Master of Philosophy in Management 6th Batch

Presentation on

Market Information and Stock Returns: The Nepalese Evidence

By Sudarshan Kadariya

Regd. No: 7-1-32-192-97Tribhuvan University

June 18, 2012

Presentation Plan

Background & Motivation

Research Gap, Research Questions & Objectives

Research Methodology

Major Findings

Conclusions

Background & Motivation

From the past decades, the financial markets have been suffering from the unforeseen and sudden economic turbulences that have been directly or indirectly influences the stock returns.

To identify these market influences, the separate discipline – the investment management was formed and developed chronologically through speculative, professionalism, and scientific phase (Francis, 1986).

Some studies became popular in firm specific variables which was focused towards predicting stock returns. For instance,

Stattman (1980), Chan, et.al (1991), Brav, et.al (2000), Daniel and Titman (2006) among others documented the book-to-market equity effects

Earnings-to-price effects by Basu (1977), Jafee, et.al (1989), Fama and French (1995) and La Porta (1996) among others

Banz (1981), Vassalou and Xing (2004), and Fama and French (2008) depicted the size effects, similarly,

Cash flows effects by Berk, et.al (1999) and Vuolteenaho (2002) among others

But, in the later period, the focus has been shifted towards the behavioral aspects. For instance,

Einhorn, et al. (1978) documented that people have great confidence in their fallible judgment.

Einhorn (1980) further conformed the overconfidence in judgment

Similarly, Ikenberry, et.al (1995), Odean (1999), Kaniel, et.al (2008), Foucault, et.al (2011), and Doskeland and Hvide (2011), among others, proved that the investor behavior is the major aspect for stock returns movements.

In sum, the recent focus has been shifted towards the intangibles rather than the fundamental effects on stock returns.

Discussion (i) – Return Decomposition

Total R

eturn

Figure 1: Graphical presentation shows the breakdown of a firm’s past return into tangible and intangible returns suggested by Daniel and Titman (2006)

Log(Pt-5)

t-5 t

Log (Pt)

Log (Pˆ)

Log (Pt-5)

Intangible Return

Tangible Return

Tangible Information Intangible Information

Market Information

Total Stock Returns

Tangible Returns Intangible Returns

LEADS

Figure 2: Conceptual Framework of market information and stock returns (the broader perspective)

Discussion (ii) – Market Info.&Returns (BP)

Figure 3: Conceptual Frameworks of Market Information and Stock Returns (the specific perspective)

Tangible / Quantitative Information

Intangible / Qualitative Information

Market Information

Tangible Returns

Intangible Returns

Total Stock Returns

L E

A D

S

B/M Equity

Investor Behavior

Market Behavior Market

Reaction

Media Effects

Psychology

Sentiments Over-confidence

News Effects

Values

Size Stock returns

Earnings

Cash Flow

Discussion (iii) – Market Info.&Returns (SP)

Figure 6: Good News

Regular Information Flow

Risk

Return

Rf

Figure 4: Normal/Informational

Irregular Information Flow

Risk

Return

Rf

Figure 5: Bad News

Bad News Events

Risk

Return

Rf

Good News Events

Discussion (iv) – New Events & Returns

Research Gap, Research Questions & Objectives

Financial economists and investors have been spending considerable time searching for best investment strategies that could help to yield sustainably above an average market returns but the reliable one is yet to be found.

Chan (2003), Vassalou and Xing (2004), Daniel and Titman (2006), Foucault, et.al (2011), Sun and Wei (2011), Doskeland and Hvide (2011), among others focused on firm specific accounting variables.

Merton (1987), Mitchell and Mulherin (1994), Maheu and McCurdy (2004), Boyd, et.al (2005), Zhang (2006), Tetlock (2007), Fang and Peress (2009), Hirshleifer, et.al (2009), Engelberg and Parsons (2011), among others focused on the intangibles (news and media, political party led government, lag variables, past performance of the firm, stock market behavior and investors’ sentiments, etc.)

Moreover, Van Rooij, et al. (2007) documented a significant association between financial literacy and investment decisions, Bogan (2006) suggested an association between stockholding and computer and Internet use.

On the other hands, Lusardi and Mitchell (2006) revealed the negative association between planning for retirement and financial education.

These evidences also suggest that the additional factors – investor awareness, financial education and the financial literacy also work as market reactors.

Based on these review, the study found considerable research gap on the area of stock returns and the market information. Thus, the study is initiated.

Research Questions: (11 RQs)

What is the relationship between past tangible information and future returns?

Is there relationship between intangible and future returns?

Is there association between the fundamentals to price scaled variables with the future returns?

Do the stock prices overreact to the past performance?

What are the most predictable fundamental accounting growth measures in stock exchange?

How long the past fundamentals help to predict the future returns?

What are the news effects on stock returns? What is the bad news effect? What is the good news effect? and what is the informational news effect?

Is there political leadership influence on Nepalese stock market? What are the effects of NC led government? CPN-UML led government? , UCPN(M) led government?, and other parties government?

What are the opinions of Nepalese stock investors on investment alternatives, decision making, market prices and stock returns?

What are the factors affecting investment decision making in equity investment?, and,

What are the opinions of stock investors on various issues like: stock returns,fundamental measures, mutual funds, central depository system, portfolio management services, credit rating agencies, sources of investment funds, rate of interest, the trading behavior on different conditions, and on the various emerging issues in stock market

performance?

Objectives:

To evaluate the relationship between stock returns and fundamental measures.

To determine the news effects – bad news, good news and informational news, on stock returns.

To examine the political leadership effects on stock returns.

To determine the factors affecting stock investment in Nepalese stock market, and

To examine investor opinions on various issues: investor education and personality type, preferences, trading behavior and practices, sources of funds for investment, risk perception, level of investor awareness, investor reactions and judgments on previous findings of the similar studies.

Methodology

Research Design Descriptive, and Causal-comparative

Nature of DatabaseSecondary data, and Primary data

Firm specif

ic variab

les

Market

returns

Financial

news

Political

leadership

Secondary data

Sources of secondary database (four types)

i. For firm specific variables: EPS, MPS, cash dividend, size, BPS, sales volume, and cash-flow suggested by Daniel and Titman (2006).

Population: NEPSE listed enterprises(176 enterprises with 1443 firm years: Both the manufacturing and non-manufacturing enterprises including delisted securities are employed.)

Sample: All the listed enterprises (data collection is based on availability

of historical data sources) (146 enterprises with 826 firm years)

Data type: Quantitative - annual

Data sources: SEBON files (hard and soft) along with the financial disclosure of concern enterprises.

Data collection: From Mid-July, 1994 to Mid-July, 2010Note: The firm year is defined as the difference between the mid-July 2010 and listing date of the enterprise.

Table 1: Overview of sector-wise observations

SN SectorObservable Observed Proportion

Percentage

Enterprises Firm Yrs Enterprises Firm Yrs Selection Obs.

