mba project work - performance evaluation of mutual fund

“Performance Evaluation of Indian Mutual Funds”

Submitted in partial fulfillment of the requirements for the Degree of Master of Business Administration in Pondicherry University

Submitted by: Under the Guidance of:

Name: Madesh.M Ms. ChayadeviRoll No. 2009 370 642MBA - Finance

DIRECTORATE OF DISTANCE EDUCATIONPONDICHERRY UNIVERSITY

PONDICHERRY – 605 014

2011

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ACKNOWLEDGEMENT

I would like to express my profound gratitude to all those who have been instrumental in the preparation

of this report which has been prepared in partial fulfillment of the requirements for the Degree of Master

of Business Administration in Pondicherry University.

We wish to place on record our deep sense of gratitude to Ms. Chayadevi a highly esteemed and

distinguished mentor for her expert advice and help.

Place: Bangalore

Date: 25.05.2011

Madesh.M

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DECLARATION

I hereby declare that the matter included in this report entitled “Performance Evaluation of Indian Mutual

Funds”, is the result of study carried out by me. I further declare that this is my original work and has not

been published anywhere before.

This Project Work has been carried out for the sole purpose of submission in partial fulfillment of partial

fulfillment of the requirements for the Degree of Master of Business Administration in Pondicherry

University.

The above is true to the best of our knowledge and information.

Name: Madesh. M

Reg. No. 2009 370 642

Ms Chayadevi

Project Mentor

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INDEX

Serial No. Topic Page Numbers

1 Executive summary 6-7

2 Introduction 8-9

3 Significance of the study 10

4 Literature review 11-17

5 Data 18

6 Research methodology 18-21

7 Data Analysis and interpretation 22-31

8 Findings and conclusion 32-33

9 References 34-35

10 Appendix 36-53

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APPENDIX

Appendix No. Description Page Numbers

Appendix 1 List of funds selected for study 36

Appendix 2 Average Returns of selected funds 37

Appendix 3 Absolute Returns of selected funds 38

Appendix 4 Standard Deviation of selected funds 39

Appendix 5 Betas of selected funds 40

Appendix 6 Relative Performance Index (RPI) 41

Appendix 7 Mann-Whitney U-Test of Average Returns 42

Appendix 8 Mann-Whitney U-Test of Absolute Returns 47

Appendix 9Hierarchical multiple clustering - Agglomeration method 52

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Executive Summary:

This study has been undertaken to evaluate the performance of the Indian Mutual Funds vis-à-vis the

Indian stock market. For the purpose of this study, 20 open ended equity based growth mutual funds were

selected as the sample. The data, which is the weekly NAV’s of the funds and the closing of the BSE

Sensex, were collected for a period of 5 years starting 19/03/2004 to 13/02/2009.

Different statistical tools were used on the data obtained to get the average returns, absolute returns,

standard deviation, Fund Beta, R-squared value, residual value, Relative Performance Index were

calculated. These variables of the funds were compared with the same variables of the market to assess

how the different funds have performed against the market.

A Statistical test, Mann Whitney U-Test, was done on the returns of the fund with respect to the Sensex

returns. Another U-Test was done taking absolute return as the variable. These U- Test were done to test

the hypothesis which was that the fund returns over the period of time are similar to the market returns

over the period of time.

All the funds were classified into a hierarchical cluster on the basis of their average returns, absolute

returns, standard deviation, fund beta, and relative performance index. This classification was to see

whether the funds have similar properties or not.

All the mutual funds gave similar returns with respect to the market expect for certain time period which

was during the late 2005 and early 2006. There is a positive correlation with the absolute returns of the

market and the mutual funds over the period of time. The study showed that the standard deviation of the

funds were high during the boom period in comparison with the market and were comparatively lower

when the recessionary trend started. The fund betas also show that there is significant correlation between

the fund returns and the market returns. Of the 21 funds considered for this study, 7 funds had RPI less

than 0.7, 3 funds had RPI of almost 1 and 11 funds had RPI of more than 1.

The results of the U-Test showed that all the funds are accepting the hypothesis that is they are giving

returns in sync with the market except for one fund which is UTI CCP Advantage growth fund, whose

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returns vary significantly from the market returns. With the help of clustering it was seen that a lot of

different funds have similar properties and so were classified into one cluster. There were a few outliers

who didn’t have any property in common with the other funds but still behaved more or less in the same

way as the market and other funds. A U-Test was also done on the absolute returns and the results of this

were also similar to the U-Test on average returns, that is, for UTI CCP Advantage Fund the returns were

not similar to the market returns and varied significantly.

Introduction:

The mutual fund industry has been in India for a long time. This came into existence in 1963 with the

establishment of Unit Trust of India, a joint effort by the Government of India and the Reserve Bank of

India. The next two decades from 1986 to 1993 can be termed as the period of public sector funds with

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entry of new public sector players into the mutual fund industry namely, Life Insurance Corporation of

India and General Insurance Corporation of India.

The year of 1993 marked the beginning of a new era in the Indian mutual fund industry with the entry of

private players like Morgan Stanley, J.P Morgan, and Capital International1. This was the first time when

the mutual fund regulations came into existence. SEBI (Security Exchange Board of India) was

established under which all the mutual funds in India were required to be registered. SEBI was set up as a

governing body to protect the interest of investor. By the end of 2008, the number of players in the

industry grew enormously with 462 fund houses functioning in the country.

With the rise of the mutual fund industry, establishing a mutual fund association became a prerequisite.

This is when AMFI (Association of Mutual Funds India) was set up in 1995 as a nonprofit organization.

Today AMFI ensures mutual funds function in a professional and healthy manner thereby protecting the

interest of the mutual funds as well as its investors.

The mutual fund industry is considered as one of the most dominant players in the world economy and is

an important constituent of the financial sector and India is no exception. The industry has witnessed

startling growth in terms of the products and services offered, returns churned, volumes generated and the

international players who have contributed to this growth. Today the industry offers different schemes

ranging from equity and debt to fixed income and money market.

The market has graduated from offering plain vanilla and equity debt products to an array of diverse

products such as gold funds, exchange traded funds (ETF’s), and capital protection oriented funds and

even thematic funds. In addition investments in overseas markets have also been a significant step. Due

credit for this evolution can be given to the regulators for building an appropriate framework and to the

fund houses for launching such different products. All these reasons have encouraged the traditional

conservative investor, from parking fund in fixed deposits and government schemes to investing in other

products giving higher returns.

