Samra Chaudary

90
























91


Investors


interval

Permutation

p-value

Compositional

invariance

ST-D 0965 [0941 1000] 0254 Yes

LT-D 0985 [0968 1000] 0097 Yes

Salience 0992 [0980 1000] 0235 Yes




95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -0287 [-0237 0243] 0022 No

LT-D -0119 [-0247 0233] 0327 Yes

Salience -0077 [-0244 0217] 0534 Yes




95 confidence

interval

Permutation

p-value

Equal variances

ST-D -0006 [-0350 0308] 0796 Yes

LT-D -0166 [-0305 0263] 0249 Yes

Salience -0099 [-0292 0302] 0494 Yes





interval

Permutation

p-value

Compositional

invariance

ST-D 0946 [0826 1000] 0017 No

LT-D 0986 [0961 1000] 0934 Yes

Salience 0989 [0970 1000] 0235 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -00006 [-0300 0313] 0693 Yes

LT-D -00007 [-0296 0296] 0100 Yes

Salience -00009 [-0308 0300] 0186 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal variances

ST-D 0025 [-0357 0443] 0330 Yes

LT-D 0030 [-0337 0419] 0402 Yes

Salience 0019 [-0341 0387] 0699 Yes



Samra Chaudary

92

























93





Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0236 0000 2519 0097 0078 0477 0000 7502 0337 0242

Salience -gt

LT-D 0454 0000 8148 0315 0229 0609 0012 1065 0655 0384





Path

coefficient

diff

Individual

-

Professional

p-value

Individual

vs

Professional

t-value

Individual

vs

Professional

f2 diff

Individual

-

Professional

R2 diff

Individual

- Professional

H3 Salience -gt

ST-D 0241 0023 2291 0235 0175

H4 Salience -gt

LT-D 0155 0048 1986 033 0168










Samra Chaudary

94










(Females) (Males)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0642 0000 8032 0775 0419 0316 0000 4496 0120 0104

Salience -gt

LT-D 0692 0000 1051 0992 0483 0516 0000 1086 0374 0269





Path

coefficient

diff

Female

-

Male

p-value

Female

vs

Male

t-value

Female

vs

Male

f2 diff

Female

-

Male

R2 diff

Female

-

Male

H3 Salience -gt

ST-D 0326 0001 3222 0655 0315

H4 Salience -gt

LT-D 0176 0024 2013 0618 0214





95
























Samra Chaudary

96

























97
























Samra Chaudary

98

























99
























Samra Chaudary

100













returns










investors


101





















Samra Chaudary

102



Abstract


















decisions




103

41 Introduction























Samra Chaudary

104

























105
























Samra Chaudary

106























developing economy


107


421 Prospect Theory



















1984)



Samra Chaudary

108

























109


economy






















Samra Chaudary

110




















et al 2018b 2018c)





111



amp Templer (1982)





















Samra Chaudary

112
























113
























Samra Chaudary

114






ones



















115
























Samra Chaudary

116
























117

















decisions


decisions





Samra Chaudary

118





431 Measures











Achievement

Power

Obsession

Budget


Love of Money



Inheritance

H1

H2

H3 H4H5 H6


119




432 Methods




















Samra Chaudary

120























in an economy


121

4322 Data Analyses























Samra Chaudary

122













Deviation


ST-D 3074 0836 (0742)

LT-D 3292 0856 0490 (0735)

Achievement 2893 0934 0297 0244 (0808)

Power 2928 0967 0268 0327 0645 (0821)

Obsession 2659 0898 0240 0209 0582 0610 (0744)


44 Results








123
























Samra Chaudary

124























and 45


125



Factor Loadings

Boot

sample

t-Values

Short-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



8112





Long-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



purposes

0798 23438



real estate etc)

0715 12630





0630 8323

Love of

Money

(second order-

formative

construct)

(Kelleramp

Siegrist

2006a)

Achievement




ability and effort

0690 17818





Power









Obsession









Budget






Samra Chaudary

126



Formative

Components of

Construct LoM

t-values of

Weights

Variance

Inflation Factor

(VIF)


Power 0458 26660 2155

Obsession 0290 14361 2029

Budget 0095 5767 1121



(CR)


(AVE)




Power 0912 0675

Obsession 0837 0555

Budget 0730 0595



Investment

Decision


Investment

Decision

Achievement

Budget 04662

Long-Term

Investment

Decision

03553 07748

Obsession 07911 04764 03102

Power 07591 03561 0432 08125

Short-Term

Investment

Decision

04514 03446 07436 04071 04057






127
























Samra Chaudary

128














p

value


Power


Short-term

investment decision

0341 0000 0160 0134 0058 0999


Long-term

investment decision

0328 0000 0154 0138 0059 0999



0002 p=0953)








129























Samra Chaudary

130

























131



















value

R2

without

moderator

R2

with

moderator

R2Δ Power

Result



Moderation


D

0373 0024 0134 0165 0031 0999 Moderation


D

0318 0044 0138 0201 0063 0999 Moderation


Money


Samra Chaudary

132




(ie low-income)






133





1

15

2

25

3

35

4

45

5

Low LoM High LoM

Short

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Long

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

Samra Chaudary

134

























135
























Samra Chaudary

136

























137










investments









effectively





Samra Chaudary

138

























139







Kim 2017)

