A Commercial Banks 23 201 23 179 100.00 89.05 21.67

B Development Bank 40 139 37 125 92.50 89.93 15.13

C Finance Companies 61 486 59 378 96.72 77.78 45.76

D Insurance Companies 19 179 18 87 94.74 48.60 10.53

E Manufacturing firms 18 265 1 9 5.56 3.40 1.09

F Others (hydro, hotels, trading, telecom & film)

15 173 8 48 53.33 27.75 5.81

Total 176 1443 146 826 82.95 57.24 100.00

Total number of observations constitute 57.24 % of total observable firm year Even though the highest observable firm year for manufacturing sector, the observed number constitute the least (9 of 265)

ii. For market returns (suggested by Daniel and Titman, 2006)

Data types: Quantitative - annual, monthly and daily data series

Data collection: From Mid-July, 1994 to Mid-July, 2010

Data sources: NEPSE files (hard and soft)

Notes: • The annual average index is calculated by averaging the index of July 16th of previous year

and July 15th of subsequent year.• The annual period is describes the period covering July 16th to July 15th or, the Nepali calendar

year. i & ii - Data collected in August and September 2011

iii. For daily financial news: Similarly, for news effects – bad news, good news and informational news suggested by Domer (2005), Lee, et.al (1994) and Tetlock (2007).

Data types: Qualitative and Quantitative – news headlines, contents and

news heading counts – annual, monthly and daily basis(Total 1683 news headings with 536 bad news, 734 good news, and 413 informational news)

Data collection: From Mid-July, 1994 to Mid-July, 2010 (6029 days)

Data sources: Kantipur daily (library - Kantipur Pub. and TU Central

library)Note: “Kantipur” is selected because its publication was started (Thursday, February 18, 1993) prior to the establishment of NEPSE (Thursday, January 13, 1994).

Appendix C

SN Date News Count News१ Thursday, January 13, 1994 0 ने�प्से� शु�रु भएको दि�ने२ Friday, January 14, 1994 1 ने�पा�लमा� स्टको एक्सेचे�न्ज७ Wednesday, January 19, 1994 1 से�यर बज�रको भबिबष्य उज्जल

११ Sunday, January 23, 1994 1 ने�को ने अयर शु�यर बिनेष्को�सेने उत्से�हजनेको से�रुवा�त

१२ Monday, January 24, 1994 1 शु�यर बज�रमा� बितब्रत� : नेय� प्रणा�ल+ सेक्री-य. . . .. . . .

३००० Sunday, March 31, 2002 1 शु�यर को�र ब�रमा� अस्थि1रत� को�यमा2, ब�च्ने�को चे�पाल� मा�ल्यमा� ह्रा�से

३००७ Sunday, April 07, 2002 1 शु�यर बिबक्री-को चे�पा घट�पाछि8 मा9ल्य ब:�;दि�३००८ Monday, April 08, 2002 1 ब=गल���शु ब?कोल� ल�भ�=शु दि�ने�३०१४ Sunday, April 14, 2002 1 शु�यर बिबक्री-को चे�पा घट�पाछि8 मा9ल्य ब:�;दि� ज�र+३०२१ Sunday, April 21, 2002 1 शु�यर को�र ब�रमा� से�धा�रको क्रीमा ज�र+

. . . .

. . . .६०१३ Wednesday, June 30, 2010 1 ने�प्से�मा� बिगर�वाट को�यमा2६०१४ Thursday, July 01, 2010 1 ने�प्से� से�मा�न्य बढ्;य ६०१५ Friday, July 02, 2010 1 ने�प्से�मा� १५ अ=कोको ब:�;दि�६०१८ Monday, July 05, 2010 1 ट�छिलकोमाको शु�यरल� घट;य ने�प्से�

Total News Headings 1683  

Appendix DSN Bad News SN Good News SN Information Only

1 Ignorance of stock exchange rules and regulation by the listed companies

1 Categorization of listed companies - 'A', 'B'..

1 General information (e.g. privatization process, appointments, stock broker licencing, resignation, etc)

2 Delisting information 2 Cash dividends 2 Analytical coverage

3 Decrease in NEPSE 3 Increase in NEPSE index

3 Share allotment

4 Increase in cost of issuance 4 Listing information 4 IPO information

5 Withdrawal of foreign investment/investor

5 Disclosure of sensitive index as new index

5 SEBON & NEPSE rules & regulation disclosure

. . . . . .

. . . . . .

37 Software problem in NEPSE 22 Stock market exhibition

11 AGM information

38 Delay in share allotment 23 Ceasefire 12 OTC market information

39 Protest of stock investors 24 Positive circuit breaker 13 NRB/MOF regulations (Margin, capital gain tax, etc)

iv. For political leadership: political leadership effect – dummies of political leadership suggested by Worthington (2006).

Data types: Qualitative – list of PMs, tenure and their political parties

Data collection: From Mid-July, 1994 to Mid-July, 2010

Data sources: News collections and historical records

Note: The King’s regime is also assumed as a political leadership and placed into other parties’ categories. iii & iv - Data collected in October and November 2011

Appendix E

S.N. Name Term start Term end Political Party

1 Girija Prasad Koirala Sunday, May 26, 1991 Wednesday, November 30, 1994

Nepali Congress

2 Man Mohan Adhikari Wednesday, November 30, 1994

Tuesday, September 12, 1995

Communist Party of Nepal (Unified Marxist–Leninist)

3 Sher Bahadur Deuba Tuesday, September 12, 1995

Wednesday, March 12, 1997 Nepali Congress

4 Lokendra Bahadur Chand

Wednesday, March 12, 1997 Tuesday, October 07, 1997 Rastriya Prajatantra Party (Chand)

5 Surya Bahadur Thapa Tuesday, October 07, 1997 Wednesday, April 15, 1998 Rastriya Prajatantra Party

. . . . .

. . . . .14 Direct rule by King

Gyanendra Bir Bikram Shah Dev

Tuesday, February 01, 2005 Tuesday, April 25, 2006 –

15 Girija Prasad Koirala Tuesday, April 25, 2006 Wednesday, May 28, 2008 Nepali Congress

16 Girija Prasad Koirala Wednesday, May 28, 2008 Monday, August 18, 2008 Nepali Congress

17 Pushpa Kamal Dahal (alias Prachanda)

Monday, August 18, 2008 Monday, May 25, 2009 Unified Communist Party of Nepal (Maoist)

18 Madhav Kumar Nepal Monday, May 25, 2009 Sunday, February 06, 2011 Communist Party of Nepal (Unified Marxist–Leninist)

Sources of primary data (Survey)

A survey was started on 1st December and concluded on 31st December 2011.

Common stock investors were selected from different brokers’ floor in Kathmandu valley.