It is interesting to note that the major benefits of investing in a mutual funds is to capitalize on the

opportunity of a professionally managed fund by a set of fund managers who apply their expertise in

investment. This is beneficial to the investors who may not have the relevant knowledge and skill in

1 India infoline website under the link mutual fund school, history 2 AMFI website as on April 21, 2009

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investing. Besides investors have an opportunity to invest in a diversified basket of stocks at a relatively

low price. Each investor owns a portion of the fund and hence shares the rise and fall in the value of the

fund. A mutual fund may invest in stocks, cash, bonds or a combination of these.

Mutual funds are considered as one of the best available investment options as compare to others

alternatives. They are very cost efficient and also easy to invest in. The biggest advantage of mutual

funds is they provide diversification, by reducing risk & maximizing returns.

India is ranked one of the fastest growing economies in the world. Despite this huge progression in the

industry, there still lies huge potential and room for growth. India has a saving rate of more than 35% of

GDP, with 80% of the population who save3. These savings could be channelized in the mutual funds

sector as it offers a wide investment option. In addition, focusing on the rapidly growing tier II and tier

III cities within India will provide a huge scope for this sector. Further tapping rural markets in India will

benefit mutual fund companies from the growth in agriculture and allied sectors. With subsequent easing

of regulations, it is estimated that the mutual fund industry will grow at a rate of 30% - 35% in the next 3

to 5 years and reach US 300 billion by 20154.

As it can be noted, there is huge growth and potential in the mutual fund industry. The development of

this sector so far has been commendable and with the above positive factors we are looking at a more

evolved industry.

Significance of the Study:

Over the last couple of years mutual funds have given impressive returns, especially equity funds 5 . The

growth period first started during early 2005 with markets appreciating significantly. With 2006

approaching more towards 2007, markets rallied like never before. The financial year 2007-08 was a year

of reckoning for the mutual fund industry in many ways. Most stocks were trading in green. All fund

houses boasted of giving phenomenal returns. Many funds outperformed markets. Equity markets were in

the limelight. Investors who were not exposed to equity stocks suddenly infused funds. AUM grew

considerably and fund houses were on a spree of launching new schemes.

3 Deccanherald.com under national, detailed story an article called “Saving rate high in India due to lack of social security”4 Sify.com under the link finance, business an article called “Mutual fund sector to grow at 30%-35% in 3-5 years”5 IBNlive.com under the link markets. Article called “Mutual Funds: The fading star of India”

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Growth funds which aim at giving capital appreciation invest in growth stocks of the fastest growing

companies. Since these funds are more risky providing above average earnings, investors pay a premium

for the same. These funds have grown to become extensively popular in India. All the leading fund

houses offer several schemes under the growth funds today.

The remarkable performance of this industry has attracted many researchers to study and examine the

growth, the performance of funds, the players in the market and the regulators. It is interesting to learn the

growth phase of these funds over this period.

The study aims at:

1. Comparing the performance of the selected funds vies-a-vies the benchmark index, BSE

(Bombay Stock Exchange) Sensex

2. Capturing differences in the performance levels, if any.

3. Ascertaining whether the returns generated by the funds are purely attributable to market

movement or individual fund performance.

Literature Review:

Performance evaluation of mutual funds is one of the preferred areas of research where a good amount of

study has been carried out. The area of research provides diverse views of the same.

For instance one paper 6evaluated the performance of Indian Mutual Fund Schemes in a bear market using

relative performance index, risk-return analysis, Treynor’s ratio, Sharpe’s ratio, Jensen’s measure, Fama’s

measure. The study finds that Medium Term Debt Funds were the best performing funds during the bear

period of September 98-April 2002 and 58 of 269 open ended mutual funds provided better returns than

the overall market returns.

6 Dr. Rao, Narayan “Performance Evaluation of Indian Mutual Funds”, www.ssrn.com, paper no.433100 and PP.1-24

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http://www.ssrn.com/

Another paper7 used Return Based Style Analysis (RBSA) to evaluate equity mutual funds in India using

quadratic optimization of an asset class factor model proposed by William Sharpe and analysis of the

relative performance of the funds with respect to their style benchmarks. Their study found that the

mutual funds generated positive monthly returns on the average, during the study period of January 2000

through June 2005. The ELSS funds lagged the Growth funds or all funds taken together, with respect to

returns generated. The mean returns of the growth funds or all funds were not only positive but also

significant. The ELSS funds also demonstrated marginally higher volatility (standard deviation) than the

Growth funds.

One study8 identified differences in characteristics of public-sector sponsored & private-sector sponsored

mutual funds find the extent of diversification in the portfolio of securities of public-sector sponsored and

private-sector sponsored mutual funds and compare the performance of public-sector sponsored and

private-sector sponsored mutual funds using traditional investment measures. They primarily use Jensen’s

alpha, Sharpe information ratio, excess standard deviation adjusted return (eSDAR) and find out that

portfolio risk characteristics measured through private-sector Indian sponsored mutual funds seems to

have outperformed both Public- sector sponsored and Private-sector foreign sponsored mutual funds and

the general linear model of analysis of covariance establishes differences in performance among the three

classes of mutual funds in terms of portfolio diversification.

Another study9 examined the risk-adjusted performance of open-end mutual funds which invest mainly in

German stocks using Jenson’s measure and Sharpe’s measure. The study finds out that the rates of return

of the mutual funds and the rates of return of the chosen benchmark both must include identical return

components. Either both must include dividends or exclude them. The performance estimates are not very

sensitive with respect to the benchmark choice. When we look at an investment strategy in which the

investment in a specific fund has the same risk as the chosen benchmark, the average underperformance is

small when we weight the individual fund returns equally. The average performance is neutral, when we

weight the individual fund returns according to fund size, measured by assets under management.

7 Prof. Banerjee, Ashok et. Al (2007),”Performance Evaluation of Indian Mutual Funds vis-à-vis their style benchmarks”, www.ssrn.com, paper no.962827 and PP.1-188 Panwar,Sharad and Dr. Madhumathi (2006), “Characteristics and performance evaluation of selected mutual funds in India”, www.ssrn.com, paper no.876402 and PP. 1-199 Stehle,Richard and Grewe,Olaf (2001), “Long-Run Performance of German Stock Mutual Funds”, www.ssrn.com, paper no.271452 and PP. 1-32

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One more paper10 analyzed whether it was more appropriate to apply a factor-based or a characteristic-

based model - both known as benchmarks in portfolio performance measurement using the Linear model,

asset pricing model and Fama and French factors. The study showed that if information on returns was

used and a linear model was proposed that adjusted return to a set of exogenous variables, then the right

side of the equation reported the achieved performance and the passive benchmark that replicated the

style or risk of the assessed portfolio. While, a factor model utilizes a replicate benchmark with short

positions implicitly symmetrical to the long positions. Performance of Russell indexes was analyzed by

applying various factor models, constructed from the indexes themselves, and other models that use the

indexes directly as benchmarks; the presence of biases was detected. Therefore, according to the

empirical findings, selection of exogenous variables that define the replicate benchmark would appear to

be more relevant than the type of model applied.