Samra Chaudary

140












future inheritance













141









Samra Chaudary

142

5 Conclusion

51 Introduction



















decisions



Conclusion

143















52 Key Findings









Samra Chaudary

144





















decisions



Conclusion

145
























Samra Chaudary

146


inheritance






















Conclusion

147











LT-D are













Samra Chaudary

148







collection
















Conclusion

149























Samra Chaudary

150























Conclusion

151
























Samra Chaudary

152











differently













Conclusion

153














Samra Chaudary

154






Economics 62(2) 313-336






Springer




58





References

155















423








Samra Chaudary

156


Reports 73(1) 3-11




95

















References

157



784
















Planning 45(5-6) 359-394





Samra Chaudary

158










179-207









59-72




References

159























Samra Chaudary

160

















Ability Testing






References

161






Finance 60(3) 1495-1534

















Samra Chaudary

162


284









NJ Erlbaum



Lawrence Earlbaum









60

References

163















42(3-5) 831-844


Finance 40(3) 793-805


York NY



Samra Chaudary

164











34(5) 1032-1046











References

165



126-134
















Methods 14(2) 370-388





Samra Chaudary

166




212







590



25(2) 195-211




Press





References

167














210



452



18(1) 39ndash50



Samra Chaudary

168
























References

169














of Finance 11(2) 325-357










Samra Chaudary

170










December














References

171




Calif Sheridan









Publications











Samra Chaudary

172



Research 91 159-168



170


















References

173






431









91- 103




1533-1597



Economics 70 74-89

Samra Chaudary

174




















126(1) 45


24(6) 852-859


References

175






659ndash680
















Sciences 11(3) 265-278

Samra Chaudary

176






















2(1999) 102-138

References

177



105-114





















Samra Chaudary

178



1325-1348



Washington DC




literature 88-02





317-333









References

179


353-358















ISSN 1454-9409






publications

Samra Chaudary

180














Research 59(4) 288-294



400






References

181





108



















Samra Chaudary

182










301-315






124




388 New York Wiley



References

183















Springer Singapore



Macmillan




Quarterly 10ndash21

Samra Chaudary

184












McGraw-Hill Irwin



145








References

185




IrwinMcGraw-Hill






280-307







Consumers 15(2) 111-124







Samra Chaudary

186











York McGraw-Hill











References

187















53(5) 1775-1798


1279-1299







Samra Chaudary

188











Review 37(2-3) 613-622













References

189

4643ndash4648



4(2) 71-84

















Economica 31(3) 377-420

Samra Chaudary

190









54



826-845











References

191







26(5) 34-35














75(9) 888-895



Samra Chaudary

192



12(5) e0178283







Finance 14 (2) 94-103












93ndash115

References

193







ed London Pearson









Finance 65(5) 1987-2010







24

Samra Chaudary

194








199-228



7207













References

195








445









53(5) 1589-1622






Samra Chaudary

196




York Modern Library




















References

197













19(6) 809ndash817











Samra Chaudary

198
























References

199







105465AMBPP201165869480





148(4) 919-937












Samra Chaudary

200








94-117












12(3) 183-206




References

201





















59 (4) 251-278



Samra Chaudary

202




Science 185(4157) 1124-1131

















369-379



References

203











Finance 12(1) 9-19













Samra Chaudary

204







making 15(4) 263-290




25(3) 597-609




Finance 54(2) 581-622








References

205







11(2) 270-295



179












and Trade 48(3) 23-34

Samra Chaudary

206













206



Appendix

207

Appendices


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Personality and

Decision-making

Heinstrom 2003

Nicholson et al

2005 Zhao amp

Seibert 2006

Mayfield et al

2008 Lim at al

2013 Oehler amp

Wedlich 2018

Oehler et al 2018

Heinstrom 2003

Van Witteloostuijin

amp Muehlfeld 2008

Durand et al 2008

Weber amp Milliman

1997 Keller amp

Siegrist 2006ab

Bateman et al

2010 Weber et al

2013 Hoffman et

al 2015 Duxbury

et al 2005 Weber

et al 2002

Hopfensitz amp

Wranik 2009

Borghans et al

2009

Verma 2008 Riaz

amp Hunjra 2016

Tauni et al

20152016 Yang et

al 2012 Wang et


Investment

Decisions

Oehler et al 2018

Mayfield et al

2008 Oehler amp

Wedlich 2018

Hershey amp Mowen

2000 Hunter amp

Kemp 2004 van

Witteloostuijin amp

Muehlfeld 2008

Durand et al 2008

2013 Tauni et al

2015 2016 Yang

et al 2012

Brandstatter 2011

Hopfensitz amp

Wranik 2009

Personality Short-

term and Long-

term Investment

Decisions

Mayfield et al

2008

Personality and

Risk Taking

Behavior

Nicholson et al

2005 Zhao amp

Seibert 2006

Weber et al 2002

Filbeck et al 2005

Mayfield et al

2008 Brandstatter

2011 Hopfensitz amp

Wranik 2009

Borghans et al

2009

Risk Taking and

Decision-making

Riaz amp Hunjra

2016

MacCrimmon amp

Wehrung 1990

Samra Chaudary

208

Weber amp Milliman

1997 Keller amp

Siegrist 2006a b

Nosic amp Weber

2010 Bateman et

al 2010 Weber et

al 2013 Hoffman

et al 2015 Lim at

al 2013 Duxbury

et al 2005 Weber

et al 2002 Wang

et al 2006

Loewenstein et al

2001 Weber amp

Johnson 2008

Big-Five

Personality Short-

term and Long-

term Investment

Decisions

This Study

Big-Five

Personality Risk

Perception Short-

term and Long-

term Investment

Decisions

This Study

Appendix

209


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Heuristics and

Decision-making

Tversky amp

Kahneman 1974

Kahneman amp

Tversky 1979

Tversky amp

Kahneman 1981

De Bondt 1998 De

Bondt amp Thaler

1985 Shefrin amp

Statman 1985

Tversky amp

Kahneman 1992

Lakonishok et al

1994 Fox amp

Tversky 1995

Kahneman amp

Riepe 1998

Odean 1998 1999

Thaler 1999 Jain

amp Wu 2000

Hirshleifer 2001

Huberman 2001

Barber et al 2005

Grinblatt amp Han

2005 Nofsinger

2005 Mishra

2014 Yalcin et al

2016 Ahearne et

al 2004 Wang et

al 2011 Lewis

1999 Barberis amp

Xiong 2009

Wermers 1999

Barber amp Odean

2001 Statman et

al 2006 Epley amp

Gilovich 2005

Furnham amp Boo

2011 Glaser et al

2007 Thaler amp

Sunstein 2008

Kahneman amp

Tversky 1979 De

Bondt amp Thaler

1985 Fox amp

Tversky 1995

Tversky amp

Kahneman 1992

De Bondt 1998

Jain amp Wu 2000

Wang et al 2011

Grinblatt amp

Keloharju 2001

Lakonishok et al

1994 Coval amp

Moskowitz 1999

Chan et al 2005

Ahearne et al

2004 Olsen 1997

Borges et al 1999

Barber amp Odean

2001 Kang amp

Stulz 1997 Odean

1998 1999 Lewis

1999 Wermers

1999 Epley amp

Gilovich 2005

Huberman 2001

Barber et al 2005

Statman et al

2006 Glaser et al

2007 Wang et al

2011 Tversky amp

Kahneman 1981

Riff amp Yagil 2016

Yalcin et al 2016

Jaiyeoba amp Haron

2016 De Vries et

al 2017 Chan et

al 2005 Olsen

1997 Metawa et

al 2019

Samra Chaudary

210

Salience and

Investment

Decisions

Yalcin et al 2016

Huberman 2001

Tverskyamp

Kahneman 1973

Merton 1987

Heath amp Tversky

1991 Fox amp

Tversky 1995

Sirri amp Tufano

1998 Jain amp Wu

2000 Barber et al

2005 Nofsinger

2005Wang et al

2011 Grinblatt amp

Keloharju 2001

Jaiyeoba amp Haron

2016 Antoniou et

al 2010 Baker amp

Ricciardi 2014

Chan et al 2005

Riff amp Yagil 2016

Sizemore 2012

Giannetti amp

Koskinen 2010

Kumar amp

Goetzmann 2003

De Vries et al

2017 Chan et al

2005 Weber et al

2005

Institutional

Investors and

Salience

Coval amp

Moskowitz 1999

Strong amp Xu 2003

Chan et al 2005

Olsen 1997

Borges et al 1999

Goldstein amp

Gigerenzer 2002

Forbes et al 2015

Individual

Investors and

Salience

Baxter 1994

French amp Poterba

1991

Baker et al 2017

De Vries et al

2017 Tesar amp

Werner 1995

Appendix

211

Ahearne et al

2004 Kang amp

Stulz 1997

Seasholes amp Zhu

2010 Karlsson amp

Norden 2007

Cooper amp Kaplanis

1994

Gender and

Salience

Anderson et al

2011 Alrabadi et

al 2018 Ang et

al 2014 Cao et al

2009 Feng amp

Seasholes 2008

Karlsson amp Norden

2007

Mohammadi amp

Shafi 2018

Prast et al 2015

Seiler et al 2008

Seiler et al 2013

Tekce et al 2016

Wang et al 2011

Anderson et al

2011 Karlsson amp

Norden 2007

Mohammadi amp

Shafi 2018 Prast et

al 2015

Seiler et al 2008

Seiler et al 2013

Wang et al 2011

Alrabadi et al

2018 Feng amp

Seasholes 2008

Tekce et al 2016

Salience Short-

term and Long-

term Investment

Decisions

This Study

Salience

Institutional

Investors

Individual

Investors Gender

Short-term and

Long-term

Investment

Decisions

This Study

Samra Chaudary

212


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Attitudes and

Decision-making

Mahastanti amp

Hariady 2013

Akhtar amp Das

2019

Lim amp Teo 1997

Keller amp Siegrist

2006a Tang et al

2006 Vitell et al

2007 Tang et al

2008 Tang amp

Chen 2008 Klontz

amp Britt 2012

Gentina et al 2018

Hampson et al

2018 Tang amp Chiu

2003 Medina et al

1996 Yamauchi amp

Templer 1982

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Tang et al

2006 Li et al

2009 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011 Jia

et al 2013

Sardzoska ampTang

2012 Mahastanti amp

Hariady 2013 Shih

amp Ke 2014 Tang

et al 2018a

Akhtar amp Das 2019

Money Attitudes

and Decision-

making

Tang amp Chiu 2003

Vitell et al 2007

Tang et al

2008ab Tang amp

Chen 2008 Li et

al 2009 Klontz amp

Britt 2012 Shih amp

Ke 2014 Tang

2016 Britt 2016

Tang et al 2018a

Greenberg amp

Hershfield 2019

Money Attitudes

and Investment

Decisions

Keller amp Siegrist

2006a Jia et al

2013 Shih amp Ke

2014 Tang et al

2018a

Demographics and

Money Attitudes

Lim amp Teo 1997

Tang amp Chiu 2003

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011

Hampson et al

2018 Gentina et al

2018 Yamauchi amp

Templer 1982

Medina et al 1996

Tang amp Chiu 2003

Tang et al 2006

Tang et al

2008ab Sardzoska

ampTang 2012

Demographics and

Investment

Decision

Warneryd 2001

Haisley et al 2008

Greenberg amp

Appendix

213

Hershfield 2019

Cicchetti amp Dubin

1994 Grable et al

2004 Hlouskova et

al 2017

Greenberg 2013

Embrey and Fox

1997

Money Attitudes

Short-term and

Long-term

Investment

Decisions

This Study

Money Attitudes

Income

Inheritance Short-

term and Long-

term Investment

Decisions

This Study

Samra Chaudary

214
























Appendix

215






Samra Chaudary

216





Appendix

217





Samra Chaudary

218





Appendix

219





Samra Chaudary

220






1 2 3 4 5



Decision




1 2 3 4 5



week

1 2 3 4 5



1 2 3 4 5



managers

1 2 3 4 5


Decision




retirement purposes

1 2 3 4 5




1 2 3 4 5




and cost efficiency

1 2 3 4 5




1 2 3 4 5

Neuroticism





1 2 3 4 5



worthless

1 2 3 4 5



1 2 3 4 5

Appendix

221

Extraversion





Openness



art and nature

1 2 3 4 5




abstract ideas

1 2 3 4 5

Agreeableness




1 2 3 4 5


egotistical

1 2 3 4 5


calculating

1 2 3 4 5

Conscientiousness





1 2 3 4 5


down to work

1 2 3 4 5

Salience

(Yalcin et al 2016)



when investing

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5



known ones

1 2 3 4 5




1 2 3 4 5

Achievement





1 2 3 4 5





1 2 3 4 5

Power




1 2 3 4 5


freedom

1 2 3 4 5

Samra Chaudary

222




1 2 3 4 5


Obsession



all of my problems

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5

Budget



money

1 2 3 4 5



buy

1 2 3 4 5


scale

1 2 3 4 5


Risky

Moderately

Risky

Relatively more

Risky

Very Risky

Risk Perception

(Weber et al 2002)



1 2 3 4 5



1 2 3 4 5



1 2 3 4 5





1048713 Yes 1048713 No





Appendix

223



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23+



iii

iv



|

by

|

Samra Chaudary

|





|

Abstract |

















v

























vi

Acknowledgments |

|





















this milestone

vii

Table of Contents



11 Introduction 1







21 Introduction 20









231 Measures 41

232 Methods 41

24 Results 46







31 Introduction 66

viii









331 Measures 81

332 Methods 81

34 Results 84








Inheritance 102

Abstract 102

41 Introduction 103








431 Measures 118

432 Methods 119

44 Results 122





ix



52 Key Findings 143




References 154







x

List of Tables














xi

List of Figures





























Introduction

1

1 Introduction

11 Introduction






















Samra Chaudary

2







Shih amp Ke 2014)

















Introduction

3
























Samra Chaudary

4
























Introduction

5
























Samra Chaudary

6
























Introduction

7







below







Samra Chaudary

8
























Introduction

9






paradigm

12 Research Context

















Samra Chaudary

10











Source wwwpsxcompk




Introduction

11




economy


















Chattopadhyay 2013)

Samra Chaudary

12






















Introduction

13























Samra Chaudary

14














Riepe 1998)










Introduction

15
























Samra Chaudary

16
























Introduction

17
























Samra Chaudary

18



















behavioral finance


19



Abstract





















Samra Chaudary

20




21 Introduction





















21
























Samra Chaudary

22
























23
























Samra Chaudary

24
























25




















al 2017 Odean 1998)

Samra Chaudary

26








1991)

















27























Samra Chaudary

28






of risky choices














Hypothesis)





29





















Samra Chaudary

30



Tupesamp

Christal

(1961)



Norman

(1963) Five








Myersamp

McCaulley

(1985)

Four



Hogan

(1982) Six


and Intellectance

CostaampMcCrae

(1985) Five


Conscientiousness

Kampamp Hough

(1986) Seven



Hogan

(1986) Six



Digmanamp Inouye

(1986) Five


Openness

Kampamp Gough

(1986) Five



Goldberg

(1990) Five


Intellect

Hough et al

(1990) Nine




Costaamp

McCrae

(1992)

Five

(Revised

NEO

personality

inventory)


Conscientiousness

Cattell









31

















McCrae 1992)





Samra Chaudary

32








dependability





















33











and moodiness




cultural interest















Samra Chaudary

34


Zaichkowsky 2004)













conscientiousness








investors


35






term investing


investing




long-term investing






term investing


term investing




Samra Chaudary

36

























37


financial market






















Samra Chaudary

38

























39









decisions










decisions





Samra Chaudary

40





Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1a

H2a

H3a

H4a

H5a

H6a

H6b

H6c

H6d

H6e

Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1b

H2b

H3b

H4b

H5b

H6f

H6g

H6h

H6i

H6j


41


231 Measures









232 Methods













Samra Chaudary

42

























43









2322 Data Analyses















Samra Chaudary

44

























45




















Samra Chaudary

46






24 Results

















ST-D 3075 0763 (0681)

LT-D 3279 0810 0551 (0702)

N 2524 0895 0206 0140 (0785)

E 3444 0929 0458 0581 -0020 (0878)

O 3298 0783 0385 0539 0099 0635 (0739)

A 2984 0880 -0229 -0273 -0358 -0199 -0189 (0760)

C 3228 0751 0253 0415 0074 0427 0432 -0345 (0707)

RP 2261 0921 0213 0308 0094 0220 0193 -0238 0169 (0812)


47
























Samra Chaudary

48



Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)


the stock market

0600 8579



0764 17620



0685 14911



0665 11816

Long-term

Investment

Decision

(Mayfield

et al

2008)



0750 23657



0716 17223




0663 14376



0659 13952


McCrae

1992)




0864 26438




feel like giving up

0770 13300


McCrae

1992)




Openness (Costa amp

McCrae

1992)






McCrae

1992)


workers

0722 10789



Conscientious

ness

(Costa amp

McCrae

1992)



done on time

0855 22739


Risk

Perception

(Weber et

al 2002)


growth mutual fund

0812 20781


stock

0888 31293


stock

0729 12008


reverse coded items


49



(CR)






Openness 0827 0546





Factors A C E LT-D

N O RP

ST-D

A

C 0634

E 0281 0706

LT-D 04 0711 0752

N 049 0352 0093 0214

O 0282 0747 0837 074 0133

RP 0343 0281 0267 0401 0127 0253

ST-D 0392 0485 065 0809 0283 0573 0303












Samra Chaudary

50

























51











of the sample size









Samra Chaudary

52



Estimates

p

value f2 R2 Q2

Statistical

Power

H1a N-gtST-D 0200 0002 0062

0352 0127 1

H2a E-gtST-D 0405 0000 0129

H3a O-gtST-D 0084 0318 0010

H4a A-gtST-D -0060 0314 0011

H5a C-gtST-D 0027 0829 0005

H1b N-gtLT-D 0073 0110 0017

0493 0209 1

H2b E-gtLT-D 0537 0000 0102

H3b O-gtLT-D 0515 0000 0069

H4b A-gtLT-D -0084 0119 0017

H5b C-gtLT-D 0373 0003 0021














2010)




53




amp Kenny 1986)




















Samra Chaudary

54









decision
















55










Direct Effect

Indirect Effect

Decision Rule

Independent

Variables

Mediator Dependent

Variables

β

p β

p

H6a Neuroticism

Risk

Perception ST-D

0202 0002 -0002 0817 Direct-only

Non-Mediation

H6b Extraversion

0392 0000 0013 0309 Direct-only

Non-Mediation

H6c Openness

0075 0331 0009 0453

No effect

Non-Mediation

H6d Agreeableness

-0040 0606 -0020 0116 No effect

Non-Mediation


0025 0708 0002 0849 No effect

Non-Mediation

H6f Neuroticism

Risk

Perception LT-D

0076 0140 -0003 0802 No effect

Non-Mediation

H6g Extraversion

0493 0000 0044 0005 Complimentary

Mediation

H6h Openness

0472 0000 0043 0006 Complimentary

Mediation

H6i Agreeableness

-0056 0276 0028 0034 Indirect-only

Mediation


0333 0000 0040 0030 Complimentary

Mediation







Samra Chaudary

56
























57




















investments




Samra Chaudary

58

























59
























Samra Chaudary

60

























61






















(Baker et al 2017)