The selection of the broker’s floor was based on the random sampling procedure. Out of 39 brokerage firms in Kathmandu valley, 10 were selected.

With due consideration of the behavioral nature of the study, the time to approach to the stock investors is strictly managed right at 12:00 noon when stock market open for trading.

The sample size is considered 364 stock investors suggested by Cochran (1977) because of the undefined population of Nepalese stock investors.

The structured questionnaires (both in Nepali and English medium) with 36 questions (7 demographic and 29 others) were distributed.

The printed questionnaires were provided to the respondents at the brokers’ floor.

Total 164 filled-up questionnaires were collected thus the response rate is 45.06 percent.

Survey was conducted in December 2011

Tools for data analysis

Tools for secondary data analysis:

Descriptive statistics

Correlation matrix analysis,

Regression analysis,

Kolmogorov-Smirnov test,

Stock returns decomposition procedure

The test of significance of econometric models using t-tests

and f-tests.

Detection and correction of autocorrelation, multicolinearity

and heterocedasticity are the major tools for analysis.

Table 2: Data cleansing

SN OLS Assumptions Test1 Normal distribution of error terms/dependent

variableK-S

2 Dependent variable is a linear function of independent variables and error terms

Plot

3 Independent variables are unrelated to error terms Correlation

4 Homoscedasticity i.e. equal variance of dependent variables

Plot

5 Autocorrelation i.e. error terms Run

6 Multicollinearity of independent variables VIF

7 Outliers Plot

Note: Regression analysis is "robust" in that it will typically provide estimates that are unbiased and efficient even when one or more of the assumptions is not completely met.

Tools for primary analysis

Descriptive statistics of demographic variables

Frequency distribution

Simple tabular presentation

Cross table analysis

Mean score analysis for Likert items

Test of association – chi-square test, and

Factor analysis which includes: – Cronbach’s Alfa test– Correlation matrix analysis– Anti-image correlation matrix – the measure of sampling adequacy (MSA), – Kaiser-Meyer-Olkin (KMO) and Bartlett's Test, – The initial and rotated solution for factor analysis, and – The scree plot

Profile Analysis (Figure 7-18)

Majority of the selected variables exhibit the downward movement. Only 3 of 12 variables indicates the upward movements i.e. market equity, sales to price ratio and the sales revenue.

Table 3: Descriptive Statistics

Variables Unit N Mean Median Minimum MaximumQuartile Std.

Dev.Q1 Q3

Earnings per share Rs 826 29.15 21.18 -444.08 626.00 11.02 36.69 48.87

Market price per share Rs 826 545.07 295.00 44.00 6830.00 174.75 626.75 716.68

Book value per share Rs 826 160.29 138.21 -364.00 1005.86 114.36 183.35 97.77

Cash dividend Percent 823 11.78 1.05 0.00 560.00 0.00 10.53 35.23

Market equity Million (Rs) 826 287.78 92.07 8.00 15000.00 48.00 320.00 815.04

Sales revenue Million (Rs) 825 3200.67 598.07 0.01 50094.73 269.82 1776.33 6776.75

Cash flow Million (Rs) 826 31.38 1.53 -9523.19 9327.70 -0.36 18.59 492.67

Book to market ratio Times 826 0.56 0.47 -1.44 4.91 0.23 0.76 0.53

Earnings to price ratio Times 826 0.07 0.06 -3.52 1.60 0.03 0.11 0.21Cash flow to price ratio in '000' 826 66.21 5.35 -17968.28 12777.67 -1.68 48.46 866.73

Sales to price ratio in Million 825 5.59 2.08 0.00 80.21 0.91 5.65 9.54

Stock returns Percent 822 5.59 2.08 0.00 80.21 0.91 5.65 9.54

Average MPPS is more than 3 times of BVPS where the average stock returns is 5.59%

Table 4: Correlation Matrix

LogMPPS LogBVPS LogSales LogCashFlow LogME LogRt LogCSI

LogEPS 0.41 0.57 0.22 0.10 -0.04 0.09 -0.08

  (0.00) (0.00) (0.00) (0.02) (0.28) (0.09) (0.10)LogMPPS   0.40 0.31 0.42 0.40 0.30 0.35

    (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)LogBVPS     0.07 0.14 -0.05 0.02 -0.07

      (0.05) (0.00) (0.16) (0.64) (0.18)LogSales       0.21 0.39 0.15 0.26

        (0.00) (0.00) (0.00) (0.00)

LogCashFlow         0.61 0.08 0.30          (0.00) (0.18) (0.00)LogME           0.18 0.58

            (0.00) (0.00)LogRt             0.06

              (0.35)

9 sets of variables have no significant correlation and the remaining 19 pairs have significant positive correlation at 95 percent confidence level.

α b1 b2 b3 Model Sig R-squareK-S Test

of residualN

Panel A: Log (Bit/Mit) = α + b1 BMi0 + b2△Bi + b3△Mi + ut

bi -0.640 0.608 0.002 -0.001 0.000 0.95 0.05 437

p (0.000) (0.000) (0.000) (0.000)        

Panel B: Log (Bit/Mit) = α + b1 LogBMi0 + b2Log△Bi + b3Log△Mi + ut

bi 0.081 0.883 0.120 -0.186 0.000 0.98 0.20 50

p (0.000) (0.000) (0.000) (0.000)        

Priori (+) (+) (-)

The priori for b1, b2 and b3 are positive, positive and negative resp., which is also proved by the database/evidence.

Table 5 Regression analysis for book to market decomposition

Major Findings (14 basic models with 148 estimated models)

Table 6: B/M Decomposition: An Extension

  α b1 b2 b3 Model Sig R-squareK-S Test of DV

(p) N

Panel B: r(t-i,t) = α + b1 log [Bt-i/Pt-i] + b2 [Bt/Bt-i] + b3 [Pt/Pt-i] + ut

(i=2)bi -1.044 -0.175 0.003 1.068 0.000 0.882 0.146 401p (0.000) (0.000) (0.739) (0.000)  

(i=3)bi -0.971 -0.230 -0.007 1.012 0.000 0.870 0.200 287p (0.000) (0.000) (0.605) (0.000)  

(i=4)bi -0.959 -0.030 0.004 0.995 0.000 0.988 0.056 169p (0.000) (0.157) (0.445) (0.000)  

(i=5)bi -0.955 -0.019 -0.001 0.998 0.000 0.971 0.087 89p (0.000) (0.534) (0.829) (0.000)        

Panel C: r(t-i,t) = α + b1 log [Bt-i/Pt-i] + b2 log [Bt/Bt-i] + b3 log [Pt/Pt-i] + ut

(i=2)bi 0.109 -0.266 -0.094 2.006 0.000 0.822 0.161 403p (0.000) (0.000) (0.145) (0.000)  

(i=3)bi 0.141 -0.281 -0.136 2.299 0.000 0.827 0.064 297p (0.000) (0.000) (0.056) (0.000)  