Another study11 aimed at analyzing performance of select open-ended equity mutual fund using Sharpe

Ratio, Hypothesis testing and return based on yield. The most important finding of the study had been that

only four Growth plans and one Dividend plan (5 out of the 42 plans studied) could generate higher

returns than that of the market which is contrary to the general opinion prevailing in the Indian mutual

fund market. Even the Sharpe ratios of Growth plans and the corresponding Dividend plans stand

testimony to the relatively better performance of Growth plans. The statistical tests in terms of F-test and

t-Test further corroborate the significant performance differences between the Growth plans and Dividend

plans.

Another study12 investigated mutual fund performance using a survivorship bias controlled sample of 506

funds from the 5 most important mutual fund countries using Carhart (1997) 4-factor asset-pricing model.

The study revealed a preference of European funds for small and high book-to-market stocks (value).

Secondly, it showed that small cap mutual funds as an investment style out-performed their benchmark,

even after control for common factors in stock returns. Finally 4 out of 5 countries delivered positive

aggregate alphas, where only UK funds out-performed significantly.

10 Carlos,Juan (2005), “Portfolio Performance: Factors or Benchmarks?”, www.ssrn.com, paper no.760204 and PP. 1-2611 Rao,D.N (2006), “Investment styles and Performance of Equity Mutual Funds in India”, www.ssrn.com, paper no. 922595 and PP. 1-3012 Otten,Rogér and Bams,Dennis, “European Mutual Fund Performance”, www.ssrn.com, paper no.213808 and PP. 1-42

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One more study13 looked at some measures of composite performance that combine risk and return levels

into a single value using Treynor’s ratio, Sharpe’s ratio, Jenson’s measure. The study analyzed the

performance of 80 mutual funds and based on the analysis of these 80 funds, it was found that none of the

mutual funds were fully diversified. This implied there is still some degree of unsystematic risk that one

cannot get rid of through diversification. This also led to another conclusion that none of those funds

would land on Markowitz’s efficient portfolio curve.

Another paper14 aimed to evaluate if mutual fund managers exhibit persistently superior stock selection

skills over a short-horizon of one year using risk-adjusted abnormal returns (RAR), One-factor capital

asset pricing model or CAPM three-factor, Fama-French model, Four-factor Carhart model. Their study

demonstrated that short-term persistence in equity mutual funds performance does not necessarily imply

superior stock selection skills. Common factors in stock returns explained some of the abnormal returns

in top ranking mutual fund schemes. Only the winner portfolios sorted on four-factor alphas' provided an

annual abnormal return of about 10% on post-formation basis using daily data. The short-term persistence

results were much better when daily data was used rather than monthly observations, thus implying that

data frequency does affect inferences about fund performance.

A similar study15 examined the empirical properties of performance measures for mutual funds using

Simulation procedures combined with random and random-stratified samples of NYSE and AMEX

securities and other performance measurement tools employed are Sharpe measure, Jensen alpha, Treynor

measure, appraisal ratio, and Fama-French three-factor model alpha. The study revealed that standard

mutual fund performance was unreliable and could result in false inferences. In particular, it was easy to

detect abnormal performance and market-timing ability when none exists. The results also showed that

the range of measured performance was quite large even when true performance was ordinary. This

provided a benchmark to gauge mutual fund performance. Comparisons of their numerical results with

those reported in actual mutual fund studies raised the possibility that reported results were due to

misspecification, rather than abnormal performance. Finally, the results indicated that procedures based

on the Fama-French 3-factor model were somewhat better than CAPM based measures.

13 Wolasmal,Hewad, “Performance evaluation of mutual funds”, published by Econ WPA, paper no. 0509023 and PP. 1-2014 Prof. Sehgal,Sanjay and Jhanwar,Manoj (2007),”Short-Term Persistence In Mutual Funds Performance: Evidence From India”, www.ssrn.com, paper no.962829 and PP. 1-2315 Kothari,S.P. and Warner,Jerold (1997), “Evaluating Mutual Fund Performance”, www.ssrn.com, paper no.75871 and PP. 1-46

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One more paper16 evaluated whether or not the selected mutual funds were able to outperform the market

on the average over the studied time period. In addition to that by examining the strength of

interrelationships of values of PCMs for successive time periods , the study also tried to infer about the

extent to which the future values of fund performance were related to its past by using single index

model. The study revealed that there were positive signals of information asymmetry in the market with

mutual fund managers having superior information about the returns of stocks as a whole. PCM also

indicated that on an average mutual funds provided excess (above-average) return, but only when unit of

time period was longer (1 qtr or 4 qtr). Therefore, they concluded that for assessing the true performance

of a particular mutual fund, a longer time horizon is better.

Another study17 examined the effect of incorporating lagged information variables into the evaluation of

mutual fund managers’ performance in Indian context with the monthly data for 89 Indian mutual fund

schemes using Treynor - Mazuy Model, Merton-Henriksson Model. The study revealed the use of

conditioning lagged information variables causing the alphas to shift towards the right and reducing the

number of negative timing coefficients, though it could not be concluded that alphas of conditional model

were better compared to its unconditional counterpart as they were not found to be statistically

significant. The noticeably different results of the unconditional timing models vis-à-vis conditional

timing models testified superiority of the model

One more study18 talked about a 4-step model for selecting the right equity fund and illustrated the same

in the context of equity mutual funds in Saudi Arabia. The 4 step model was as follows:

1. Compare returns across funds within the same category.

2. Compare fund returns with the returns of benchmark index.

3. Compare against the fund’s own performance.

4. Risk-related parameters : as indicated by the Standard Deviation (SD) and risk-adjusted returns as

calculated by the Sharpe Ratio (SR).