Samra Chaudary

62

























63
























Samra Chaudary

64










65




Abstract





















Samra Chaudary

66








31 Introduction

















67
























Samra Chaudary

68



















321 Prospect Theory






69
























Samra Chaudary

70

























71
























Samra Chaudary

72






securities


















73












investor protection












Samra Chaudary

74

























75



















Soufian 2015)





Samra Chaudary

76

























77
























Samra Chaudary

78

























79
























Samra Chaudary

80



















81


331 Measures






332 Methods
















Samra Chaudary

82

















10 million

3322 Data Analyses







83
























Samra Chaudary

84








Deviation

Short-term

Investment

Decision

Long-term

Investment

Decision

Salience

Short-term

Investment

Decision

3113 0779 (0742)

Long-term

Investment

Decision

3311 0846 0518 (0728)

Salience 3039 0827 0359 0515 (0728)



34 Results












85





















Samra Chaudary

86



Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)







Long-term

Investment

Decision

(Mayfield

et al

2008)





etc)

0713 15358




Salience (Yalcin et

al 2016)





when investing

0668 15584










(CR)




Salience 0849 0531



Decision


Salience 0691



87
























Samra Chaudary

88





















Statistical

Power

H1 Salience -gt ST-D 03295 0000 0150 0224 0091 0999

H2 Salience -gt LT-D 05017 0000 0363 0340 0146 1000







p=0736)


89
























Samra Chaudary

90
























91


Investors


interval

Permutation

p-value

Compositional

invariance

ST-D 0965 [0941 1000] 0254 Yes

LT-D 0985 [0968 1000] 0097 Yes

Salience 0992 [0980 1000] 0235 Yes




95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -0287 [-0237 0243] 0022 No

LT-D -0119 [-0247 0233] 0327 Yes

Salience -0077 [-0244 0217] 0534 Yes




95 confidence

interval

Permutation

p-value

Equal variances

ST-D -0006 [-0350 0308] 0796 Yes

LT-D -0166 [-0305 0263] 0249 Yes

Salience -0099 [-0292 0302] 0494 Yes





interval

Permutation

p-value

Compositional

invariance

ST-D 0946 [0826 1000] 0017 No

LT-D 0986 [0961 1000] 0934 Yes

Salience 0989 [0970 1000] 0235 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -00006 [-0300 0313] 0693 Yes

LT-D -00007 [-0296 0296] 0100 Yes

Salience -00009 [-0308 0300] 0186 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal variances

ST-D 0025 [-0357 0443] 0330 Yes

LT-D 0030 [-0337 0419] 0402 Yes

Salience 0019 [-0341 0387] 0699 Yes



Samra Chaudary

92

























93





Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0236 0000 2519 0097 0078 0477 0000 7502 0337 0242

Salience -gt

LT-D 0454 0000 8148 0315 0229 0609 0012 1065 0655 0384





Path

coefficient

diff

Individual

-

Professional

p-value

Individual

vs

Professional

t-value

Individual

vs

Professional

f2 diff

Individual

-

Professional

R2 diff

Individual

- Professional

H3 Salience -gt

ST-D 0241 0023 2291 0235 0175

H4 Salience -gt

LT-D 0155 0048 1986 033 0168










Samra Chaudary

94










(Females) (Males)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0642 0000 8032 0775 0419 0316 0000 4496 0120 0104

Salience -gt

LT-D 0692 0000 1051 0992 0483 0516 0000 1086 0374 0269





Path

coefficient

diff

Female

-

Male

p-value

Female

vs

Male

t-value

Female

vs

Male

f2 diff

Female

-

Male

R2 diff

Female

-

Male

H3 Salience -gt

ST-D 0326 0001 3222 0655 0315

H4 Salience -gt

LT-D 0176 0024 2013 0618 0214





95
























Samra Chaudary

96

























97
























Samra Chaudary

98

























99
























Samra Chaudary

100













returns










investors


101





















Samra Chaudary

102



Abstract


















decisions




103

41 Introduction























Samra Chaudary

104

























105
























Samra Chaudary

106























developing economy


107


421 Prospect Theory



















1984)



Samra Chaudary

108

























109


economy






















Samra Chaudary

110




















et al 2018b 2018c)





111



amp Templer (1982)





















Samra Chaudary

112
























113
























Samra Chaudary

114






ones



















115
























Samra Chaudary

116
























117

















decisions


decisions





Samra Chaudary

118





431 Measures











Achievement

Power

Obsession

Budget


Love of Money



Inheritance

H1

H2

H3 H4H5 H6


119




432 Methods




















Samra Chaudary

120























in an economy


121

4322 Data Analyses























Samra Chaudary

122













Deviation


ST-D 3074 0836 (0742)

LT-D 3292 0856 0490 (0735)

Achievement 2893 0934 0297 0244 (0808)

Power 2928 0967 0268 0327 0645 (0821)

Obsession 2659 0898 0240 0209 0582 0610 (0744)


44 Results








123
























Samra Chaudary

124























and 45


125



Factor Loadings

Boot

sample

t-Values

Short-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



8112





Long-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



purposes

0798 23438



real estate etc)

0715 12630





0630 8323

Love of

Money

(second order-

formative

construct)

(Kelleramp

Siegrist

2006a)

Achievement




ability and effort

0690 17818





Power









Obsession









Budget






Samra Chaudary

126



Formative

Components of

Construct LoM

t-values of

Weights

Variance

Inflation Factor

(VIF)


Power 0458 26660 2155

Obsession 0290 14361 2029

Budget 0095 5767 1121



(CR)


(AVE)




Power 0912 0675

Obsession 0837 0555

Budget 0730 0595



Investment

Decision


Investment

Decision

Achievement

Budget 04662

Long-Term

Investment

Decision

03553 07748

Obsession 07911 04764 03102

Power 07591 03561 0432 08125

Short-Term

Investment

Decision

04514 03446 07436 04071 04057






127
























Samra Chaudary

128














p

value


Power


Short-term

investment decision

0341 0000 0160 0134 0058 0999


Long-term

investment decision

0328 0000 0154 0138 0059 0999



0002 p=0953)








129























Samra Chaudary

130

























131



















value

R2

without

moderator

R2

with

moderator

R2Δ Power

Result



Moderation


D

0373 0024 0134 0165 0031 0999 Moderation


D

0318 0044 0138 0201 0063 0999 Moderation


Money


Samra Chaudary

132




(ie low-income)






133





1

15

2

25

3

35

4

45

5

Low LoM High LoM

Short

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Long

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

Samra Chaudary

134

























135
























Samra Chaudary

136

























137










investments









effectively





Samra Chaudary

138

























139







Kim 2017)

