(i=4)bi 0.033 -0.166 -0.076 3.106 0.000 0.964 0.074 124p (0.003) (0.000) (0.024) (0.000)  

(i=5)bi 0.036 -0.038 -0.060 3.166 0.000 0.965 0.070 95p (0.014) (0.298) (0.093) (0.000)        

Firm level stock returns is negatively affected by the lagged BM ratio and positively by market price to lagged market price ratio but, for book to lagged book values it is inconclusive. There is a significant lagged B/M effect for stock returns up to three years, while transforming independent variables it extend up to 4 years

Table 7: S/P Decomposition

Α b1 b2 b3Model

Sig R-squareK-S Test of Res/DV (p) N

Panel B: r(t-i,t) = α + b1 log [St-i/Pt-i] + b2 [St/St-i] + b3 [Pt/Pt-i] + ut

(i=2)bi -0.894 -0.002 0.000 0.985 0.000 0.867 0.200 380p (0.000) (0.718) (0.428) (0.000)  

(i=3)bi -0.801 -0.006 0.000 0.942 0.000 0.876 0.064 296p (0.000) (0.411) (0.209) (0.000)        

(i=4)bi -0.803 0.005 0.000 0.923 0.000 0.848 0.061 210p (0.000) (0.615) (0.283) (0.000)  

(i=5)bi -0.784 -0.006 0.000 0.964 0.000 0.885 0.053 155p (0.000) (0.572) (0.171) (0.000)        

Panel C: r(t-i,t) = α + b1 log [St-i/Pt-i] + b2 log [St/St-i] + b3 log [Pt/Pt-i] + ut

(i=2)bi 0.001 0.000 0.020 2.533 0.000 0.998 0.200 57

p (0.642) (0.634) (0.000) (0.000)  

(i=3)bi 0.009 -0.001 -0.003 2.663 0.000 0.997 0.200 65

p (0.058) (0.356) (0.080) (0.000)        

(i=4)bi 0.022 0.000 -0.005 2.584 0.000 0.992 0.200 47

p (0.031) (0.810) (0.172) (0.000)  

(i=5)bi 0.183 -0.026 -0.050 3.620 0.000 0.977 0.200 113

p (0.000) (0.000) (0.000) (0.000)        

Consistent positive relation between firm returns and price to lagged price ratio whereas inconclusive and least effects of lagged sales to price and sales to lagged sales ratio for stock returns.

Table 8: C/P Decompositionα b1 b2 b3 Model Sig R-square

K-S Test of Res/DV (p) N

Panel B: r(t-i,t) = α + b1 log [Ct-i/Pt-i] + b2 [Ct/Ct-i] + b3 [Pt/Pt-i] + ut

(i=2)bi -0.944 0.012 0.000 0.953 0.000 0.850 0.059 282p (0.000) (0.055) (0.736) (0.000)  

(i=2)bi -0.993 0.005 0.000 1.014 0.000 0.985 0.061 247p (0.000) (0.288) (0.074) (0.000)        

(i=3)bi -0.968 0.020 0.000 0.978 0.000 0.898 0.059 195p (0.000) (0.146) (0.577) (0.000)        

(i=4)bi -0.998 0.000 0.000 1.001 0.000 0.999 0.089 84p (0.000) (0.489) (0.000) (0.000)        

(i=5)bi -0.978 0.013 0.000 1.022 0.000 0.918 0.059 90p (0.000) (0.464) (0.845) (0.000)        Panel C: r(t-i,t) = α + b1 log [Ct-i/Pt-i] + b2 log [Ct/Ct-i] + b3 log [Pt/Pt-i] + ut

(i=1)bi -0.008 0.002 0.000 1.976 0.000 0.996 0.092 69p (0.163) (0.077) (0.785) (0.000)        

(i=2)bi -0.123 0.050 0.031 2.885 0.000 0.967 0.085 132p (0.003) (0.000) (0.001) (0.000)        

(i=3)bi -0.042 0.012 0.001 3.389 0.000 0.976 0.066 71p (0.398) (0.284) (0.965) (0.000)  

(i=4)bi 0.017 0.009 -0.007 3.505 0.000 0.959 0.199 83p (0.851) (0.660) (0.677) (0.000)  

(i=5)bi 0.072 -0.025 -0.030 4.349 0.000 0.963 0.093 67p (0.557) (0.368) (0.246) (0.000)        

Consistent positive effect of price to lagged price ratio for firm returns whereas inconclusive and least effects of lagged CF to price and CF to lagged CF ratio

Table 9: E/P Decomposition

α b1 b2 b3 Model Sig R-squareK-S Test of Res/DV (p) N

Panel B: r(t-i,t) = α + b1 log [Et-i/Pt-i] + b2 [Et/Et-i] + b3 [Pt/Pt-i] + ut

(i=1)bi -0.955 0.014 0.001 1.003 0.000 0.986 0.200 255

p (0.000) (0.030) (0.262) (0.000)  

(i=2)bi -0.894 0.032 0.001 0.993 0.000 0.961 0.200 134

p (0.000) (0.033) (0.462) (0.000)  

(i=3)bi -0.887 0.029 0.000 0.985 0.000 0.961 0.099 228

p (0.000) (0.027) (0.357) (0.000)  

(i=4)bi -0.825 -0.014 0.000 0.950 0.000 0.863 0.200 205

p (0.000) (0.701) (0.652) (0.000)  

(i=5)bi -0.829 -0.014 -0.001 0.962 0.000 0.887 0.050 156

p (0.000) (0.754) (0.350) (0.000)        

Panel C: r(t-i,t) = α + b1 log [Et-i/Pt-i] + b2 log [Et/Et-i] + b3 log [Pt/Pt-i] + ut

(i=1)bi 0.006 0.001 -0.004 1.918 0.000 0.994 0.200 180

p (0.025) (0.617) (0.114) (0.000)  

(i=2)bi -0.001 -0.003 -0.008 2.627 0.000 0.997 0.053 65

p (0.765) (0.369) (0.012) (0.000)  

(i=3)bi 0.002 -0.010 0.008 2.693 0.000 0.992 0.092 70

p (0.814) (0.148) (0.256) (0.000)  

(i=4)bi -0.018 -0.027 -0.026 3.655 0.000 0.967 0.200 149

p (0.567) (0.320) (0.234) (0.000)  

(i=5)bi 0.036 0.060 0.098 3.763 0.000 0.974 0.171 107

p (0.360) (0.075) (0.001) (0.000)        

Consistent positive price to lagged price effect for stock returns, and inconclusive effect of lagged E/P and earnings to lagged earnings ratio There is a significant effect of lagged E/P ratio for stock returns up to three years

Table 10Regression analysis of firm returns on price scaled variables

  α b1 b2 b3 b4 Model Sig R-squareK-S Test of Res (p)