The study revealed that most of the funds invested in Arab stocks had been in existence for less than a

year and the volatility of the GCC stock markets contributed to the relatively poor performance of these

16 Bhattacharjee,Kaushik and Prof. Roy,Bijan (2006), “Fund Performance Measurement Without Benchmark - A Case Of Select Indian Mutual Funds”, www.ssrn.com, paper no.962035 and PP. 1-1017 Roy,Bijanand and Deb,Saikat (2003), “The Conditional Performance of Indian Mutual Funds- An Empirical Study”, www.ssrn.com, paper no.593723 and PP. 1-2418 Rao,D.N. (2006), “4 Step model to evaluate performance of Mutual Funds in Saudi Arabia” www.ssrn.com, paper no.946937 and PP. 1-16

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funds and the turnaround of these funds could take place only with the rallying of GCC and other Arab

markets. Out of the six categories of equity mutual funds in Saudi Arabia discussed above, Funds

invested in Asian and European stocks were more consistent in their performance and yielded relatively

higher returns than other categories, though funds invested in Saudi stocks yielded higher 3-year returns.

Given the future outlook of Asian economies, particularly China and India and the newly emerging

economies such as Brazil and Russia, funds invested in the stocks of these countries are likely to continue

their current performance in near future.

One more paper19 studied the performance and portfolio characteristics of 828 newly launched U.S. equity

mutual funds over the time period 1991-2005 using Carhart (1997) 4-factor asset-pricing model. Their

study revealed new U.S. equity mutual funds outperformed their peers by 0.12% per month over the first

three years. However, there were distinct patterns in this superior risk-adjusted performance estimated

using Carhart’s (1997) 4-factor model. The number of fund that started to outperform older funds shrunk

substantially after one to three years. These results suggested that the initially favorable performance was

to some extent due to risk taking and not necessarily superior manager skill. Scrutinizing the returns

further confirmed that the returns of fund started to exhibit higher standard deviations and higher

unsystematic risk that could not be explained by the risk exposure to the four factors of the Car hart

model.

Another paper20, analyzed the Indian Mutual Fund Industry pricing mechanism with empirical studies on

its valuation. It also analyzed data at both the fund-manager and fund-investor levels. It stated that

mispricing of the Mutual funds could be evaluated by comparing the return on market and return on

stock. During the pricing period, if the return on stock is negative, then it indicates overpricing and if are

positive indicates under pricing. Relative performance measurement was used to measure the

performance of the MF with SENSEX and it used Standard Deviation, Correlation analysis, Co-efficient

of Determination and Null Hypothesis. This study revealed that standard deviations of the 3-month

returns were significant with the increase in the period. The Standard Deviation increase indicated higher

deviations from the actual means. The variance and coefficient of variation (COV) were also significant.

Variance increases in the later periods indicated higher variability in the returns. As the time horizon

increased COV decreased implying value are less consistent as compared to small duration of

investments.

19 Karoui,Aymen and Meier,Iwan (2008), “Performance and Characteristics of Mutual fund”, www.ssrn.com, paper no.1313284 and PP. 1-3720Agrawal,Deepak (2007), “Measuring Performance of Indian Mutual funds”, www.ssrn.com, paper no.1311761 and PP. 1-17

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One more study21, provided extensive evidence on portfolio characteristics of mutual funds and studied

the relation between fund performance and the fund manager's investment strategy using both the

traditional unconditional alpha model, as in Jensen (1968), and the conditional alpha, following Ferson

and Schadt (1996). The study showed that a weak negative relation exists between performance and past

stock returns in the portfolio. Investing in value stocks could help to improve overall performance. It also

showed that mutual funds with a more diversified portfolio performed somewhat better than funds with a

less diversified portfolio. However, diversification could be achieved by extending the funds' investment

universe and investing in non-listed stocks. Elton, Gruber, Das and Hlavka (1993) showed that funds

investing in these types of assets could achieve superior performance simply because these assets were

not captured within the benchmark model. This paper, however, found no evidence to indicate that

investment outside the fund's primary investment universe would enhance performance. Moreover, the

effects of cash holdings on performance were explored, and some weak evidence suggested that large

cash holdings implied better tactical decisions.

Another paper22 examined the performance of equity and bond mutual funds that invested primarily in

the emerging markets using Treynor’s ratio, Sharpe’s ratio, Jensen’s measure. With this research they

found that on an average the U.S. stock market outperformed emerging equity markets but the emerging

market bonds outperformed U.S. bonds. They also found that overall emerging market stock funds under-

performed the respective MSCI indexes. These were evident by their lower return, higher risk, and thus

lower Sharpe ratios.

One more paper23 studied the performance of mutual funds around the world using a sample of 10,568

open-end actively managed equity funds from 19 countries using different models, mainly, domestic

market model, international market model, Carhart (1997) domestic four-factor model, Carhart (1997)

international four-factor model. With the help of this research they came to a conclusion that the funds

size was positively related with fund performance. Larger funds performed better suggesting the presence

of significant economies of scale in the mutual fund industry worldwide. This conclusion is consistent

among domestic and foreign funds, and in several other robustness tests. Fund age is negatively related

with fund performance indicating that younger funds tend to perform better. This finding seemed mainly

21Engström,Stefan (2004), “Investment Strategies, Fund Performance and Portfolio Characteristics”, www.ssrn.com, paper no.520442 and PP. 1-2922 Ahmed,Parvez; Gangopadhyay, Partha & Nanda, Sudhir (2001), “Performance of Emerging Market Mutual Funds”, www.ssrn.com, paper no.289278 and PP. 1-4123 Ferreira, Miguel A.; Miguel, António F.; Ramos, Sofiann (2006), “The Determinants of Mutual Fund Performance: A Cross-Country Study”, www.ssrn.com, paper no.947098 and PP. 1-58

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driven by the samples of foreign and U.S. funds. When investing abroad, young mutual funds seemed to

offer investors higher returns.

Data:

For the purpose of this study, out of 46 fund houses available in India, 21 Funds across 5 fund houses

have been selected. On the basis of the highest AUM (assets under management) 24; these 5 fund houses

were selected. All the funds were selected by simple random sampling. First the sample size was 30, but

because of the non availability of data for 9 funds, only 21 funds were considered for the study. All the

funds selected for the study are open-ended equity funds under the growth option. The Net Asset Values

(NAV) for all the 21 funds are from March 2004 to March 2009, which is the period of this study.

Since, all these are equity funds, the BSE Sensex (Bombay Stock Exchange Sensitive Index); which is the

oldest, most widely and commonly used benchmark index in India; has been considered as the benchmark

index. The funds selected for this study can be found in Annexure - appendix 1.