Samra Chaudary

140












future inheritance













141









Samra Chaudary

142

5 Conclusion

51 Introduction



















decisions



Conclusion

143















52 Key Findings









Samra Chaudary

144





















decisions



Conclusion

145
























Samra Chaudary

146


inheritance






















Conclusion

147











LT-D are













Samra Chaudary

148







collection
















Conclusion

149























Samra Chaudary

150























Conclusion

151
























Samra Chaudary

152











differently













Conclusion

153














Samra Chaudary

154






Economics 62(2) 313-336






Springer




58





References

155















423








Samra Chaudary

156


Reports 73(1) 3-11




95

















References

157



784
















Planning 45(5-6) 359-394





Samra Chaudary

158










179-207









59-72




References

159























Samra Chaudary

160

















Ability Testing






References

161






Finance 60(3) 1495-1534

















Samra Chaudary

162


284









NJ Erlbaum



Lawrence Earlbaum









60

References

163















42(3-5) 831-844


Finance 40(3) 793-805


York NY



Samra Chaudary

164











34(5) 1032-1046











References

165



126-134
















Methods 14(2) 370-388





Samra Chaudary

166




212







590



25(2) 195-211




Press





References

167














210



452



18(1) 39ndash50



Samra Chaudary

168
























References

169














of Finance 11(2) 325-357










Samra Chaudary

170










December














References

171




Calif Sheridan









Publications











Samra Chaudary

172



Research 91 159-168



170


















References

173






431









91- 103




1533-1597



Economics 70 74-89

Samra Chaudary

174




















126(1) 45


24(6) 852-859


References

175






659ndash680
















Sciences 11(3) 265-278

Samra Chaudary

176






















2(1999) 102-138

References

177



105-114





















Samra Chaudary

178



1325-1348



Washington DC




literature 88-02





317-333









References

179


353-358















ISSN 1454-9409






publications

Samra Chaudary

180














Research 59(4) 288-294



400






References

181





108



















Samra Chaudary

182










301-315






124




388 New York Wiley



References

183















Springer Singapore



Macmillan




Quarterly 10ndash21

Samra Chaudary

184












McGraw-Hill Irwin



145








References

185




IrwinMcGraw-Hill






280-307







Consumers 15(2) 111-124







Samra Chaudary

186











York McGraw-Hill











References

187















53(5) 1775-1798


1279-1299







Samra Chaudary

188











Review 37(2-3) 613-622













References

189

4643ndash4648



4(2) 71-84

















Economica 31(3) 377-420

Samra Chaudary

190









54



826-845











References

191







26(5) 34-35














75(9) 888-895



Samra Chaudary

192



12(5) e0178283







Finance 14 (2) 94-103












93ndash115

References

193







ed London Pearson









Finance 65(5) 1987-2010







24

Samra Chaudary

194








199-228



7207













References

195








445









53(5) 1589-1622






Samra Chaudary

196




York Modern Library




















References

197













19(6) 809ndash817











Samra Chaudary

198
























References

199







105465AMBPP201165869480





148(4) 919-937












Samra Chaudary

200








94-117












12(3) 183-206




References

201





















59 (4) 251-278



Samra Chaudary

202




Science 185(4157) 1124-1131

















369-379



References

203











Finance 12(1) 9-19













Samra Chaudary

204







making 15(4) 263-290




25(3) 597-609




Finance 54(2) 581-622








References

205







11(2) 270-295



179












and Trade 48(3) 23-34

Samra Chaudary

206













206



Appendix

207

Appendices


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Personality and

Decision-making

Heinstrom 2003

Nicholson et al

2005 Zhao amp

Seibert 2006

Mayfield et al

2008 Lim at al

2013 Oehler amp

Wedlich 2018

Oehler et al 2018

Heinstrom 2003

Van Witteloostuijin

amp Muehlfeld 2008

Durand et al 2008

Weber amp Milliman

1997 Keller amp

Siegrist 2006ab

Bateman et al

2010 Weber et al

2013 Hoffman et

al 2015 Duxbury

et al 2005 Weber

et al 2002

Hopfensitz amp

Wranik 2009

Borghans et al

2009

Verma 2008 Riaz

amp Hunjra 2016

Tauni et al

20152016 Yang et

al 2012 Wang et


Investment

Decisions

Oehler et al 2018

Mayfield et al

2008 Oehler amp

Wedlich 2018

Hershey amp Mowen

2000 Hunter amp

Kemp 2004 van

Witteloostuijin amp

Muehlfeld 2008

Durand et al 2008

2013 Tauni et al

2015 2016 Yang

et al 2012

Brandstatter 2011

Hopfensitz amp

Wranik 2009

Personality Short-

term and Long-

term Investment

Decisions

Mayfield et al

2008

Personality and

Risk Taking

Behavior

Nicholson et al

2005 Zhao amp

Seibert 2006

Weber et al 2002

Filbeck et al 2005

Mayfield et al

2008 Brandstatter

2011 Hopfensitz amp

Wranik 2009

Borghans et al

2009

Risk Taking and

Decision-making

Riaz amp Hunjra

2016

MacCrimmon amp

Wehrung 1990

Samra Chaudary

208

Weber amp Milliman

1997 Keller amp

Siegrist 2006a b

Nosic amp Weber

2010 Bateman et

al 2010 Weber et

al 2013 Hoffman

et al 2015 Lim at

al 2013 Duxbury

et al 2005 Weber

et al 2002 Wang

et al 2006

Loewenstein et al

2001 Weber amp

Johnson 2008

Big-Five

Personality Short-

term and Long-

term Investment

Decisions

This Study

Big-Five

Personality Risk

Perception Short-

term and Long-

term Investment

Decisions

This Study

Appendix

209


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Heuristics and

Decision-making

Tversky amp

Kahneman 1974

Kahneman amp

Tversky 1979

Tversky amp

Kahneman 1981

De Bondt 1998 De

Bondt amp Thaler

1985 Shefrin amp

Statman 1985

Tversky amp

Kahneman 1992

Lakonishok et al

1994 Fox amp

Tversky 1995

Kahneman amp

Riepe 1998

Odean 1998 1999

Thaler 1999 Jain

amp Wu 2000

Hirshleifer 2001

Huberman 2001

Barber et al 2005

Grinblatt amp Han

2005 Nofsinger

2005 Mishra

2014 Yalcin et al

2016 Ahearne et

al 2004 Wang et

al 2011 Lewis

1999 Barberis amp

Xiong 2009

Wermers 1999

Barber amp Odean

2001 Statman et

al 2006 Epley amp

Gilovich 2005

Furnham amp Boo

2011 Glaser et al

2007 Thaler amp

Sunstein 2008

Kahneman amp

Tversky 1979 De

Bondt amp Thaler

1985 Fox amp

Tversky 1995

Tversky amp

Kahneman 1992

De Bondt 1998

Jain amp Wu 2000

Wang et al 2011

Grinblatt amp

Keloharju 2001

Lakonishok et al

1994 Coval amp

Moskowitz 1999

Chan et al 2005

Ahearne et al

2004 Olsen 1997

Borges et al 1999

Barber amp Odean

2001 Kang amp

Stulz 1997 Odean

1998 1999 Lewis

1999 Wermers

1999 Epley amp

Gilovich 2005

Huberman 2001

Barber et al 2005

Statman et al

2006 Glaser et al

2007 Wang et al

2011 Tversky amp

Kahneman 1981

Riff amp Yagil 2016

Yalcin et al 2016

Jaiyeoba amp Haron

2016 De Vries et

al 2017 Chan et

al 2005 Olsen

1997 Metawa et

al 2019

Samra Chaudary

210

Salience and

Investment

Decisions

Yalcin et al 2016

Huberman 2001

Tverskyamp

Kahneman 1973

Merton 1987

Heath amp Tversky

1991 Fox amp

Tversky 1995

Sirri amp Tufano

1998 Jain amp Wu

2000 Barber et al

2005 Nofsinger

2005Wang et al

2011 Grinblatt amp

Keloharju 2001

Jaiyeoba amp Haron

2016 Antoniou et

al 2010 Baker amp

Ricciardi 2014

Chan et al 2005

Riff amp Yagil 2016

Sizemore 2012

Giannetti amp

Koskinen 2010

Kumar amp

Goetzmann 2003

De Vries et al

2017 Chan et al

2005 Weber et al

2005

Institutional

Investors and

Salience

Coval amp

Moskowitz 1999

Strong amp Xu 2003

Chan et al 2005

Olsen 1997

Borges et al 1999

Goldstein amp

Gigerenzer 2002

Forbes et al 2015

Individual

Investors and

Salience

Baxter 1994

French amp Poterba

1991

Baker et al 2017

De Vries et al

2017 Tesar amp

Werner 1995

Appendix

211

Ahearne et al

2004 Kang amp

Stulz 1997

Seasholes amp Zhu

2010 Karlsson amp

Norden 2007

Cooper amp Kaplanis

1994

Gender and

Salience

Anderson et al

2011 Alrabadi et

al 2018 Ang et

al 2014 Cao et al

2009 Feng amp

Seasholes 2008

Karlsson amp Norden

2007

Mohammadi amp

Shafi 2018

Prast et al 2015

Seiler et al 2008

Seiler et al 2013

Tekce et al 2016

Wang et al 2011

Anderson et al

2011 Karlsson amp

Norden 2007

Mohammadi amp

Shafi 2018 Prast et

al 2015

Seiler et al 2008

Seiler et al 2013

Wang et al 2011

Alrabadi et al

2018 Feng amp

Seasholes 2008

Tekce et al 2016

Salience Short-

term and Long-

term Investment

Decisions

This Study

Salience

Institutional

Investors

Individual

Investors Gender

Short-term and

Long-term

Investment

Decisions

This Study

Samra Chaudary

212


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Attitudes and

Decision-making

Mahastanti amp

Hariady 2013

Akhtar amp Das

2019

Lim amp Teo 1997

Keller amp Siegrist

2006a Tang et al

2006 Vitell et al

2007 Tang et al

2008 Tang amp

Chen 2008 Klontz

amp Britt 2012

Gentina et al 2018

Hampson et al

2018 Tang amp Chiu

2003 Medina et al

1996 Yamauchi amp

Templer 1982

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Tang et al

2006 Li et al

2009 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011 Jia

et al 2013

Sardzoska ampTang

2012 Mahastanti amp

Hariady 2013 Shih

amp Ke 2014 Tang

et al 2018a

Akhtar amp Das 2019

Money Attitudes

and Decision-

making

Tang amp Chiu 2003

Vitell et al 2007

Tang et al

2008ab Tang amp

Chen 2008 Li et

al 2009 Klontz amp

Britt 2012 Shih amp

Ke 2014 Tang

2016 Britt 2016

Tang et al 2018a

Greenberg amp

Hershfield 2019

Money Attitudes

and Investment

Decisions

Keller amp Siegrist

2006a Jia et al

2013 Shih amp Ke

2014 Tang et al

2018a

Demographics and

Money Attitudes

Lim amp Teo 1997

Tang amp Chiu 2003

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011

Hampson et al

2018 Gentina et al

2018 Yamauchi amp

Templer 1982

Medina et al 1996

Tang amp Chiu 2003

Tang et al 2006

Tang et al

2008ab Sardzoska

ampTang 2012

Demographics and

Investment

Decision

Warneryd 2001

Haisley et al 2008

Greenberg amp

Appendix

213

Hershfield 2019

Cicchetti amp Dubin

1994 Grable et al

2004 Hlouskova et

al 2017

Greenberg 2013

Embrey and Fox

1997

Money Attitudes

Short-term and

Long-term

Investment

Decisions

This Study

Money Attitudes

Income

Inheritance Short-

term and Long-

term Investment

Decisions

This Study

Samra Chaudary

214
























Appendix

215






Samra Chaudary

216





Appendix

217





Samra Chaudary

218





Appendix

219





Samra Chaudary

220






1 2 3 4 5



Decision




1 2 3 4 5



week

1 2 3 4 5



1 2 3 4 5



managers

1 2 3 4 5


Decision




retirement purposes

1 2 3 4 5




1 2 3 4 5




and cost efficiency

1 2 3 4 5




1 2 3 4 5

Neuroticism





1 2 3 4 5



worthless

1 2 3 4 5



1 2 3 4 5

Appendix

221

Extraversion





Openness



art and nature

1 2 3 4 5




abstract ideas

1 2 3 4 5

Agreeableness




1 2 3 4 5


egotistical

1 2 3 4 5


calculating

1 2 3 4 5

Conscientiousness





1 2 3 4 5


down to work

1 2 3 4 5

Salience

(Yalcin et al 2016)



when investing

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5



known ones

1 2 3 4 5




1 2 3 4 5

Achievement





1 2 3 4 5





1 2 3 4 5

Power




1 2 3 4 5


freedom

1 2 3 4 5

Samra Chaudary

222




1 2 3 4 5


Obsession



all of my problems

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5

Budget



money

1 2 3 4 5



buy

1 2 3 4 5


scale

1 2 3 4 5


Risky

Moderately

Risky

Relatively more

Risky

Very Risky

Risk Perception

(Weber et al 2002)



1 2 3 4 5



1 2 3 4 5



1 2 3 4 5





1048713 Yes 1048713 No





Appendix

223



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23+



iv



|

by

|

Samra Chaudary

|





|

Abstract |

















v

























vi

Acknowledgments |

|





















this milestone

vii

Table of Contents



11 Introduction 1







21 Introduction 20









231 Measures 41

232 Methods 41

24 Results 46







31 Introduction 66

viii









331 Measures 81

332 Methods 81

34 Results 84








Inheritance 102

Abstract 102

41 Introduction 103








431 Measures 118

432 Methods 119

44 Results 122





ix



52 Key Findings 143




References 154







x

List of Tables














xi

List of Figures





























Introduction

1

1 Introduction

11 Introduction






















Samra Chaudary

2







Shih amp Ke 2014)

















Introduction

3
























Samra Chaudary

4
























Introduction

5
























Samra Chaudary

6
























Introduction

7







below







Samra Chaudary

8
























Introduction

9






paradigm

12 Research Context

















Samra Chaudary

10











Source wwwpsxcompk




Introduction

11




economy


















Chattopadhyay 2013)

Samra Chaudary

12






















Introduction

13























Samra Chaudary

14














Riepe 1998)










Introduction

15
























Samra Chaudary

16
























Introduction

17
























Samra Chaudary

18



















behavioral finance


19



Abstract





















Samra Chaudary

20




21 Introduction





















21
























Samra Chaudary

22
























23
























Samra Chaudary

24
























25




















al 2017 Odean 1998)

Samra Chaudary

26








1991)

















27























Samra Chaudary

28






of risky choices














Hypothesis)





29





















Samra Chaudary

30



Tupesamp

Christal

(1961)



Norman

(1963) Five








Myersamp

McCaulley

(1985)

Four



Hogan

(1982) Six


and Intellectance

CostaampMcCrae

(1985) Five


Conscientiousness

Kampamp Hough

(1986) Seven



Hogan

(1986) Six



Digmanamp Inouye

(1986) Five


Openness

Kampamp Gough

(1986) Five



Goldberg

(1990) Five


Intellect

Hough et al

(1990) Nine




Costaamp

McCrae

(1992)

Five

(Revised

NEO

personality

inventory)


Conscientiousness

Cattell









31

















McCrae 1992)





Samra Chaudary

32








dependability





















33











and moodiness




cultural interest















Samra Chaudary

34


Zaichkowsky 2004)













conscientiousness








investors


35






term investing


investing




long-term investing






term investing


term investing




Samra Chaudary

36

























37


financial market






















Samra Chaudary

38

























39









decisions










decisions





Samra Chaudary

40





Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1a

H2a

H3a

H4a

H5a

H6a

H6b

H6c

H6d

H6e

Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1b

H2b

H3b

H4b

H5b

H6f

H6g

H6h

H6i

H6j


41


231 Measures









232 Methods













Samra Chaudary

42

























43









2322 Data Analyses















Samra Chaudary

44

























45




















Samra Chaudary

46






24 Results

















ST-D 3075 0763 (0681)

LT-D 3279 0810 0551 (0702)

N 2524 0895 0206 0140 (0785)

E 3444 0929 0458 0581 -0020 (0878)

O 3298 0783 0385 0539 0099 0635 (0739)

A 2984 0880 -0229 -0273 -0358 -0199 -0189 (0760)

C 3228 0751 0253 0415 0074 0427 0432 -0345 (0707)

RP 2261 0921 0213 0308 0094 0220 0193 -0238 0169 (0812)


47
























Samra Chaudary

48



Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)


the stock market

0600 8579



0764 17620



0685 14911



0665 11816

Long-term

Investment

Decision

(Mayfield

et al

2008)



0750 23657



0716 17223




0663 14376



0659 13952


McCrae

1992)




0864 26438




feel like giving up

0770 13300


McCrae

1992)




Openness (Costa amp

McCrae

1992)






McCrae

1992)


workers

0722 10789



Conscientious

ness

(Costa amp

McCrae

1992)



done on time

0855 22739


Risk

Perception

(Weber et

al 2002)


growth mutual fund

0812 20781


stock

0888 31293


stock

0729 12008


reverse coded items


49



(CR)