N

r(t-i,t) = α + b0 [Bt-i/Pt-i] + b1 [St-i/Pt-i] + b2 [Ct-i/Pt-i] + b3 [Et-i/Pt-i] + ut

(i=1) bi -0.242 0.340 0.000 0.000 0.234 0.000 0.247 0.200 576p (0.000) (0.000) (0.000) (0.531) (0.000)  

(i=2) bi -0.269 0.354 0.000 0.000 0.262 0.000 0.289 0.067 502p (0.000) (0.000) (0.000) (0.067) (0.000)  

(i=3) bi -0.173 0.255 0.000 0.000 -0.019 0.000 0.114 0.200 319p (0.000) (0.000) (0.000) (0.156) (0.887)  

(i=4) bi 0.033 -0.049 0.000 0.000 0.217 0.019 0.041 0.053 289p (0.426) (0.273) (0.050) (0.015) (0.148)  

(i=5) bi 0.082 0.000 0.000 0.000 -0.338 0.539 0.013 0.200 236p (0.159) (0.996) (0.580) (0.356) (0.180)        

Maximum 3 years of historical accounting

database are useful for market predictability

Similarly, out of four price scaled variables only two

namely, B/M and E/P ratios have strong predictive power

On the other hands, S/P and C/P ratios have no predictive power for firm returns up to 5

lag years

Table 11: Regression analysis of firm returns on B/M, E/P, past returns and share issuance measuresrt = α + b1 BP(t-i,t) + b2 EP(t-i,t) + b3 rB(t-i,t) + b4 r(t-i,t) + b5 ι(t-i) + ut

  α b1 b2 b3 b4 b5 Model Sig R-squareK-S Test of Res(p) N

(i=0)bi 0.053 -0.017 0.022 0.050   0.000 0.000 0.204 0.064 549p (0.005) (0.492) (0.665) (0.011)   (0.000)        

(i=1)bi -0.152 0.259 0.130 -0.065 0.019 0.000 0.000 0.304 0.200 398p (0.000) (0.000) (0.023) (0.021) (0.197) (0.000)  

(i=1)bi -0.210 0.302 0.169 -0.049 0.033   0.000 0.237 0.200 398p (0.000) (0.000) (0.005) (0.096) (0.027)          

(i=2)bi -0.031 0.162 -0.015 -0.103 -0.127 0.000 0.000 0.471 0.074 312p (0.159) (0.000) (0.743) (0.000) (0.000) (0.000)  

(i=2)bi -0.071 0.201 -0.005 -0.103 -0.134   0.000 0.454 0.080 297p (0.001) (0.000) (0.916) (0.000) (0.000)          

(i=3)bi 0.057 0.043 0.230 0.065 -0.241 0.000 0.000 0.235 0.057 276p (1.631) (1.077) (2.053) (2.010) (-7.184) (-0.776)  

(i=3)bi 0.022 0.032 0.147 0.078 -0.229   0.000 0.255 0.200 254p (0.471) (0.382) (0.142) (0.007) (0.000)          

(i=4)bi 0.171 -0.300 0.499 0.072 -0.221 0.000 0.000 0.160 0.200 202p (0.001) (0.000) (0.004) (0.053) (0.000) (0.000)  

(i=4)bi 0.094 -0.232 0.443 0.065 -0.192   0.001 0.086 0.200 202p (0.053) (0.001) (0.014) (0.091) (0.001)          

(i=5)bi 0.141 -0.114 -0.928 0.703 -0.299 0.000 0.000 0.229 0.200 165p (2.433) (-1.516) (-3.266) (5.040) (-4.466) (3.129)  

(i=5)bi 0.195 -0.139 -0.901 0.622 -0.316   0.000 0.181 0.200 165p (0.001) (0.072) (0.002) (0.000) (0.000)          

Against the earlier findings, B/M ratio exhibit the

fluctuating relation with firm returns

In majority cases, the relationship between the past returns and the current firm returns is

negative which suggest that the early winner fail to achieve in later periods and vice-versa.

Table 12Regression Analysis of Firm Returns on Book-to-Market and Book Returns

r(t-i, t) = b0 + b1 BP (t-i, t) + b2 riB

(t-i,t) + ui,t

  α b1 b2 Model Sig R-squareK-S Test of Res (p)

N

(i=0)bi -0.024 0.052 0.012 0.001 0.030 0.200 430p (0.096) (0.003) (0.420)  

(i=1)bi 0.046 -0.003 0.034 0.004 0.036 0.200 305p (0.000) (0.838) (0.002)  

(i=2)bi 0.179 -0.107 0.078 0.000 0.100 0.200 285p (0.000) (0.000) (0.000)  

(i=3)bi 0.089 -0.025 0.045 0.047 0.026 0.200 232p (0.000) (0.222) (0.014)  

(i=4)bi 0.120 -0.071 0.069 0.005 0.049 0.200 212p (0.000) (0.016) (0.002)  

(i=5)bi 0.087 -0.061 0.164 0.172 0.022 0.200 158p (0.010) (0.152) (0.071)        

Even though book returns is not included in stock return calculations, it is proved that there is positive relationship between themAnd, in some cases, the strength of relationship is high and significant

Table 13An Analysis of Firm Returns on Price Scaled Variables with Fundamental Returns Measures

r(t-i, t) = y0 + y1BP (t-i,t) + y2SP (t-i.t) + y3CP (t-i,t) + y4EP(t-i,t) + y5.riB

(t-i,t) + y6.riS

(t-i, t) + y7.riC

(t-i, t) + y8. riE

(t-i, t) + ui,t

  α y1 y2 y3 y4 y5 y6 y7 y8Model Sig

R-square

K-S Test of Res/DV (p)

N

(i=1)bi 0.08 0.01 0.00 0.00 -0.03 -0.01 0.00 0.00 0.00 0.000 0.218 0.200 335t (5.01) (0.69) (-4.20) (4.02) (-1.05) (-0.63) (6.94) (1.25) (1.27)  

(i=1)bi 0.07 -0.02 0.00 0.00 0.06 0.00       0.000 0.135 0.200 313t (4.32) (-0.97) (-4.64) (4.55) (1.29) (0.40)  

(i=1)bi 0.06 0.02     -0.02 0.00       0.561 0.005 0.200 380t (3.65) (1.36) (-0.55) (-0.12)  

(i=2)bi 0.21 -0.20 0.00 0.00 0.39 0.05 0.00 0.00 0.00 0.000 0.221 0.200 271t (9.17) (-7.25) (-1.16) (0.71) (6.12) (3.76) (-0.78) (-0.28) (-2.28)  

(i=2)bi 0.18 -0.17     0.29 0.02 0.00   0.00 0.000 0.191 0.200 259t (10.21) (-6.75) (5.56) (1.84) (-0.26) (-2.29)  