Research Methodology:

The funds which have been evaluated for this study have been randomly selected from the Indian fund

houses like Reliance, Birla, UTI, HDFC, and ICICI. The data, which is the weekly NAV’s (Net Asset

Value), of the selected fund was collected from Reuters.

To compare the funds with a market index the BSE Sensex was selected for the only reason that it is

India’s most widely and commonly used Benchmark index. The weekly NAV’s and the Sensex closing

24 As on April 21, 2009. AUM which is assets under management refers to the total assets managed by a fund. It is often used as a measure of comparison vis-à-vis competitors.

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were collected over a period of 5 years. The NAV’s and the Sensex closing were then divided into 32

periods with 8 weekly NAV’s (on an average) in each group.

After this the returns were calculated for both the funds and the BSE Sensex. Once the grouping of

weekly NAV’s of the funds and the BSE Sensex were done the average return, standard deviation, and

absolute returns were calculated both for Fund NAV’s and the Sensex closing. These calculations were

done for each group for all the 21 funds.

Hierarchical Clustering:

For the purpose of this study we have used agglomerative hierarchical clustering, which is a method

which builds a hierarchy of clusters using a bottom up approach, wherein it starts with a single cluster and

then merges a pair of cluster as it moves up the hierarchy.

For the purpose of clustering, an appropriate metric should be used and for this study, Euclidean distance

method is used. This is a metric which is an ordinary distance between and two given points on a scale

and can be measured by a ruler, proven by the Pythagoras theorem.

This can be represented by the following formula:

These results are then graphically represented using a dendogram, which an arrangement of clusters

obtained from hierarchical clustering.

Hypothesis Testing:

It is a method of making statistical decisions using experimental data. For this study, we have 21 funds

with a 5 year weekly data, which is divided into 32 periods which effectively gives us 32 average returns

and 32 absolute returns for the period. The main purpose of this exercise is to obtain significant sample

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size in order to conduct a non-parametric Mann-Whitney U-Test which was proposed by Mann and

Whitney (1947). This kind of hypothesis testing is used on samples which are not normally distributed

and since the sample used for the purpose of this study is not normally distributed, we have used the

Mann-Whitney U-Test.

Mann-Whitney U-Test for Average Returns:

For the purpose of this study, hypothesis is used to test the changes in the average returns over the given

32 periods and compare these average returns with the BSE Sensex returns for the same period, to

conclude whether the average returns of the fund and the benchmark index are the same.

The U-test can be represented in an equation as per the below:

Where,

n1 and n2 = sample size of the mutual fund and BSE Sensex index.

The following formula is used to compute the Z value:

Where,

U = U value,

mu = mean of the U values and

σu = standard deviation of the U values.

On the basis of the above inputs, the U-test hypothesis is established as per below:

H0: x1 = x2

Ha: x1 ≠ x2

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x1 = Mean returns for the BSE Sensex Index.

x2 = Mean returns for the Mutual Fund.

Mann-Whitney U-Test for Absolute Returns:

For the purpose of this study, hypothesis is used to test the changes in the absolute returns over the given

32 periods and compare these absolute returns with the BSE Sensex returns for the same period, to

conclude whether the absolute returns of the fund and the benchmark index are the same.

U-test hypothesis is as per below:

H0: x1 = x2

Ha: x1 ≠ x2

Where,

x1 = Absolute returns for the Base Sensex Index.

x2 = Absolute returns for the Mutual Fund.

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Data analysis and Interpretation:

Returns:

Returns are the yield that an asset generates over a period of time. It is the percentage increase or decrease

in the value of the investment over a period of time.

In this study the fund returns and the Sensex returns have been calculated for each of the period.

There are 21 funds with a 5 year weekly data, which is divided into 32 periods which effectively gives us

32 betas and 32 average returns for the period. The main purpose of this exercise is to obtain significantly

large sample size in order to conduct a non-parametric Mann-Whitney U-Test.

The fund returns for each of the period were calculated as follows:

Current NAV – Previous NAV x 100

Previous NAV

The BSE Sensex returns were calculated as follows:

Current Closing – Previous Closing x 100

Previous Closing

Average Returns:

Average return is the simple average of the returns generated by an asset. In this study daily average

return of both the Sensex and the funds were calculated for each of the 32 periods.

21

Average returns of the BSE Sensex returns and the fund’s returns have been calculated with this formula:

Where, = average return,

n = number of weeks in the period,

x1 – xn = return of the corresponding week

In the data collected for the study, the selected mutual funds have given average returns in varying

degrees. During late 2004, funds posted average returns in the range of 0.50% - 2.75% while markets in

the same period gave average returns of 0.69%. Similar average returns were seen in late 2005 and early

2006 when markets went up significantly. However, with the fall in markets in mid 2006, negative

average returns were seen. Average returns posted by these funds were in the range of -1.7% to -3.75%

while markets had returns of roughly -2%. Beginning of 2008 and onwards faced worse returns to the

extent of -6% by funds and similar returns by markets. On the whole, mutual funds provided average

returns in the same range as markets with the exception of certain time periods as represented in Table 1

and Table 2 in the Appendix 2.

The average returns of the funds are not significantly different over the period, this has been proved by

conducting a Mann Whitney U-test on the average returns of the 21 funds and with 95% confidence we

can conclude that the average returns of the funds were not significantly different from the average

returns of the BSE Sensex index. This study shows that although the markets slumped in the later half of

the 2nd period, the gains out of the bull run in the 1st half where the average returns for these funds were

in the range of 0.5% to 2.75% of the 2nd period offsets the losses where the average returns of these

funds were in the range of -1.7% to -3.75%, and hence the overall returns in the 1st period and the 2nd

period are quite similar.

Absolute Returns:

22

After analyzing the average returns a clears no conclusion could be drawn hence absolute return were

calculated to give a clearer indication of the returns generated. Absolute Returns refers to the returns that

an asset achieves over a period of time. It measures the percentage appreciation or depreciation in the

value of an asset over a certain time frame.

The absolute returns of the BSE Sensex returns and the fund returns were calculated as follows:

Return of the last week – Return of the first week x 100

Return of the first week

Absolute return measures the appreciation or fall in the fund’s performance as a percentage of the initial

invested amount. These returns were compared to the benchmark index to in order to ascertain the extent

to which the portfolio has outperformed / underperformed in relation to the index. Typically there should

be a low correlation between the fund’s performance and the index (refer), as the fund is expected to

outperform and deliver positive absolute return vis-à-vis index.