Openness 0827 0546





Factors A C E LT-D

N O RP

ST-D

A

C 0634

E 0281 0706

LT-D 04 0711 0752

N 049 0352 0093 0214

O 0282 0747 0837 074 0133

RP 0343 0281 0267 0401 0127 0253

ST-D 0392 0485 065 0809 0283 0573 0303












Samra Chaudary

50

























51











of the sample size









Samra Chaudary

52



Estimates

p

value f2 R2 Q2

Statistical

Power

H1a N-gtST-D 0200 0002 0062

0352 0127 1

H2a E-gtST-D 0405 0000 0129

H3a O-gtST-D 0084 0318 0010

H4a A-gtST-D -0060 0314 0011

H5a C-gtST-D 0027 0829 0005

H1b N-gtLT-D 0073 0110 0017

0493 0209 1

H2b E-gtLT-D 0537 0000 0102

H3b O-gtLT-D 0515 0000 0069

H4b A-gtLT-D -0084 0119 0017

H5b C-gtLT-D 0373 0003 0021














2010)




53




amp Kenny 1986)




















Samra Chaudary

54









decision
















55










Direct Effect

Indirect Effect

Decision Rule

Independent

Variables

Mediator Dependent

Variables

β

p β

p

H6a Neuroticism

Risk

Perception ST-D

0202 0002 -0002 0817 Direct-only

Non-Mediation

H6b Extraversion

0392 0000 0013 0309 Direct-only

Non-Mediation

H6c Openness

0075 0331 0009 0453

No effect

Non-Mediation

H6d Agreeableness

-0040 0606 -0020 0116 No effect

Non-Mediation


0025 0708 0002 0849 No effect

Non-Mediation

H6f Neuroticism

Risk

Perception LT-D

0076 0140 -0003 0802 No effect

Non-Mediation

H6g Extraversion

0493 0000 0044 0005 Complimentary

Mediation

H6h Openness

0472 0000 0043 0006 Complimentary

Mediation

H6i Agreeableness

-0056 0276 0028 0034 Indirect-only

Mediation


0333 0000 0040 0030 Complimentary

Mediation







Samra Chaudary

56
























57




















investments




Samra Chaudary

58

























59
























Samra Chaudary

60

























61






















(Baker et al 2017)

Samra Chaudary

62

























63
























Samra Chaudary

64










65




Abstract





















Samra Chaudary

66








31 Introduction

















67
























Samra Chaudary

68



















321 Prospect Theory






69
























Samra Chaudary

70

























71
























Samra Chaudary

72






securities


















73












investor protection












Samra Chaudary

74

























75



















Soufian 2015)





Samra Chaudary

76

























77
























Samra Chaudary

78

























79
























Samra Chaudary

80



















81


331 Measures






332 Methods
















Samra Chaudary

82

















10 million

3322 Data Analyses







83
























Samra Chaudary

84








Deviation

Short-term

Investment

Decision

Long-term

Investment

Decision

Salience

Short-term

Investment

Decision

3113 0779 (0742)

Long-term

Investment

Decision

3311 0846 0518 (0728)

Salience 3039 0827 0359 0515 (0728)



34 Results












85





















Samra Chaudary

86



Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)







Long-term

Investment

Decision

(Mayfield

et al

2008)





etc)

0713 15358




Salience (Yalcin et

al 2016)





when investing

0668 15584










(CR)




Salience 0849 0531



Decision


Salience 0691



87
























Samra Chaudary

88





















Statistical

Power

H1 Salience -gt ST-D 03295 0000 0150 0224 0091 0999

H2 Salience -gt LT-D 05017 0000 0363 0340 0146 1000







p=0736)


89
























Samra Chaudary

90
























91


Investors


interval

Permutation

p-value

Compositional

invariance

ST-D 0965 [0941 1000] 0254 Yes

LT-D 0985 [0968 1000] 0097 Yes

Salience 0992 [0980 1000] 0235 Yes




95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -0287 [-0237 0243] 0022 No

LT-D -0119 [-0247 0233] 0327 Yes

Salience -0077 [-0244 0217] 0534 Yes




95 confidence

interval

Permutation

p-value

Equal variances

ST-D -0006 [-0350 0308] 0796 Yes

LT-D -0166 [-0305 0263] 0249 Yes

Salience -0099 [-0292 0302] 0494 Yes





interval

Permutation

p-value

Compositional

invariance

ST-D 0946 [0826 1000] 0017 No

LT-D 0986 [0961 1000] 0934 Yes

Salience 0989 [0970 1000] 0235 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -00006 [-0300 0313] 0693 Yes

LT-D -00007 [-0296 0296] 0100 Yes

Salience -00009 [-0308 0300] 0186 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal variances

ST-D 0025 [-0357 0443] 0330 Yes

LT-D 0030 [-0337 0419] 0402 Yes

Salience 0019 [-0341 0387] 0699 Yes



Samra Chaudary

92

























93





Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0236 0000 2519 0097 0078 0477 0000 7502 0337 0242

Salience -gt

LT-D 0454 0000 8148 0315 0229 0609 0012 1065 0655 0384





Path

coefficient

diff

Individual

-

Professional

p-value

Individual

vs

Professional

t-value

Individual

vs

Professional

f2 diff

Individual

-

Professional

R2 diff

Individual

- Professional

H3 Salience -gt

ST-D 0241 0023 2291 0235 0175

H4 Salience -gt

LT-D 0155 0048 1986 033 0168










Samra Chaudary

94










(Females) (Males)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0642 0000 8032 0775 0419 0316 0000 4496 0120 0104

Salience -gt

LT-D 0692 0000 1051 0992 0483 0516 0000 1086 0374 0269





Path

coefficient

diff

Female

-

Male

p-value

Female

vs

Male

t-value

Female

vs

Male

f2 diff

Female

-

Male

R2 diff

Female

-

Male

H3 Salience -gt

ST-D 0326 0001 3222 0655 0315

H4 Salience -gt

LT-D 0176 0024 2013 0618 0214





95
























Samra Chaudary

96

























97
























Samra Chaudary

98

























99
























Samra Chaudary

100













returns










investors


101





















Samra Chaudary

102



Abstract


















decisions




103

41 Introduction























Samra Chaudary

104

























105
























Samra Chaudary

106























developing economy


107


421 Prospect Theory



















1984)



Samra Chaudary

108

























109


economy






















Samra Chaudary

110




















et al 2018b 2018c)





111



amp Templer (1982)





















Samra Chaudary

112
























113
























Samra Chaudary

114






ones



















115
























Samra Chaudary

116
























117

















decisions


decisions





Samra Chaudary

118





431 Measures











Achievement

Power

Obsession

Budget


Love of Money



Inheritance

H1

H2

H3 H4H5 H6


119




432 Methods




















Samra Chaudary

120























in an economy


121

4322 Data Analyses























Samra Chaudary

122













Deviation


ST-D 3074 0836 (0742)

LT-D 3292 0856 0490 (0735)

Achievement 2893 0934 0297 0244 (0808)

Power 2928 0967 0268 0327 0645 (0821)

Obsession 2659 0898 0240 0209 0582 0610 (0744)


44 Results








123
























Samra Chaudary

124























and 45


125



Factor Loadings

Boot

sample

t-Values

Short-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



8112





Long-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



purposes

0798 23438



real estate etc)

0715 12630





0630 8323

Love of

Money

(second order-

formative

construct)

(Kelleramp

Siegrist

2006a)

Achievement




ability and effort

0690 17818





Power









Obsession









Budget






Samra Chaudary

126



Formative

Components of

Construct LoM

t-values of

Weights

Variance

Inflation Factor

(VIF)


Power 0458 26660 2155

Obsession 0290 14361 2029

Budget 0095 5767 1121



(CR)


(AVE)




Power 0912 0675

Obsession 0837 0555

Budget 0730 0595



Investment

Decision


Investment

Decision

Achievement

Budget 04662

Long-Term

Investment

Decision

03553 07748

Obsession 07911 04764 03102

Power 07591 03561 0432 08125

Short-Term

Investment

Decision

04514 03446 07436 04071 04057






127
























Samra Chaudary

128














p

value


Power


Short-term

investment decision

0341 0000 0160 0134 0058 0999


Long-term

investment decision

0328 0000 0154 0138 0059 0999



0002 p=0953)








129























Samra Chaudary

130

























131



















value

R2

without

moderator

R2

with

moderator

R2Δ Power

Result



Moderation


D

0373 0024 0134 0165 0031 0999 Moderation


D

0318 0044 0138 0201 0063 0999 Moderation


Money


Samra Chaudary

132




(ie low-income)






133





1

15

2

25

3

35

4

45

5

Low LoM High LoM

Short

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Long

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

Samra Chaudary

134

























135
























Samra Chaudary

136

























137










investments









effectively





Samra Chaudary

138

























139







Kim 2017)

