(i=3)bi 0.19 -0.15 0.00 0.00 0.26 0.00 0.00 0.00 0.00 0.000 0.234 0.200 235t (6.91) (-4.53) (-1.65) (1.20) (4.18) (0.04) (5.95) (1.11) (-1.23)  

(i=3)bi 0.14 -0.08     0.20         0.005 0.038 0.051 275t (6.01) (-2.86) (2.73)  

(i=4)bi 0.20 -0.23 0.00 0.00 0.47 0.03 0.00 0.00 0.00 0.000 0.151 0.085 232t (4.80) (-4.47) (-1.47) (-0.33) (3.58) (1.39) (2.93) (-1.62) (-0.91)  

(i=4)bi 0.08 -0.09     0.31 0.03       0.001 0.100 0.200 160t (2.80) (-2.35) (3.54) (2.19)  

(i=5)bi 0.06 -0.09 0.00 0.00 0.46 0.05 0.00 0.00 0.00 0.000 0.220 0.200 158t (1.64) (-2.01) (-0.64) (-0.28) (2.81) (2.30) (4.85) (-0.10) (-0.93)  

(i=5)bi 0.04 -0.05     0.28 0.05     0.00 0.027 0.066 0.200 163t (1.16) (-1.10)     (1.66) (2.39)     (-1.41)        

B/M & E/P ratios have strong predictive

power whereas S/P & C/P have no predictive

power

The usefulness of the historical data is

proved to be the lagged 2 to 4 years

Among the fundamental return measures, only the

book returns has more explanatory power

Table 14Regressions Analysis of Holding Period Stock Returns with Intangible Information

  Α b0 b1 b2 b3 Model Sig R-squareK-S Test of Residuals(p)

N

Panel A: ri(t) = α + b0 BP (t-i) + b1 rB(t-i,t) + b2 rI(B) + b3 ι (t-i,t) + ut

(i=1)bi -0.154) 0.317 -0.108 0.033 0.000 0.000 0.245 0.057 435t (-5.119) (8.705) (-3.794) (1.955) (-3.482)  

(i=2)bi -0.016 0.174 -0.113 -0.124 0.000 0.000 0.372 0.178 356t (-0.550) (5.584) (-5.293) (-7.437) (-4.299)  

(i=3)bi 0.107 0.038 0.050 -0.186 0.000 0.000 0.201 0.200 302t (2.506) (0.903) (1.359) (-4.860) (-3.936)  

(i=4)bi 0.304 -0.249 0.049 -0.136 0.000 0.000 0.239 0.200 209t (5.670) (-4.275) (1.350) (-2.487) (-7.227)  

(i=5)bi 0.513 -0.495 0.334 -0.335 0.000 0.000 0.291 0.200 173t (6.942) (-5.848) (2.478) (-4.954) (-5.536)        

Panel B: ri(t) = α + b0 SP(t-i) + b1 rS(t-i,t) + b2 rI(S) + b3 ι (t-i,t) + ut

(i=1)bi 0.027 0.000 0.000 0.020 0.000 0.000 0.253 0.053 445t (1.476) (10.643) (-1.553) (1.187) (-11.322)  

(i=2)bi 0.066 0.000 0.000 -0.077 0.000 0.000 0.547 0.054 281t (4.535) (9.971) (5.758) (-6.205) (-13.031)  

(i=3)bi 0.074 0.000 0.000 -0.119 0.000 0.000 0.338 0.200 296t (2.881) (8.533) (-0.696) (-3.347) (-7.948  

(i=4)bi 0.117 0.000 0.000 -0.060 0.000 0.000 0.218 0.200 238t (3.312) (5.604) (-0.223) (-1.029) (-7.446)  

(i=5)bi 0.108 0.000 0.000 -0.104 0.000 0.000 0.224 0.200 176t (2.478) (4.105) (2.239) (-1.545) (-5.804)        

Significant B/M effect except 3 lag periods but relation is inconclusiveIntangibles using B/M shows –ve effects except 1 lagShare issuance measure have no effect

No effect of S/P for returnsIntangibles using S/P shows –ve effects except 1 lagShare issuance measure have no effect

  Α b0 b1 b2 b3 Model Sig R-squareK-S Test of Residuals(p)

N

Panel C: ri(t) = α + b0 CP(t-i) + b1 rC(t-i,t) + b2 rI(C) + b3 ι (t-i,t) + ut

(i=1)bi 0.071 0.000 -0.001 -0.023 0.000 0.000 0.157 0.113 406t (4.549) (-0.779) (-1.651) (-1.584) (-8.370)  

(i=2)bi 0.065 0.000 0.000 -0.137 0.000 0.000 0.482 0.200 288t (4.427) (4.444) (0.131) (-10.268) (-9.469)  

(i=3)bi 0.141 0.000 0.000 -0.180 0.000 0.000 0.190 0.079 302t (5.445) (-0.198) (0.292) (-4.842) (-4.841)  

(i=4)bi 0.132 0.000 0.000 -0.150 0.000 0.000 0.217 0.081 215t (4.402) (2.362) (1.439) (-2.749) (-6.283)  

(i=5)bi 0.118 0.000 0.000 -0.193 0.000 0.000 0.152 0.200 168t (2.943) (0.722) (-0.757) (-2.839) (-4.073)        

Panel D: ri(t) = α + b0 EP(t-i) + b1 rE(t-i,t) + b2 rI(E) + b3 ι (t-i,t) + ut

(i=1)bi 0.066 0.131 0.000 -0.021 0.000 0.000 0.206 0.100 383t (4.351) (2.746) (0.230) (-1.519) (-9.309)  

(i=2)bi 0.090 0.051 -0.001 -0.129 0.000 0.000 0.446 0.065 296t (5.762) (1.215) (-1.489) (-9.823) (-8.884)  

(i=3)bi 0.128 -0.042 0.000 -0.136 0.000 0.000 0.440 0.081 219t (6.702) (-0.621) (-1.301) (-5.561) (-8.960)  

(i=4)bi 0.142 -0.009 0.000 -0.148 0.000 0.000 0.136 0.200 226t (3.616) (-0.056) (-0.035) (-2.434) (-4.821)  

(i=5) bi 0.206 -0.735 0.000 -0.207 0.000 0.000 0.216 0.200 164t (4.333) (-3.181) (0.039) (-3.047) (-4.828)        

No effect of C/P for returnsIntangibles using C/P shows –ve effectsShare issuance measure have no effect

Least effect of E/P for returnsIntangibles using E/P shows –ve effectsFurther, the share issuance measure have no effect

Mostly, t

he intangibles

pull

down the s

tock re

turns

&

when th

e lag peri

od

increases

, the s

trength of

the rela

tionship also

inversely

incre

ases.