Form the analysis in appendix 3 Table 3 and 4, it can be noted that mutual funds have delivered varying

returns over different time periods. During the last quarter of 2004, mutual funds delivered impressive

returns. On an average the selected mutual funds had returns of approximately 10% whilst markets gave

returns of around 6% during the same period. A similar phase was witnessed in mid 2005 where on an

average funds gave returns of 13% and markets posted returns on the same lines. During 2006 and 2007

funds gave comparable returns to the previous years but this time around the index outperformed the

funds significantly.

The absolute returns of the funds till the end of 2007 was in the range of 10% to 13% and the absolute

returns of the BSE Sensex in the same period ranged from 6% to 17%, in the period between 2004 to end

of 2005 the funds have managed to outperform the BSE Sensex, however, we observe that in the period

between 2006 to end of 2007 the funds have significantly underperformed compared to the BSE Sensex.

However, there was massive slump in the period of September 2008 to October 2008, during which the

funds returns fell to -35% as compared to BSE Sensex returns of -40%. This study shows the correlation

in the absolute returns of the funds and the BSE Sensex and shows us that in the long-run the absolute

returns of the fund and index are quite similar as represented in Table 3 and Table 4 in the appendix.

23

Hence it can be seen, that on the whole, it can be concluded that in terms of absolute returns, funds have

been performing in line with markets. However, the extent of the impact and movement has been lesser or

more in relation to markets in certain periods.

Standard Deviation:

Standard Deviation is a tool which measures the variability of the data set. It is the square root of the

square of the mean deviations from the arithmetic mean of a data series. It is calculated to measure the

riskiness of a fund, stock or portfolio. Higher the standard deviation means higher the risk and higher the

returns of the asset and a low standard deviation mans that the asset is less risky and will generate less

returns.

The standard deviation of the fund returns and the BSE Sensex returns were calculated with the following

formula:

Where, s = Standard Deviation,

N = number of weeks in the period,

= mean of the period,

xi = return of the corresponding week.

Standard deviation which measures variability and extent of dispersion from data, expresses the volatility

of the fund. It mainly indicates the risk associated with the given fund.

Form the analysis in appendix 4 table 5 and table 6; it was observed that mutual funds have witnessed

high standard deviation in booming markets. During mid 2004 and mid 2006 Standard deviation is in the

range of 3% - 9%; which is fairly high compared to the market. The markets in the same period had an

average volatility of approximately 2%. This shows that during these periods, funds were more volatile

compared to the other time periods. This shows that the risk associated with these funds were much

higher during these periods compared to the market.

24

This also meant that since the mutual funds were having much higher risks and volatility; they were

susceptible to high returns also. During this period, standard deviation in the range of 1% - 14 % was

seen. However, with the fall of markets in 2008 and recession beating down the markets, returns

collapsed and the funds posted negative returns. Standard deviation marginally came down and is

currently hovering in the range of 2% - 6.5%.

The standard deviation of the fund returns were significantly high during the 2007 to 2008 period when

the BSE Sensex moved up sharply from 12000 levels in March 2007 to 21000 levels in December 2007,

here the standard deviation moved up sharply from the 3% to 8% levels to 3% to 14% levels. This trend

was observed in the period from January 2008 to June 2008 when the BSE Sensex plummeted from the

21000 levels to 13000 levels, this shows that sudden rise or fall in the markets result in the similar

movement in the standard deviation of the fund returns.

Regression:

Regression is a statistical tool to analyze the fund returns with respect to the market returns to calculate

the fund beta and the R squared value. Here the fund returns are the dependent variables and the market

returns are the independent variables. The regression Equation is as follows.

Y = a + bx + c

Where, Y = dependent Variable

X = independent variable

a = y – intercept of the line

b = slope of the regression line

c = residual value.

With the help of this the fund beta is calculated. Beta is the measure of volatility of a stock, fund,

portfolio, etc with respect to the market. If the beta is positive then the fund returns are directly

proportional to the market returns and if the beta is negative then the fund returns are inversely

proportional to the market.

25

Beta of a fund is calculated with the following formula:

Where, βa = fund beta

Cov (ra,rp) = covariance of the returns of the fund and the market,

Var rp = variance of the market returns.

The beta of the portfolio expresses how the expected return of the mutual fund is correlated with the

returns of the markets in the given period.

The study takes into consideration each beta of the 32 periods of 21 funds, here the average betas of 20

funds is in the range of 0.6 to 0.9 and for one fund the average beta exceeds 1 as per appendix 5 in Table

7 and Table 8. This shows that there is a significant level of correlation in the returns of the funds as

compared to BSE Sensex index and that most the funds have performed as much or near the market

performance.

Overall it can be concluded that from the data collected for the study, most of the funds are sensitive to

the market and have given returns as much as the market has or near the market returns.

Residual Value:

Using the regression equation and the regression analysis the ‘c’ value or the residual value has been

calculated for all the 32 periods for each of the 21 funds.

The residual value shows that how much portion of the return can be attributed to the fund or the

portfolio and how much is the attributed to the market. Residual value shows what percentage of return is

independent of the market and is that because of the fund properties.

26

The residual value for each of the 21 funds for all the 32 periods is coming up to 0. So it can be inferred

that the funds are responding to the markets only. And the funds returns cannot to attributed to the fund

properties or the fund components. This is true for all the funds during each of the 32 periods.

Relative Performance Index:

The Relative Performance Index for the sample size has been computed. This is calculated to show how

each fund has performed in relation to the market. Here, we take the market index as the BSE Sensex

Index.

On the basis of the RPI analysis, we graded the funds as:

Under-performers (X<=0.7),

Par-performers (0.8<=X<=1.1) and

Over-performers (X>=1.2)

Relative Performance Index has been calculated for all the funds. It has been calculated with the

following formula:

(Current NAV-Beginning Period NAV) / Beginning Period NAV___

(Current BSE – BSE at Beginning Period) / BSE at Beginning Period

This is calculated to show how each fund has performed in relation to the market. BSE Sensex has been

taken as the market index. The following observations were made in this study as seen in appendix 6

Table 9:

There were a total of 7 funds that gave a return that was lower than the market return over the 5

year period and hence had a RPI of less than 0.7

There were a total of 3 funds that gave approximately the same return as the market return over

the 5 year period.

The remaining 11 funds gave a return in excess of the market return over the 5 year period and

hence they all have a RPI of over 1. This shows that some fund managers were able to diversify

27

the risks and generate an overall positive return even after over a year long bear market run from

January 2008 onwards.