Samra Chaudary

140












future inheritance













141









Samra Chaudary

142

5 Conclusion

51 Introduction



















decisions



Conclusion

143















52 Key Findings









Samra Chaudary

144





















decisions



Conclusion

145
























Samra Chaudary

146


inheritance






















Conclusion

147











LT-D are













Samra Chaudary

148







collection
















Conclusion

149























Samra Chaudary

150























Conclusion

151
























Samra Chaudary

152











differently













Conclusion

153














Samra Chaudary

154






Economics 62(2) 313-336






Springer




58





References

155















423








Samra Chaudary

156


Reports 73(1) 3-11




95

















References

157



784
















Planning 45(5-6) 359-394





Samra Chaudary

158










179-207









59-72




References

159























Samra Chaudary

160

















Ability Testing






References

161






Finance 60(3) 1495-1534

















Samra Chaudary

162


284









NJ Erlbaum



Lawrence Earlbaum









60

References

163















42(3-5) 831-844


Finance 40(3) 793-805


York NY



Samra Chaudary

164











34(5) 1032-1046











References

165



126-134
















Methods 14(2) 370-388





Samra Chaudary

166




212







590



25(2) 195-211




Press





References

167














210



452



18(1) 39ndash50



Samra Chaudary

168
























References

169














of Finance 11(2) 325-357










Samra Chaudary

170










December














References

171




Calif Sheridan









Publications











Samra Chaudary

172



Research 91 159-168



170


















References

173






431









91- 103




1533-1597



Economics 70 74-89

Samra Chaudary

174




















126(1) 45


24(6) 852-859


References

175






659ndash680
















Sciences 11(3) 265-278

Samra Chaudary

176






















2(1999) 102-138

References

177



105-114





















Samra Chaudary

178



1325-1348



Washington DC




literature 88-02





317-333









References

179


353-358















ISSN 1454-9409






publications

Samra Chaudary

180














Research 59(4) 288-294



400






References

181





108



















Samra Chaudary

182










301-315






124




388 New York Wiley



References

183















Springer Singapore



Macmillan




Quarterly 10ndash21

Samra Chaudary

184












McGraw-Hill Irwin



145








References

185




IrwinMcGraw-Hill






280-307







Consumers 15(2) 111-124







Samra Chaudary

186











York McGraw-Hill











References

187















53(5) 1775-1798


1279-1299







Samra Chaudary

188











Review 37(2-3) 613-622













References

189

4643ndash4648



4(2) 71-84

















Economica 31(3) 377-420

Samra Chaudary

190









54



826-845











References

191







26(5) 34-35














75(9) 888-895



Samra Chaudary

192



12(5) e0178283







Finance 14 (2) 94-103












93ndash115

References

193







ed London Pearson









Finance 65(5) 1987-2010







24

Samra Chaudary

194








199-228



7207













References

195








445









53(5) 1589-1622






Samra Chaudary

196




York Modern Library




















References

197













19(6) 809ndash817











Samra Chaudary

198
























References

199







105465AMBPP201165869480





148(4) 919-937












Samra Chaudary

200








94-117












12(3) 183-206




References

201





















59 (4) 251-278



Samra Chaudary

202




Science 185(4157) 1124-1131

















369-379



References

203











Finance 12(1) 9-19













Samra Chaudary

204







making 15(4) 263-290




25(3) 597-609




Finance 54(2) 581-622








References

205







11(2) 270-295



179












and Trade 48(3) 23-34

Samra Chaudary

206













206



Appendix

207

Appendices


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Personality and

Decision-making

Heinstrom 2003

Nicholson et al

2005 Zhao amp

Seibert 2006

Mayfield et al

2008 Lim at al

2013 Oehler amp

Wedlich 2018

Oehler et al 2018

Heinstrom 2003

Van Witteloostuijin

amp Muehlfeld 2008

Durand et al 2008

Weber amp Milliman

1997 Keller amp

Siegrist 2006ab

Bateman et al

2010 Weber et al

2013 Hoffman et

al 2015 Duxbury

et al 2005 Weber

et al 2002

Hopfensitz amp

Wranik 2009

Borghans et al

2009

Verma 2008 Riaz

amp Hunjra 2016

Tauni et al

20152016 Yang et

al 2012 Wang et


Investment

Decisions

Oehler et al 2018

Mayfield et al

2008 Oehler amp

Wedlich 2018

Hershey amp Mowen

2000 Hunter amp

Kemp 2004 van

Witteloostuijin amp

Muehlfeld 2008

Durand et al 2008

2013 Tauni et al

2015 2016 Yang

et al 2012

Brandstatter 2011

Hopfensitz amp

Wranik 2009

Personality Short-

term and Long-

term Investment

Decisions

Mayfield et al

2008

Personality and

Risk Taking

Behavior

Nicholson et al

2005 Zhao amp

Seibert 2006

Weber et al 2002

Filbeck et al 2005

Mayfield et al

2008 Brandstatter

2011 Hopfensitz amp

Wranik 2009

Borghans et al

2009

Risk Taking and

Decision-making

Riaz amp Hunjra

2016

MacCrimmon amp

Wehrung 1990

Samra Chaudary

208

Weber amp Milliman

1997 Keller amp

Siegrist 2006a b

Nosic amp Weber

2010 Bateman et

al 2010 Weber et

al 2013 Hoffman

et al 2015 Lim at

al 2013 Duxbury

et al 2005 Weber

et al 2002 Wang

et al 2006

Loewenstein et al

2001 Weber amp

Johnson 2008

Big-Five

Personality Short-

term and Long-

term Investment

Decisions

This Study

Big-Five

Personality Risk

Perception Short-

term and Long-

term Investment

Decisions

This Study

Appendix

209


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Heuristics and

Decision-making

Tversky amp

Kahneman 1974

Kahneman amp

Tversky 1979

Tversky amp

Kahneman 1981

De Bondt 1998 De

Bondt amp Thaler

1985 Shefrin amp

Statman 1985

Tversky amp

Kahneman 1992

Lakonishok et al

1994 Fox amp

Tversky 1995

Kahneman amp

Riepe 1998

Odean 1998 1999

Thaler 1999 Jain

amp Wu 2000

Hirshleifer 2001

Huberman 2001

Barber et al 2005

Grinblatt amp Han

2005 Nofsinger

2005 Mishra

2014 Yalcin et al

2016 Ahearne et

al 2004 Wang et

al 2011 Lewis

1999 Barberis amp

Xiong 2009

Wermers 1999

Barber amp Odean

2001 Statman et

al 2006 Epley amp

Gilovich 2005

Furnham amp Boo

2011 Glaser et al

2007 Thaler amp

Sunstein 2008

Kahneman amp

Tversky 1979 De

Bondt amp Thaler

1985 Fox amp

Tversky 1995

Tversky amp

Kahneman 1992

De Bondt 1998

Jain amp Wu 2000

Wang et al 2011

Grinblatt amp

Keloharju 2001

Lakonishok et al

1994 Coval amp

Moskowitz 1999

Chan et al 2005

Ahearne et al

2004 Olsen 1997

Borges et al 1999

Barber amp Odean

2001 Kang amp

Stulz 1997 Odean

1998 1999 Lewis

1999 Wermers

1999 Epley amp

Gilovich 2005

Huberman 2001

Barber et al 2005

Statman et al

2006 Glaser et al

2007 Wang et al

2011 Tversky amp

Kahneman 1981

Riff amp Yagil 2016

Yalcin et al 2016

Jaiyeoba amp Haron

2016 De Vries et

al 2017 Chan et

al 2005 Olsen

1997 Metawa et

al 2019

Samra Chaudary

210

Salience and

Investment

Decisions

Yalcin et al 2016

Huberman 2001

Tverskyamp

Kahneman 1973

Merton 1987

Heath amp Tversky

1991 Fox amp

Tversky 1995

Sirri amp Tufano

1998 Jain amp Wu

2000 Barber et al

2005 Nofsinger

2005Wang et al

2011 Grinblatt amp

Keloharju 2001

Jaiyeoba amp Haron

2016 Antoniou et

al 2010 Baker amp

Ricciardi 2014

Chan et al 2005

Riff amp Yagil 2016

Sizemore 2012

Giannetti amp

Koskinen 2010

Kumar amp

Goetzmann 2003

De Vries et al

2017 Chan et al

2005 Weber et al

2005

Institutional

Investors and

Salience

Coval amp

Moskowitz 1999

Strong amp Xu 2003

Chan et al 2005

Olsen 1997

Borges et al 1999

Goldstein amp

Gigerenzer 2002

Forbes et al 2015

Individual

Investors and

Salience

Baxter 1994

French amp Poterba

1991

Baker et al 2017

De Vries et al

2017 Tesar amp

Werner 1995

Appendix

211

Ahearne et al

2004 Kang amp

Stulz 1997

Seasholes amp Zhu

2010 Karlsson amp

Norden 2007

Cooper amp Kaplanis

1994

Gender and

Salience

Anderson et al

2011 Alrabadi et

al 2018 Ang et

al 2014 Cao et al

2009 Feng amp

Seasholes 2008

Karlsson amp Norden

2007

Mohammadi amp

Shafi 2018

Prast et al 2015

Seiler et al 2008

Seiler et al 2013

Tekce et al 2016

Wang et al 2011

Anderson et al

2011 Karlsson amp

Norden 2007

Mohammadi amp

Shafi 2018 Prast et

al 2015

Seiler et al 2008

Seiler et al 2013

Wang et al 2011

Alrabadi et al

2018 Feng amp

Seasholes 2008

Tekce et al 2016

Salience Short-

term and Long-

term Investment

Decisions

This Study

Salience

Institutional

Investors

Individual

Investors Gender

Short-term and

Long-term

Investment

Decisions

This Study

Samra Chaudary

212


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Attitudes and

Decision-making

Mahastanti amp

Hariady 2013

Akhtar amp Das

2019

Lim amp Teo 1997

Keller amp Siegrist

2006a Tang et al

2006 Vitell et al

2007 Tang et al

2008 Tang amp

Chen 2008 Klontz

amp Britt 2012

Gentina et al 2018

Hampson et al

2018 Tang amp Chiu

2003 Medina et al

1996 Yamauchi amp

Templer 1982

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Tang et al

2006 Li et al

2009 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011 Jia

et al 2013

Sardzoska ampTang

2012 Mahastanti amp

Hariady 2013 Shih

amp Ke 2014 Tang

et al 2018a

Akhtar amp Das 2019

Money Attitudes

and Decision-

making

Tang amp Chiu 2003

Vitell et al 2007

Tang et al

2008ab Tang amp

Chen 2008 Li et

al 2009 Klontz amp

Britt 2012 Shih amp

Ke 2014 Tang

2016 Britt 2016

Tang et al 2018a

Greenberg amp

Hershfield 2019

Money Attitudes

and Investment

Decisions

Keller amp Siegrist

2006a Jia et al

2013 Shih amp Ke

2014 Tang et al

2018a

Demographics and

Money Attitudes

Lim amp Teo 1997

Tang amp Chiu 2003

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011

Hampson et al

2018 Gentina et al

2018 Yamauchi amp

Templer 1982

Medina et al 1996

Tang amp Chiu 2003

Tang et al 2006

Tang et al

2008ab Sardzoska

ampTang 2012

Demographics and

Investment

Decision

Warneryd 2001

Haisley et al 2008

Greenberg amp

Appendix

213

Hershfield 2019

Cicchetti amp Dubin

1994 Grable et al

2004 Hlouskova et

al 2017

Greenberg 2013

Embrey and Fox

1997

Money Attitudes

Short-term and

Long-term

Investment

Decisions

This Study

Money Attitudes

Income

Inheritance Short-

term and Long-

term Investment

Decisions

This Study

Samra Chaudary

214
























Appendix

215






Samra Chaudary

216





Appendix

217





Samra Chaudary

218





Appendix

219





Samra Chaudary

220






1 2 3 4 5



Decision




1 2 3 4 5



week

1 2 3 4 5



1 2 3 4 5



managers

1 2 3 4 5


Decision




retirement purposes

1 2 3 4 5




1 2 3 4 5




and cost efficiency

1 2 3 4 5




1 2 3 4 5

Neuroticism





1 2 3 4 5



worthless

1 2 3 4 5



1 2 3 4 5

Appendix

221

Extraversion





Openness



art and nature

1 2 3 4 5




abstract ideas

1 2 3 4 5

Agreeableness




1 2 3 4 5


egotistical

1 2 3 4 5


calculating

1 2 3 4 5

Conscientiousness





1 2 3 4 5


down to work

1 2 3 4 5

Salience

(Yalcin et al 2016)



when investing

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5



known ones

1 2 3 4 5




1 2 3 4 5

Achievement





1 2 3 4 5





1 2 3 4 5

Power




1 2 3 4 5


freedom

1 2 3 4 5

Samra Chaudary

222




1 2 3 4 5


Obsession



all of my problems

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5

Budget



money

1 2 3 4 5



buy

1 2 3 4 5


scale

1 2 3 4 5


Risky

Moderately

Risky

Relatively more

Risky

Very Risky

Risk Perception

(Weber et al 2002)



1 2 3 4 5



1 2 3 4 5



1 2 3 4 5





1048713 Yes 1048713 No





Appendix

223



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23+



v

























vi

Acknowledgments |

|





















this milestone

vii

Table of Contents



11 Introduction 1







21 Introduction 20









231 Measures 41

232 Methods 41

24 Results 46







31 Introduction 66

viii









331 Measures 81

332 Methods 81

34 Results 84








Inheritance 102

Abstract 102

41 Introduction 103








431 Measures 118

432 Methods 119

44 Results 122





ix



52 Key Findings 143




References 154







x

List of Tables














xi

List of Figures





























Introduction

1

1 Introduction

11 Introduction






















Samra Chaudary

2







Shih amp Ke 2014)

















Introduction

3
























Samra Chaudary

4
























Introduction

5
























Samra Chaudary

6
























Introduction

7







below







Samra Chaudary

8
























Introduction

9






paradigm

12 Research Context

















Samra Chaudary

10











Source wwwpsxcompk




Introduction

11




economy


















Chattopadhyay 2013)

Samra Chaudary

12






















Introduction

13























Samra Chaudary

14














Riepe 1998)










Introduction

15
























Samra Chaudary

16
























Introduction

17
























Samra Chaudary

18



















behavioral finance


19



Abstract





















Samra Chaudary

20




21 Introduction





















21
























Samra Chaudary

22
























23
























Samra Chaudary

24
























25




















al 2017 Odean 1998)

Samra Chaudary

26








1991)

















27























Samra Chaudary

28






of risky choices














Hypothesis)





29





















Samra Chaudary

30



Tupesamp

Christal

(1961)



Norman

(1963) Five








Myersamp

McCaulley

(1985)

Four



Hogan

(1982) Six


and Intellectance

CostaampMcCrae

(1985) Five


Conscientiousness

Kampamp Hough

(1986) Seven



Hogan

(1986) Six



Digmanamp Inouye

(1986) Five


Openness

Kampamp Gough

(1986) Five



Goldberg

(1990) Five


Intellect

Hough et al

(1990) Nine




Costaamp

McCrae

(1992)

Five

(Revised

NEO

personality

inventory)


Conscientiousness

Cattell









31

















McCrae 1992)





Samra Chaudary

32








dependability





















33











and moodiness




cultural interest















Samra Chaudary

34


Zaichkowsky 2004)













conscientiousness








investors


35






term investing


investing




long-term investing






term investing


term investing




Samra Chaudary

36

























37


financial market






















Samra Chaudary

38

























39









decisions










decisions





Samra Chaudary

40





Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1a

H2a

H3a

H4a

H5a

H6a

H6b

H6c

H6d

H6e

Conscientiousness

Neuroticism

Extraversion

Openness

Agreeableness


Risk Perception

H1b

H2b

H3b

H4b

H5b

H6f

H6g

H6h

H6i

H6j


41


231 Measures









232 Methods













Samra Chaudary

42

























43









2322 Data Analyses















Samra Chaudary

44

























45




















Samra Chaudary

46






24 Results

















ST-D 3075 0763 (0681)