Table 15: News Effect on Average Market Returnsrm_avr = α + b0 bXt + b1 gXt + b2 iXt + ui

Model Constant bXt gXt iXt Sig. R2 K-S N

Panel A: Yearly database

1bi 0.001 -0.014 0.012   0.00 0.710 0.200 16t (0.015) (-4.576) (5.674)  

2bi 0.076   0.005 -0.009 0.09 0.310 0.190 16t (0.424) (2.381) (-1.050)  

3bi 0.004 -0.014 0.012 0.000 0.00 0.710 0.200 16t (0.035) (-4.109) (5.429) (-0.032)        

Panel B: Monthly database

4bi 0.026 -0.008     0.00 0.215 0.200 146t (5.115) (-6.284)          

5bi 0.008 -0.010 0.007 0.00 0.331 0.200 151t (1.447) (-7.746) (6.741)        

6bi 0.001 0.003 -0.002 0.00 0.092 0.063 141t (0.155)   (3.748) (-1.036)      

7bi 0.026 -0.007 0.000 0.00 0.239 0.200 134t (4.822) (-6.118)   (-0.051)      

8bi 0.011 -0.011 0.008 -0.001 0.00 0.424 0.200 145t (1.853) (-9.135) (7.821) (-0.301)        

Panel C: Daily database

9bi 0.001 -0.006     0.00 0.116 0.200 1,331t (5.592) (-13.174)          

10bi 0.000 -0.004 0.003 0.00 0.134 0.126 1,253t (3.042) (-10.473) (8.635)        

11bi 0.000 -0.005 0.001 0.00 0.108 0.064 1,259t (4.582) (-12.097)   (2.438)      

12bi 0.000 -0.004 0.002 0.001 0.00 0.125 0.068 1,209t (3.351) (-9.743) (8.078) (2.152)      

Findin

gs bas

ed on

AR:

-ve e

ffect

of bad

news

+ve im

pact o

f goo

d news

Inco

nsisten

t effe

ct of

info

rmat

ional

news

Table 16: News Effect on Mid-July Market Returnsrm_midjuly = α + b0 bXt + b1 gXt + b2 iXt + ui

Model Constant bXt gXt iXt Sig. R2 K-S NPanel A: Yearly database

1Bi 0.072 -0.020 0.015   0.00 0.750 0.200 16T (-0.926) (-5.837) (6.190)  

2Bi 0.241   0.006 -0.016 0.17 0.240 0.200 16T (1.044) (1.970) (-1.501)  

3Bi 0.141 -0.019 0.015 -0.004 0.00 0.760 0.200 16T (1.036) (-5.122) (6.075) (-0.625)        

Panel B: Monthly database

4Bi 0.031 -0.011     0.004 0.459 0.200 127T (7.308) (-10.294)            

5Bi 0.006 -0.013 0.010 0.00 0.595 0.200 137T (1.196) (-12.212) (11.590)          

6Bi -0.001 0.007 -0.006 0.00 0.228 0.200 141T (-0.094)   (6.289) (-2.581)        

7Bi 0.037 -0.009 -0.004 0.00 0.409 0.054 131T (6.822) (-7.930)   (-2.118)        

8Bi 0.019 -0.013 0.009 -0.004 0.00 0.489 0.200 149T (2.995) (-10.241) (8.906) (-1.818)        

Panel C: Daily database

9Bi 0.001 -0.002     0.00 0.026 0.142 1,674T (5.579) (-6.738)            

10Bi 0.000 -0.002 0.001 0.00 0.035 0.200 1,687T (4.534) (-6.297) (4.447)          

11Bi 0.001 -0.002 -0.001 0.00 0.029 0.128 1,673T (5.981) (-6.746)   (-2.220)        

12Bi 0.000 -0.002 0.001 -0.001 0.00 0.036 0.149 1,689T (4.722) (-5.880) (4.708) (-2.211)        

Findings based

on EPR:

-ve effe

ct of b

ad news

+ve impact

of good new

s

-ve effe

ct of in

formatio

nal new

s

There is –ve effect of bad news, +ve effect of good news and inconsistent effect of informational news for market returns

The strength of good news have relatively weaker than bad news and the informational news on the other hands, have marginal effect for market returns

Table 17: Political Leadership Effect on Average Market Returnsrm_ave = α + b1D1 + b2D2 + b3D3 + ui

Model Constant b1D1 b2D2 b3D3 Sig. R2 K-S NPanel A: Yearly database

1Bi 0.180 -0.283 -0.104   0.318 0.162 0.200 16T (1.990) (-1.569) (-0.638)          

Panel B: Monthly database

2Bi -0.051 0.074 0.027 0.062 0.000 0.176 0.096 148T (-3.422) (4.648) (1.386) (3.841)        

Panel C: Daily database

3Bi -0.002 0.003 0.000 0.002 0.000 0.088 0.063 1,239T (-4.850) (6.863) (-0.478) (4.902)        

Table 18: Political Leadership Effect on Mid-July Market Returnsrm_midJul = α + b1D1 + b2D2 + b3D3 + ui

Model Constant b1D1 b2D2 b3D3 Sig. R2 K-S NPanel A: Yearly database

1Bi 0.185 -0.402 -0.041   0.198 0.220 0.200 16T (1.741) (-1.889) (-0.213)          

Panel B: Monthly database

2Bi -0.058 0.088 0.033 0.068 0.000 0.193 0.086 144T (-3.453) (4.910) (1.539) (3.727)        

Panel C: Daily database

3Bi -0.002 0.003 -0.001 0.002 0.000 0.086 0.111 1,715T (-4.483) (7.005) (-1.887) (4.719)        

There is lower contribution of the NC led government for the market growth where CPN-UML and UCPN (M) leadership have on an average higher/positive contribution for average stock returns.

Support the findings of Table 17

Table 19: A Regression Analysis of Market Returns on News and Political Leadership from 1994:07 – 2010:07Section A: rm_ave = α + b0 bXt + b1 gXt + b2 iXt + b4D1 + b5D2 + b6D3 + ui

Model

Panel A: Yearly

database

1

Panel B: Monthly database

2

Panel C: Daily

database

3(ANCOVA) bi t bi t bi tConstant 0.041 (0.266) -0.028 (-1.656) -0.002 (-3.812)b0 -0.014 (-3.083) -0.009 (-6.032) -0.003 (-7.165)b1 0.012 (4.269) 0.007 (6.245) 0.002 (8.312)b2 -0.001 (-0.183) 0.000 (0.184) 0.001 (2.081)b4     0.036 (2.197) 0.003 (5.500)b5 -0.002 (-0.012) 0.017 (0.912) 0.000 (-0.814)b6 -0.051 (-0.447) 0.035 (2.099) 0.002 (3.775)Sig. 0.014   0.000   0.000  R2 0.719   0.357   0.169  K-S 0.200   0.200   0.127  N 16   153   1,245  

Section B: rm_midJul = α + b0 bXt + b1 gXt + b2 iXt + b4D1 + b5D2 + b6D3 + ui Model