Mann-Whitney U-Test for Average Returns:

To measure the performance of the mutual fund a U-test has been conducted on the average returns of the

mutual funds and the BSE Sensex index. For the purpose of this study, hypothesis is used to test the

changes in the average returns of the fund and the BSE Sensex Index over the given 32 periods, to

conclude whether the average returns of the fund and the BSE Sensex Index are the same.

In this study each fund has 32 average returns and these average returns are then compared to the returns

of the BSE Sensex Index, hypothesis is used to test the changes in the average returns over the given 32

periods and compare these average returns with the BSE Sensex returns for the same period, to conclude

whether the average returns of the fund and the benchmark index are the same. The null hypothesis is

accepted if the average returns of the two are same. If not then the null hypothesis is rejected.

H0: x1 = x2

Ha: x1 ≠ x2

On conducting the U-Test for the 32 average returns for each fund the following was observed as per the

appendix7.

At 95% confidence interval, the significance level for 20 funds is more than 0.05, which helps us accept

the null hypothesis, which says that the average returns of the funds over the tested two periods are

similar.

One fund in particular, UTI CCP growth fund, has a significant value of 0.003 which is less than 0.05.

This shows that for UTI CCP growth fund the null hypothesis is rejected; that the fund returns are similar

to the market returns.

UTI CCP growth fund has given returns which are not similar to the market returns given over the period

of 5 years which have been considered for this study. UTI CCP growth fund has given an average return

of 0.0058% where as the BSE Sensex during the same 5 year period has given an average return of

0.2919%, which is significantly higher than the return given UTI CCP growth fund.

28

Mann-Whitney U-Test for Absolute Returns:

For the purpose of this study, hypothesis is used to test the changes in the absolute returns of the fund and

the BSE Sensex Index over the given 32 periods, to conclude whether the absolute returns of the fund and

the BSE Sensex Index are the same.

In this study each fund has 32 absolute returns and these absolute returns are then compared to the returns

of the BSE Sensex Index, hypothesis is used to test the changes in the absolute returns over the given 32

periods and compare these absolute returns with the BSE Sensex returns for the same period, to conclude

whether the absolute returns of the fund and the benchmark index are the same. The null hypothesis is

accepted if the absolute returns of the two are same. If not then the null hypothesis is rejected.

On conducting the U-Test for the 32 average returns for each fund the following was observed as per the

appendix 8.

At 95% confidence interval, the significance level for 20 funds is more than 0.05, which helps us accept

the null hypothesis, which says that the average returns of the funds over the tested two periods are

similar.

One fund in particular, UTI CCP growth fund, has a significant value of 0.006 which is less than 0.05.

This shows that for UTI CCP growth fund the null hypothesis is rejected; that the fund returns are similar

to the market returns.

By running the Mann-Whitney U-test on the Average returns as well as Absolute returns of the BSE

Sensex Index and the average returns confirms the hypothesis that at 95% confidence, 20 out of the 21

funds have returns quite similar to the returns of the BSE Sensex Index. Also, the UTI CCP growth is one

common outlier which has generated significantly lower returns as compared to the benchmark index.

Hierarchical Clustering:

Hierarchical Clustering has been done for all the funds considered in this study. Clustering has been done

on the basis of different properties which are, Average Returns, Absolute Returns, Standard Deviation,

Beta, R Squared, and Relative Performance Index.

29

With the help of the agglomeration schedule table 10 appendix 9 the clusters of mutual funds were

formed. The graphical representation of the clusters formed can be seen in the form of a dendogram

figure1, appendix 9. Birla Sun Life Advantage Fund, UTI Master Equity Plan and HDFC Top 200 Fund,

form one cluster. Another cluster is being formed by ICICI Prudential Power, ICICI Prudential Growth

fund , UTI Master Index Fund and ICICI Prudential Ind. These clusters are formed because they are

closely related to each other and the variables values that they have with each other are more or less the

same. Birla Sun Life Midcap, ICICI Prudential Tax, HDFC Equity Fund-Growth, Reliance Vision Fund,

HDFC Growth Fund-Growth, Birla Sun Life Equity, Birla Sun Life Buy and HDFC Long Term

Advantage have again been clustered into similar groups.

Findings and Conclusions:

The study done on the performance evaluation of Indian mutual funds was fruitful as all the objectives of

the study were successfully achieved. The following are the findings from this study.

The selected for the study gave returns in synchronization with the markets. When there was

boom in the stock market the funds gave positive returns a little more than what the market had

given. During the recessionary phase the markets declined steadily and so did the fund returns.

Overall the fund returns and the market returns, for the period of 5 years taken into consideration

for this study, was the more or less same with a very nominal difference in them.

30

The performance of the funds were different from each other, though a few firm had common

attributes which can be seen from the clusters that they make, a few funds didn’t fall into any

cluster at all. One such fund UTI CCP Advantage Fund was an outlier and gave returns very less

than the market and also when compared to the other funds.

It can be easily concluded that most of the fund returns can be attributed to the market that is

they were in direct correlation with the market. But in the sample of 21 funds considered for this

study one fund; UTI CCP Advantage Fund; didn’t perform as the market and for this fund the

returns generated cannot be attributed to the market. The performance of this fund can be

attributed to both the market and as well as the fund composition and properties.

Limitations of the Study:

Since the funds selected for this study were open ended equity based growth mutual funds the

fund composition kept on changing over the time period, so it became difficult to understand the

fund properties as historical data pertaining to the fund composition was not available.

Because of unavailability of historical data and fund composition it was difficult to ascertain the

performance to the fund properties and a simple evaluation was done against the market

performance.