LT-D 3279 0810 0551 (0702)

N 2524 0895 0206 0140 (0785)

E 3444 0929 0458 0581 -0020 (0878)

O 3298 0783 0385 0539 0099 0635 (0739)

A 2984 0880 -0229 -0273 -0358 -0199 -0189 (0760)

C 3228 0751 0253 0415 0074 0427 0432 -0345 (0707)

RP 2261 0921 0213 0308 0094 0220 0193 -0238 0169 (0812)


47
























Samra Chaudary

48



Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)


the stock market

0600 8579



0764 17620



0685 14911



0665 11816

Long-term

Investment

Decision

(Mayfield

et al

2008)



0750 23657



0716 17223




0663 14376



0659 13952


McCrae

1992)




0864 26438




feel like giving up

0770 13300


McCrae

1992)




Openness (Costa amp

McCrae

1992)






McCrae

1992)


workers

0722 10789



Conscientious

ness

(Costa amp

McCrae

1992)



done on time

0855 22739


Risk

Perception

(Weber et

al 2002)


growth mutual fund

0812 20781


stock

0888 31293


stock

0729 12008


reverse coded items


49



(CR)






Openness 0827 0546





Factors A C E LT-D

N O RP

ST-D

A

C 0634

E 0281 0706

LT-D 04 0711 0752

N 049 0352 0093 0214

O 0282 0747 0837 074 0133

RP 0343 0281 0267 0401 0127 0253

ST-D 0392 0485 065 0809 0283 0573 0303












Samra Chaudary

50

























51











of the sample size









Samra Chaudary

52



Estimates

p

value f2 R2 Q2

Statistical

Power

H1a N-gtST-D 0200 0002 0062

0352 0127 1

H2a E-gtST-D 0405 0000 0129

H3a O-gtST-D 0084 0318 0010

H4a A-gtST-D -0060 0314 0011

H5a C-gtST-D 0027 0829 0005

H1b N-gtLT-D 0073 0110 0017

0493 0209 1

H2b E-gtLT-D 0537 0000 0102

H3b O-gtLT-D 0515 0000 0069

H4b A-gtLT-D -0084 0119 0017

H5b C-gtLT-D 0373 0003 0021














2010)




53




amp Kenny 1986)




















Samra Chaudary

54









decision
















55










Direct Effect

Indirect Effect

Decision Rule

Independent

Variables

Mediator Dependent

Variables

β

p β

p

H6a Neuroticism

Risk

Perception ST-D

0202 0002 -0002 0817 Direct-only

Non-Mediation

H6b Extraversion

0392 0000 0013 0309 Direct-only

Non-Mediation

H6c Openness

0075 0331 0009 0453

No effect

Non-Mediation

H6d Agreeableness

-0040 0606 -0020 0116 No effect

Non-Mediation


0025 0708 0002 0849 No effect

Non-Mediation

H6f Neuroticism

Risk

Perception LT-D

0076 0140 -0003 0802 No effect

Non-Mediation

H6g Extraversion

0493 0000 0044 0005 Complimentary

Mediation

H6h Openness

0472 0000 0043 0006 Complimentary

Mediation

H6i Agreeableness

-0056 0276 0028 0034 Indirect-only

Mediation


0333 0000 0040 0030 Complimentary

Mediation







Samra Chaudary

56
























57




















investments




Samra Chaudary

58

























59
























Samra Chaudary

60

























61






















(Baker et al 2017)

Samra Chaudary

62

























63
























Samra Chaudary

64










65




Abstract





















Samra Chaudary

66








31 Introduction

















67
























Samra Chaudary

68



















321 Prospect Theory






69
























Samra Chaudary

70

























71
























Samra Chaudary

72






securities


















73












investor protection












Samra Chaudary

74

























75



















Soufian 2015)





Samra Chaudary

76

























77
























Samra Chaudary

78

























79
























Samra Chaudary

80



















81


331 Measures






332 Methods
















Samra Chaudary

82

















10 million

3322 Data Analyses







83
























Samra Chaudary

84








Deviation

Short-term

Investment

Decision

Long-term

Investment

Decision

Salience

Short-term

Investment

Decision

3113 0779 (0742)

Long-term

Investment

Decision

3311 0846 0518 (0728)

Salience 3039 0827 0359 0515 (0728)



34 Results












85





















Samra Chaudary

86



Standardized

Factor

Loadings

Boot

sample t-

Values

Short-term

Investment

Decision

(Mayfield

et al

2008)







Long-term

Investment

Decision

(Mayfield

et al

2008)





etc)

0713 15358




Salience (Yalcin et

al 2016)





when investing

0668 15584










(CR)




Salience 0849 0531



Decision


Salience 0691



87
























Samra Chaudary

88





















Statistical

Power

H1 Salience -gt ST-D 03295 0000 0150 0224 0091 0999

H2 Salience -gt LT-D 05017 0000 0363 0340 0146 1000







p=0736)


89
























Samra Chaudary

90
























91


Investors


interval

Permutation

p-value

Compositional

invariance

ST-D 0965 [0941 1000] 0254 Yes

LT-D 0985 [0968 1000] 0097 Yes

Salience 0992 [0980 1000] 0235 Yes




95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -0287 [-0237 0243] 0022 No

LT-D -0119 [-0247 0233] 0327 Yes

Salience -0077 [-0244 0217] 0534 Yes




95 confidence

interval

Permutation

p-value

Equal variances

ST-D -0006 [-0350 0308] 0796 Yes

LT-D -0166 [-0305 0263] 0249 Yes

Salience -0099 [-0292 0302] 0494 Yes





interval

Permutation

p-value

Compositional

invariance

ST-D 0946 [0826 1000] 0017 No

LT-D 0986 [0961 1000] 0934 Yes

Salience 0989 [0970 1000] 0235 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal mean

values

ST-D -00006 [-0300 0313] 0693 Yes

LT-D -00007 [-0296 0296] 0100 Yes

Salience -00009 [-0308 0300] 0186 Yes


(Female-Male)

95 confidence

interval

Permutation

p-value

Equal variances

ST-D 0025 [-0357 0443] 0330 Yes

LT-D 0030 [-0337 0419] 0402 Yes

Salience 0019 [-0341 0387] 0699 Yes



Samra Chaudary

92

























93





Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0236 0000 2519 0097 0078 0477 0000 7502 0337 0242

Salience -gt

LT-D 0454 0000 8148 0315 0229 0609 0012 1065 0655 0384





Path

coefficient

diff

Individual

-

Professional

p-value

Individual

vs

Professional

t-value

Individual

vs

Professional

f2 diff

Individual

-

Professional

R2 diff

Individual

- Professional

H3 Salience -gt

ST-D 0241 0023 2291 0235 0175

H4 Salience -gt

LT-D 0155 0048 1986 033 0168










Samra Chaudary

94










(Females) (Males)

Hypotheses Path

coefficient

p

value

t

value f2 R2

Path

coefficient

p

value

t

value f2 R2

Salience -gt

ST-D 0642 0000 8032 0775 0419 0316 0000 4496 0120 0104

Salience -gt

LT-D 0692 0000 1051 0992 0483 0516 0000 1086 0374 0269





Path

coefficient

diff

Female

-

Male

p-value

Female

vs

Male

t-value

Female

vs

Male

f2 diff

Female

-

Male

R2 diff

Female

-

Male

H3 Salience -gt

ST-D 0326 0001 3222 0655 0315

H4 Salience -gt

LT-D 0176 0024 2013 0618 0214





95
























Samra Chaudary

96

























97
























Samra Chaudary

98

























99
























Samra Chaudary

100













returns










investors


101





















Samra Chaudary

102



Abstract


















decisions




103

41 Introduction























Samra Chaudary

104

























105
























Samra Chaudary

106























developing economy


107


421 Prospect Theory



















1984)



Samra Chaudary

108

























109


economy






















Samra Chaudary

110




















et al 2018b 2018c)





111



amp Templer (1982)





















Samra Chaudary

112
























113
























Samra Chaudary

114






ones



















115
























Samra Chaudary

116
























117

















decisions


decisions





Samra Chaudary

118





431 Measures











Achievement

Power

Obsession

Budget


Love of Money



Inheritance

H1

H2

H3 H4H5 H6


119




432 Methods




















Samra Chaudary

120























in an economy


121

4322 Data Analyses























Samra Chaudary

122













Deviation


ST-D 3074 0836 (0742)

LT-D 3292 0856 0490 (0735)

Achievement 2893 0934 0297 0244 (0808)

Power 2928 0967 0268 0327 0645 (0821)

Obsession 2659 0898 0240 0209 0582 0610 (0744)


44 Results








123
























Samra Chaudary

124























and 45


125



Factor Loadings

Boot

sample

t-Values

Short-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



8112





Long-term

Investment

Decision

(reflective

construct)

(Mayfield

et al

2008)



purposes

0798 23438



real estate etc)

0715 12630





0630 8323

Love of

Money

(second order-

formative

construct)

(Kelleramp

Siegrist

2006a)

Achievement




ability and effort

0690 17818





Power









Obsession









Budget






Samra Chaudary

126



Formative

Components of

Construct LoM

t-values of

Weights

Variance

Inflation Factor

(VIF)


Power 0458 26660 2155

Obsession 0290 14361 2029

Budget 0095 5767 1121



(CR)


(AVE)




Power 0912 0675

Obsession 0837 0555

Budget 0730 0595



Investment

Decision


Investment

Decision

Achievement

Budget 04662

Long-Term

Investment

Decision

03553 07748

Obsession 07911 04764 03102

Power 07591 03561 0432 08125

Short-Term

Investment

Decision

04514 03446 07436 04071 04057






127
























Samra Chaudary

128














p

value


Power


Short-term

investment decision

0341 0000 0160 0134 0058 0999


Long-term

investment decision

0328 0000 0154 0138 0059 0999



0002 p=0953)








129























Samra Chaudary

130

























131



















value

R2

without

moderator

R2

with

moderator

R2Δ Power

Result



Moderation


D

0373 0024 0134 0165 0031 0999 Moderation


D

0318 0044 0138 0201 0063 0999 Moderation


Money


Samra Chaudary

132




(ie low-income)






133





1

15

2

25

3

35

4

45

5

Low LoM High LoM

Short

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

1

15

2

25

3

35

4

45

5

Low LoM High LoM

Long

-T

erm

Invest

ment

Deci

sion

No Inheritance

Inheritance

Samra Chaudary

134

























135
























Samra Chaudary

136

























137










investments









effectively





Samra Chaudary

138

























139







Kim 2017)

