Panel A: Yearly

database

1

Panel B: Monthly database

2

Panel C: Daily

database

3(ANCOVA) bi t bi t bi tConstant 0.148 (0.846) -0.012 (-0.748) -0.001 (-3.313)b0 -0.019 (-3.856) -0.013 (-8.944) -0.001 (-2.299)b1 0.015 (4.759) 0.010 (8.881) 0.002 (6.485)b2 -0.004 (-0.570) -0.004 (-1.889) -0.001 (-2.792)b4     0.034 (2.158) 0.003 (6.116)b5 0.014 (0.083) 0.021 (1.164) -0.002 (-3.096)b6 -0.009 (-0.069) 0.026 (1.624) 0.001 (3.530)Sig. 0.007   0.000   0.000  R2 0.761   0.521   0.124  K-S 0.200   0.200   0.051  N 16   148   1,671  

Bad news have consistent –ve effect for returnsGood news have consistent +ve effect for returns

Informational news have inconclusive effect for returnsDaily news as well as leadership effect is more stronger than yearly and monthly effects

Monthly series have more predictive power than yearly and daily series

CPN-UML led government is proved to be a market friendly government followed by UCPN (M)

There is no reliable patterns of the variables&

There is no clarity that whether news leads market returns or vice-versa

Good news

headings

dictates the

other news

categories

Table 20: Respondents profileVariables Demographic Characteristics Number Percentage

Panel A: Gender

Female 12 7.3 Male 152 92.7 Total 164 100.0

 Panel B: Age of respondents

Below 25 13 7.9 25 to 40 100 61.0 Above 40 51 31.1 Total 164 100.0

 Panel E: Stock investment (size)

Less than Rs 5 lakh 51 31.1 5 to 10 27 16.5 10 to 25 39 23.8 More than 25 lakh 37 22.6 Undisclosed 10 6.1 Total 164 100.0

 Panel F: Experience

Less than 1 year 9 5.5 1 to 5 years 88 53.7 5 to 10 years 43 26.2 10 to 17 years 14 8.5 Above 17 years 5 3.0 Undisclosed 5 3.0 Total 164 100.0

Survey results

Table 21Investor's perception and awareness level

Panel A: Investor's perception

OptionsMF CDS CRA PMS

Number % Number % Number % Number %Not important 9 5.5 9 5.5 8 4.9 10 6.1Less important 7 4.3 8 4.9 11 6.7 8 4.9Neutral 14 8.5 10 6.1 19 11.6 21 12.8Important 58 35.4 51 31.1 53 32.3 59 36.0Most important 61 37.2 70 42.7 49 29.9 47 28.7Undisclosed 15 9.1 16 9.8 24 14.6 19 11.6Total 164 100 164 100 164 100 164 100

Panel B: Investor's Awareness

OptionsMF CDS CRA PMS

Number % Number % Number % Number %Not aware 25 15.2 17 10.4 33 20.1 24 14.6Less aware 10 6.1 16 9.8 18 11.0 20 12.2Neutral 21 12.8 22 13.4 29 17.7 30 18.3Aware 60 36.6 64 39.0 44 26.8 45 27.4Highly aware 37 22.6 33 20.1 26 15.9 30 18.3Undisclosed 11 6.7 12 7.3 14 8.5 15 9.1Total 164 100 164 100 164 100 164 100

Majority investors perceived MF, CDS, CRA and PMS are most important mechanism for market growth and development but they are not highly aware on any of them.

Table 22: Investor Judgment on various issues and evidencesPanel A: Investor judgment on the various issues

Statements N MeanAgree Disagree I don't know Total

%Num. % Num. % Num. %

a) Investing in IPO is more risky than investing in Secondary market (Loughran and Ritter, 1995)

160 1.875 22 13.4 136 82.9 2 1.2 97.6

b) Seasonal offerings do not maximize the shareholders' wealth 160 1.731 48 29.3 107 65.2 5 3.0 97.6

c) If reliable private info., it would be better to invest in single security 158 1.658 60 36.6 92 56.1 6 3.7 96.3

d) The most frequent trading is harmful for investors' wealth 159 1.792 42 25.6 108 65.9 9 5.5 97.0

e) News events lead some investors to react quickly (Klibanoff, et.al, 1998)

159 1.170 139 84.8 13 7.9 7 4.3 97.0

Panel B: Investor judgment on the various evidences

Statements N MeanSt. agree Agree Disagree St. disagree Total

%

Num. % Num. % Num. % Num. %

a) Stock market exhibit higher returns following good news and lower on bad news (Zhang, 2006)

157 1.904 52 31.71 74 45.12 25 15.24 6 3.66 95.7

b) Media effect, market noise, seasonal effect, etc strongly influence men investor but not for women (Biais et.al, 2005)

158 2.380 33 20.12 42 25.61 73 44.51 10 6.10 96.3

c) High information uncertainty enhance the investor's overconfidence (Jiang et.al, 2004)

155 2.523 25 15.24 49 29.88 56 34.15 25 15.24 94.5

d) Investor under-react to public info. and overreact to perceived private information (Chan, 2003)

158 2.259 31 18.90 66 40.24 50 30.49 11 6.71 96.3

e) Investors respond mistakenly in initial phase of the information disclosure (Ikenberry et.al, 1995)

156 2.340 26 15.85 59 35.98 63 38.41 8 4.88 95.1

Majority agreed on last issue & disagree on others

Majority agreed on only two evidences

Table 23Factor analysis: The rotated solution

StatementsComponents

1 2 3

X3   Brokers usually alter my investment decisions 0.768

X11  Media coverage largely influence my investment decisions 0.652

X15 My friends recommend/help me to decide most of my investment alternatives

0.587

X8  I use dividend payment records while buying and selling stocks 0.839

X7  I use the average prices (6 months, 1 yr, 2 yrs, etc) to determine the current prices

0.788

X10 It is important to look at debt and equity structure before investing 0.820

X5   I always evaluate the company profile & track records of management while investing

0.677

X9 The prices move in a direction (increasing/decreasing) provides insight about future price

0.457

External Factor

Self-knowledge

Factor

Firm Specific

Factor

Factor analysis concluded that there are three factors that affect the investment decision making process. Namely, the external factor (Brokers, Media & Friends), self-knowledge factor (using dividends & price records), and the firm specific factor (D-E structure, Management & price movement)

Only the three years of historical accounting data are useful to find the market signals.Book to price and earnings to price ratios have strong predictive power among the other price-scaled variables for firm level stock returns. There is negative effect of bad news, positive effect of good news, and inconsistent effect of informational news for market returns. Based on the assumptions of the study, it is proved that CPN-UML led government is a market friendly government compare to others, andThere are three factors that influences the stock price movement namely - the external factor, self-knowledge factor, and firm specific factor.

Conclusions

Thank you.