31

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PP.1-37

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32

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33


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Annexure

Appendix 1

The list of Funds selected for the study is:

Birla Sun Life India Opportunities Fund - Growth

Birla Sun Life Advantage Fund-Growth

Birla Sun Life Equity Fund-Growth

Birla Sun Life Midcap Fund-Growth

Birla Sun Life Buy India Fund-Growth

UTI Mastershare-Income

UTI CCP Advantage Fund-Growth

UTI Master Index Fund-Growth

UTI Energy Fund-Income

UTI MNC Fund-Income

34

UTI Master Equity Plan Unit Scheme

ICICI Prudential Power Plan-Growth

ICICI Prudential Tax Plan-Growth

ICICI Prudential Index Fund

ICICI Prudential Growth Plan-Growth

HDFC Equity Fund-Growth

HDFC Long Term Advantage Fund-Growth

HDFC Growth Fund-Growth

HDFC Top 200 Fund-Dividend

Reliance Growth Fund-Growth Plan

Reliance Vision Fund-Growth

Appendix 2

35

Table 1: Average Returns for the period ending from 14th May, 2005 to 1st September, 2006

Table 2: Average Returns for the period ending from 27th September, 2006 to 13th February, 2009

36

Appendix 3

Table 3: Absolute Returns for the period ending from 14th May, 2005 to 1st September, 2006

Table 4: Absolute Returns for the period ending from 27th September, 2006 to 13th February, 2009

37

Appendix4

Table 5: Standard deviation of returns for the period ending from 14th May, 2005 to 1st September, 2006

Table 6: Standard deviation of returns for the period ending from 27th September, 2006 to 13th February,

2009

38

Appendix 5

Table 7: Betas for the period ending from 14th May, 2005 to 1st September, 2006

Table 8: Betas for the period ending from 27th September, 2006 to 13th February, 2009

39

Appendix 6

Relative Performance Index:

Table 9: Relative Performance Index

40

Appendix 7

RanksTest Statistics

Name NMean Rank

Sum of Ranks

Avg. returns

Birla Sun Life Advantage Fund-Growth

32 32.06 1026.00

BSE Sensex Returns

32 32.94 1054.00

Total 64

Ranks Test Statistics

Name NMean Rank

Sum of Ranks

Avg. returns


32 32.38 1036.00

BSE Sensex Returns

32 32.63 1044.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns


32 33.78 1081.00

BSE Sensex Returns

32 31.22 999.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

Birla Sun Life India Opportunities Fund-Growth

32 30.03 961.00

BSE Sensex Returns

32 34.97 1119.00

Avg. returns

Mann-Whitney U 498.000Wilcoxon W 1026.000Z -.188Asymp. Sig. (2-tailed)

.851

Avg. returns


.957

Avg. returns


.582

Avg. returns

Mann-Whitney U 433.000Wilcoxon W 961.000Z -1.061Asymp. Sig. (2-tailed)

.289

41

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns


32 33.59 1075.00

BSE Sensex Returns

32 31.41 1005.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 32.13 1028.00

HDFC Equity Fund-Growth 32 32.88 1052.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 32.00 1024.00


32 33.00 1056.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 33.03 1057.00


32 31.97 1023.00

Total 64

Avg. returns


.638

Avg. returns


.872

Avg. returns


.830

Avg. returns


.819

42


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 33.53 1073.00

HDFC Top 200 Fund-Dividend 32 31.47 1007.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 32.50 1040.00


32 32.50 1040.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 32.31 1034.00


32 32.69 1046.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 31.88 1020.00


32 33.13 1060.00

Total 64

Avg. returns


.658

Avg. returns

Mann-Whitney U 512.000Wilcoxon W 1040.000Z .000Asymp. Sig. (2-tailed)

1.000

Avg. returns


.936

Avg. returns

Mann-Whitney U

492.000

Wilcoxon W 1020.000Z -.269Asymp. Sig. (2-tailed)

.788

43


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 31.44 1006.00


32 33.56 1074.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 30.44 974.00


32 34.56 1106.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 31.94 1022.00


32 33.06 1058.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 39.44 1262.00


32 25.56 818.00

Total 64


Avg. returns


.648

Avg. returns


.376

Avg. returns


.809

Avg. returns


.003

44

Name N Mean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 36.13 1156.00


32 28.88 924.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 33.44 1070.00


32 31.56 1010.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 32.56 1042.00


32 32.44 1038.00

Total 64


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 34.47 1103.00


32 30.53 977.00

Total 64


Avg. returns


.119

Avg. returns


.687

Avg. returns


.979

Avg. returns


.398

45

Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 36.03 1153.00

UTI MNC Fund-Income

32 28.97 927.00

Total 64

Mann-Whitney U- Test Results for Average Returns of 21 funds

Appendix 8


Name NMean Rank

Sum of Ranks

Abs. Returns


32 32.94 1054.00

BSE Sensex Returns

32 32.06 1026.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns


32 34.34 1099.00

BSE Sensex Returns

32 30.66 981.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

Birla Sun Life India Opportunities Fund-Growth

32 30.69 982.00

BSE Sensex Returns

32 34.31 1098.00

Total 64

Avg. returns


.129

Abs. ReturnsMann-Whitney U 498.000

1026.000Z -.188Asymp. Sig. (2-tailed)

.851

Abs. ReturnsMann-Whitney U 453.000Wilcoxon W 981.000Z -.792Asymp. Sig. (2-tailed)

.428


.436

46


Name NMean Rank

Sum of Ranks

Abs. Returns


32 34.13 1092.00

BSE Sensex Returns

32 30.88 988.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 31.94 1022.00

HDFC Equity Fund-Growth 32 33.06 1058.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 31.97 1023.00


32 33.03 1057.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 32.56 1042.00


32 32.44 1038.00

Total 64



.485


.809


.819


.979

47

Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 33.25 1064.00

HDFC Top 200 Fund-Dividend 32 31.75 1016.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 32.38 1036.00


32 32.63 1044.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 32.00 1024.00


32 33.00 1056.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 31.84 1019.00


32 33.16 1061.00

Total 64



.747


.957


.830


.778

48

Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 31.88 1020.00


32 33.13 1060.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 30.56 978.00


32 34.44 1102.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 31.75 1016.00


32 33.25 1064.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 38.84 1243.00


32 26.16 837.00

Total 64


Name NMean Rank

Sum of Ranks


.788


.405


.747

Abs. ReturnsMann-Whitney U 309.000Wilcoxon W 837.000Z -2.726Asymp. Sig. (2-tailed)

.006

49

Abs. Returns

BSE Sensex Returns

32 35.56 1138.00


32 29.44 942.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 32.72 1047.00


32 32.28 1033.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 32.69 1046.00


32 32.31 1034.00

Total 64


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 34.56 1106.00


32 30.44 974.00

Total 64


Name NMean Rank

Sum of Ranks


.188


.925


.936


.376

50

Abs. Returns

BSE Sensex Returns

32 35.38 1132.00

UTI MNC Fund-Income

32 29.63 948.00

Total 64

Mann-Whitney U- Test Results for Absolute Returns of 21 funds

Appendix 9

Table 10 : Hierarchical multiple clustering using agglomeration method


.217

51

Figure 1: Dendogram of the hierarchical clustering

52

mba project work - performance evaluation of mutual fund

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