Samra Chaudary

140












future inheritance













141









Samra Chaudary

142

5 Conclusion

51 Introduction



















decisions



Conclusion

143















52 Key Findings









Samra Chaudary

144





















decisions



Conclusion

145
























Samra Chaudary

146


inheritance






















Conclusion

147











LT-D are













Samra Chaudary

148







collection
















Conclusion

149























Samra Chaudary

150























Conclusion

151
























Samra Chaudary

152











differently













Conclusion

153














Samra Chaudary

154






Economics 62(2) 313-336






Springer




58





References

155















423








Samra Chaudary

156


Reports 73(1) 3-11




95

















References

157



784
















Planning 45(5-6) 359-394





Samra Chaudary

158










179-207









59-72




References

159























Samra Chaudary

160

















Ability Testing






References

161






Finance 60(3) 1495-1534

















Samra Chaudary

162


284









NJ Erlbaum



Lawrence Earlbaum









60

References

163















42(3-5) 831-844


Finance 40(3) 793-805


York NY



Samra Chaudary

164











34(5) 1032-1046











References

165



126-134
















Methods 14(2) 370-388





Samra Chaudary

166




212







590



25(2) 195-211




Press





References

167














210



452



18(1) 39ndash50



Samra Chaudary

168
























References

169














of Finance 11(2) 325-357










Samra Chaudary

170










December














References

171




Calif Sheridan









Publications











Samra Chaudary

172



Research 91 159-168



170


















References

173






431









91- 103




1533-1597



Economics 70 74-89

Samra Chaudary

174




















126(1) 45


24(6) 852-859


References

175






659ndash680
















Sciences 11(3) 265-278

Samra Chaudary

176






















2(1999) 102-138

References

177



105-114





















Samra Chaudary

178



1325-1348



Washington DC




literature 88-02





317-333









References

179


353-358















ISSN 1454-9409






publications

Samra Chaudary

180














Research 59(4) 288-294



400






References

181





108



















Samra Chaudary

182










301-315






124




388 New York Wiley



References

183















Springer Singapore



Macmillan




Quarterly 10ndash21

Samra Chaudary

184












McGraw-Hill Irwin



145








References

185




IrwinMcGraw-Hill






280-307







Consumers 15(2) 111-124







Samra Chaudary

186











York McGraw-Hill











References

187















53(5) 1775-1798


1279-1299







Samra Chaudary

188











Review 37(2-3) 613-622













References

189

4643ndash4648



4(2) 71-84

















Economica 31(3) 377-420

Samra Chaudary

190









54



826-845











References

191







26(5) 34-35














75(9) 888-895



Samra Chaudary

192



12(5) e0178283







Finance 14 (2) 94-103












93ndash115

References

193







ed London Pearson









Finance 65(5) 1987-2010







24

Samra Chaudary

194








199-228



7207













References

195








445









53(5) 1589-1622






Samra Chaudary

196




York Modern Library




















References

197













19(6) 809ndash817











Samra Chaudary

198
























References

199







105465AMBPP201165869480





148(4) 919-937












Samra Chaudary

200








94-117












12(3) 183-206




References

201





















59 (4) 251-278



Samra Chaudary

202




Science 185(4157) 1124-1131

















369-379



References

203











Finance 12(1) 9-19













Samra Chaudary

204







making 15(4) 263-290




25(3) 597-609




Finance 54(2) 581-622








References

205







11(2) 270-295



179












and Trade 48(3) 23-34

Samra Chaudary

206













206



Appendix

207

Appendices


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Personality and

Decision-making

Heinstrom 2003

Nicholson et al

2005 Zhao amp

Seibert 2006

Mayfield et al

2008 Lim at al

2013 Oehler amp

Wedlich 2018

Oehler et al 2018

Heinstrom 2003

Van Witteloostuijin

amp Muehlfeld 2008

Durand et al 2008

Weber amp Milliman

1997 Keller amp

Siegrist 2006ab

Bateman et al

2010 Weber et al

2013 Hoffman et

al 2015 Duxbury

et al 2005 Weber

et al 2002

Hopfensitz amp

Wranik 2009

Borghans et al

2009

Verma 2008 Riaz

amp Hunjra 2016

Tauni et al

20152016 Yang et

al 2012 Wang et


Investment

Decisions

Oehler et al 2018

Mayfield et al

2008 Oehler amp

Wedlich 2018

Hershey amp Mowen

2000 Hunter amp

Kemp 2004 van

Witteloostuijin amp

Muehlfeld 2008

Durand et al 2008

2013 Tauni et al

2015 2016 Yang

et al 2012

Brandstatter 2011

Hopfensitz amp

Wranik 2009

Personality Short-

term and Long-

term Investment

Decisions

Mayfield et al

2008

Personality and

Risk Taking

Behavior

Nicholson et al

2005 Zhao amp

Seibert 2006

Weber et al 2002

Filbeck et al 2005

Mayfield et al

2008 Brandstatter

2011 Hopfensitz amp

Wranik 2009

Borghans et al

2009

Risk Taking and

Decision-making

Riaz amp Hunjra

2016

MacCrimmon amp

Wehrung 1990

Samra Chaudary

208

Weber amp Milliman

1997 Keller amp

Siegrist 2006a b

Nosic amp Weber

2010 Bateman et

al 2010 Weber et

al 2013 Hoffman

et al 2015 Lim at

al 2013 Duxbury

et al 2005 Weber

et al 2002 Wang

et al 2006

Loewenstein et al

2001 Weber amp

Johnson 2008

Big-Five

Personality Short-

term and Long-

term Investment

Decisions

This Study

Big-Five

Personality Risk

Perception Short-

term and Long-

term Investment

Decisions

This Study

Appendix

209


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Heuristics and

Decision-making

Tversky amp

Kahneman 1974

Kahneman amp

Tversky 1979

Tversky amp

Kahneman 1981

De Bondt 1998 De

Bondt amp Thaler

1985 Shefrin amp

Statman 1985

Tversky amp

Kahneman 1992

Lakonishok et al

1994 Fox amp

Tversky 1995

Kahneman amp

Riepe 1998

Odean 1998 1999

Thaler 1999 Jain

amp Wu 2000

Hirshleifer 2001

Huberman 2001

Barber et al 2005

Grinblatt amp Han

2005 Nofsinger

2005 Mishra

2014 Yalcin et al

2016 Ahearne et

al 2004 Wang et

al 2011 Lewis

1999 Barberis amp

Xiong 2009

Wermers 1999

Barber amp Odean

2001 Statman et

al 2006 Epley amp

Gilovich 2005

Furnham amp Boo

2011 Glaser et al

2007 Thaler amp

Sunstein 2008

Kahneman amp

Tversky 1979 De

Bondt amp Thaler

1985 Fox amp

Tversky 1995

Tversky amp

Kahneman 1992

De Bondt 1998

Jain amp Wu 2000

Wang et al 2011

Grinblatt amp

Keloharju 2001

Lakonishok et al

1994 Coval amp

Moskowitz 1999

Chan et al 2005

Ahearne et al

2004 Olsen 1997

Borges et al 1999

Barber amp Odean

2001 Kang amp

Stulz 1997 Odean

1998 1999 Lewis

1999 Wermers

1999 Epley amp

Gilovich 2005

Huberman 2001

Barber et al 2005

Statman et al

2006 Glaser et al

2007 Wang et al

2011 Tversky amp

Kahneman 1981

Riff amp Yagil 2016

Yalcin et al 2016

Jaiyeoba amp Haron

2016 De Vries et

al 2017 Chan et

al 2005 Olsen

1997 Metawa et

al 2019

Samra Chaudary

210

Salience and

Investment

Decisions

Yalcin et al 2016

Huberman 2001

Tverskyamp

Kahneman 1973

Merton 1987

Heath amp Tversky

1991 Fox amp

Tversky 1995

Sirri amp Tufano

1998 Jain amp Wu

2000 Barber et al

2005 Nofsinger

2005Wang et al

2011 Grinblatt amp

Keloharju 2001

Jaiyeoba amp Haron

2016 Antoniou et

al 2010 Baker amp

Ricciardi 2014

Chan et al 2005

Riff amp Yagil 2016

Sizemore 2012

Giannetti amp

Koskinen 2010

Kumar amp

Goetzmann 2003

De Vries et al

2017 Chan et al

2005 Weber et al

2005

Institutional

Investors and

Salience

Coval amp

Moskowitz 1999

Strong amp Xu 2003

Chan et al 2005

Olsen 1997

Borges et al 1999

Goldstein amp

Gigerenzer 2002

Forbes et al 2015

Individual

Investors and

Salience

Baxter 1994

French amp Poterba

1991

Baker et al 2017

De Vries et al

2017 Tesar amp

Werner 1995

Appendix

211

Ahearne et al

2004 Kang amp

Stulz 1997

Seasholes amp Zhu

2010 Karlsson amp

Norden 2007

Cooper amp Kaplanis

1994

Gender and

Salience

Anderson et al

2011 Alrabadi et

al 2018 Ang et

al 2014 Cao et al

2009 Feng amp

Seasholes 2008

Karlsson amp Norden

2007

Mohammadi amp

Shafi 2018

Prast et al 2015

Seiler et al 2008

Seiler et al 2013

Tekce et al 2016

Wang et al 2011

Anderson et al

2011 Karlsson amp

Norden 2007

Mohammadi amp

Shafi 2018 Prast et

al 2015

Seiler et al 2008

Seiler et al 2013

Wang et al 2011

Alrabadi et al

2018 Feng amp

Seasholes 2008

Tekce et al 2016

Salience Short-

term and Long-

term Investment

Decisions

This Study

Salience

Institutional

Investors

Individual

Investors Gender

Short-term and

Long-term

Investment

Decisions

This Study

Samra Chaudary

212


Literature

Evidences from

Developed

Economies

Evidences from

Developing

Economies

Attitudes and

Decision-making

Mahastanti amp

Hariady 2013

Akhtar amp Das

2019

Lim amp Teo 1997

Keller amp Siegrist

2006a Tang et al

2006 Vitell et al

2007 Tang et al

2008 Tang amp

Chen 2008 Klontz

amp Britt 2012

Gentina et al 2018

Hampson et al

2018 Tang amp Chiu

2003 Medina et al

1996 Yamauchi amp

Templer 1982

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Tang et al

2006 Li et al

2009 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011 Jia

et al 2013

Sardzoska ampTang

2012 Mahastanti amp

Hariady 2013 Shih

amp Ke 2014 Tang

et al 2018a

Akhtar amp Das 2019

Money Attitudes

and Decision-

making

Tang amp Chiu 2003

Vitell et al 2007

Tang et al

2008ab Tang amp

Chen 2008 Li et

al 2009 Klontz amp

Britt 2012 Shih amp

Ke 2014 Tang

2016 Britt 2016

Tang et al 2018a

Greenberg amp

Hershfield 2019

Money Attitudes

and Investment

Decisions

Keller amp Siegrist

2006a Jia et al

2013 Shih amp Ke

2014 Tang et al

2018a

Demographics and

Money Attitudes

Lim amp Teo 1997

Tang amp Chiu 2003

Oezgen amp Bayoglu

2005 Du amp Tang

2005 Bhardwaj amp

Bhattacharjee

2010 Carol amp

Samsinar 2011

Hampson et al

2018 Gentina et al

2018 Yamauchi amp

Templer 1982

Medina et al 1996

Tang amp Chiu 2003

Tang et al 2006

Tang et al

2008ab Sardzoska

ampTang 2012

Demographics and

Investment

Decision

Warneryd 2001

Haisley et al 2008

Greenberg amp

Appendix

213

Hershfield 2019

Cicchetti amp Dubin

1994 Grable et al

2004 Hlouskova et

al 2017

Greenberg 2013

Embrey and Fox

1997

Money Attitudes

Short-term and

Long-term

Investment

Decisions

This Study

Money Attitudes

Income

Inheritance Short-

term and Long-

term Investment

Decisions

This Study

Samra Chaudary

214
























Appendix

215






Samra Chaudary

216





Appendix

217





Samra Chaudary

218





Appendix

219





Samra Chaudary

220






1 2 3 4 5



Decision




1 2 3 4 5



week

1 2 3 4 5



1 2 3 4 5



managers

1 2 3 4 5


Decision




retirement purposes

1 2 3 4 5




1 2 3 4 5




and cost efficiency

1 2 3 4 5




1 2 3 4 5

Neuroticism





1 2 3 4 5



worthless

1 2 3 4 5



1 2 3 4 5

Appendix

221

Extraversion





Openness



art and nature

1 2 3 4 5




abstract ideas

1 2 3 4 5

Agreeableness




1 2 3 4 5


egotistical

1 2 3 4 5


calculating

1 2 3 4 5

Conscientiousness





1 2 3 4 5


down to work

1 2 3 4 5

Salience

(Yalcin et al 2016)



when investing

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5



known ones

1 2 3 4 5




1 2 3 4 5

Achievement





1 2 3 4 5





1 2 3 4 5

Power




1 2 3 4 5


freedom

1 2 3 4 5

Samra Chaudary

222




1 2 3 4 5


Obsession



all of my problems

1 2 3 4 5




1 2 3 4 5



1 2 3 4 5

Budget



money

1 2 3 4 5



buy

1 2 3 4 5


scale

1 2 3 4 5


Risky

Moderately

Risky

Relatively more

Risky

Very Risky

Risk Perception

(Weber et al 2002)



1 2 3 4 5



1 2 3 4 5



1 2 3 4 5





1048713 Yes 1048713 No





Appendix

223



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23+



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