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ARP ReportOn

“Performance Evaluation of Indian Mutual Funds”

Submitted in partial fulfillment of the requirement ofGlobal Masters in Business Administration (GMBA)

Wealth Management and Investment Banking

Submitted by: Under the Guidance of:

Name: Kanchan Chainani Dr. Parvinder AroraRoll No. GDEC08WM028

Name: Rounak JhawarRoll No. GDEC08IB015

Name: Sagar BavishiRoll No. GDEC08WM033

GMBA Batch Dec 08

S P Jain Center of ManagementDubai UAE / Singapore

1

ACKNOWLEDGEMENT

We would like to express our profound gratitude to all those who have been instrumental in the

preparation of this report which has been prepared in partial fulfillment of Global Masters in

Business Administration (GMBA).

We wish to thank our dean, Mr. Michael Barnes, Dr. Seetharaman, Dean, SPJCM Singapore,

Mrs. Vinika Rao, Mr. Parvinder Arora, Mr. Sandeep Chakrobarty, Mr. Uday Bhate, Mr. AVR

Srinivas, Mrs. Suparna Mallya and all the staff and Faculty members of SPJCM for their support

and vision.

We wish to place on record our deep sense of gratitude to Mr. Parvinder Arora a highly

esteemed and distinguished mentor for his expert advice and help.

This project could only be completed with the assistance of Mr. Sandeep Chakrobarty and Mr.

Uday Bhate both having being a valued guide.

Finally we would like to thank our Parents, Family, Friends and God almighty for their unending

inspiration and encouragement.

Place: Singapore Kanchan Chainani

Date: 25.04.2009 Rounak Jhawar

Sagar Bavishi

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DECLARATION

We hereby declare that the matter included in this ARPs report entitled “Performance Evaluation

of Indian Mutual Funds”, is the result of study carried out by us. We further declare that this is

our 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

Global Masters in Business Administration (GMBA) in Wealth Management and Investment

Banking at SP Jain Center of Management, Singapore.

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

Name: Kanchan Chainani

Roll No. GDEC08WM028

Name: Rounak Jhawar

Roll No. GDEC08IB015

Name: Sagar Bavishi

Roll No. GDEC08WM033

GMBA Batch Dec 08

SP Jain Center of Management

10, Hyderabad Road (Dr. Parvinder Arora)

Singapore Project Mentor

3

INDEX

Serial No. TopicPage

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.

DescriptionPage

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 42-47

Appendix 8 Mann-Whitney U-Test of Absolute Returns 47-52

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, 21 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.

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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 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.

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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 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

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

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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 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:

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”

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

funds5 . 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.

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:

5 IBNlive.com under the link markets. Article called “Mutual Funds: The fading star of India”

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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.

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.

6 Dr. Rao, Narayan “Performance Evaluation of Indian Mutual Funds”, www.ssrn.com, paper no.433100 and PP.1-247 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. 1-19

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http://www.ssrn.com/



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.

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

9 Stehle,Richard and Grewe,Olaf (2001), “Long-Run Performance of German Stock Mutual Funds”, www.ssrn.com, paper no.271452 and PP. 1-3210 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. 1-30

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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.

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.

12 Otten,Rogér and Bams,Dennis, “European Mutual Fund Performance”, www.ssrn.com, paper no.213808 and PP. 1-4213 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. 1-23

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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.

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

15 Kothari,S.P. and Warner,Jerold (1997), “Evaluating Mutual Fund Performance”, www.ssrn.com, paper no.75871 and PP. 1-4616 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. 1-24

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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 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

18 Rao,D.N. (2006), “4 Step model to evaluate performance of Mutual Funds in Saudi Arabia” www.ssrn.com, paper no.946937 and PP. 1-1619 Karoui,Aymen and Meier,Iwan (2008), “Performance and Characteristics of Mutual fund”, www.ssrn.com, paper no.1313284 and PP. 1-37

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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.

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

20Agrawal,Deepak (2007), “Measuring Performance of Indian Mutual funds”, www.ssrn.com, paper no.1311761 and PP. 1-1721Engström,Stefan (2004), “Investment Strategies, Fund Performance and Portfolio Characteristics”, www.ssrn.com, paper no.520442 and PP. 1-29

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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 driven by the

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

investors higher returns.

Data:22 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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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 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:

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.

18

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 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:

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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

x1 = Mean returns for the BSE Sensex Index.

x2 = Mean returns for the Mutual Fund.

Mann-Whitney U-Test for Absolute Returns:

20

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.

Data analysis and Interpretation:

21

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.

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

this formula:

22

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:

23

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.

24

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

25

that the risk associated with these funds were much higher during these periods compared to

the market.

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

26

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

proportional to the market.

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.

27

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.

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

28

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 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.

29

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.

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.

30

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.

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.

31

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.

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.

32

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.

33

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34

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35


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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

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

36

Appendix 2

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

37

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

38

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

39

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

40

Appendix 6

Relative Performance Index:

Table 9: Relative Performance Index

41

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

42

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

43


Name NMean Rank

Sum of Ranks

Avg. returns

BSE Sensex Returns

32 33.53 1073.00


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

ICICI Prudential Power Plan-Growth

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 1020.000

Z -.269Asymp. Sig. (2-tailed)

.788

44


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

Avg. returns


.648

Avg. returns


.376

Avg. returns


.809

Avg. returns


.003

45

Total 64


Name NMean 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

Avg. returns


.119

Avg. returns


.687

Avg. returns


.979

Avg. returns


.398

46

Total 64


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

Avg. returns


.129

Abs. Returns

Mann-Whitney U 498.0001026.000

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

.851

Abs. Returns


.428

Abs. Returns


.436

47

BSE Sensex Returns

32 34.31 1098.00

Total 64


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

Abs. Returns


.485

Abs. Returns


.809

Abs. Returns


.819

Abs. Returns


.979

48


Name NMean Rank

Sum of Ranks

Abs. Returns

BSE Sensex Returns

32 33.25 1064.00


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

ICICI Prudential Power Plan-

32 33.16 1061.00

Abs. Returns


.747

Abs. Returns


.957

Abs. Returns


.830

Abs. Returns


.778

49

GrowthTotal 64


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

Abs. Returns


.788

Abs. Returns


.405

Abs. Returns


.747

Abs. Returns


.006

50

Total 64


Name NMean Rank

Sum of Ranks

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

Abs. Returns


.188

Abs. Returns


.925

Abs. Returns


.936

Abs. Returns


.376

51


Name NMean Rank

Sum of Ranks

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

Abs. Returns


.217

52

Table 10 : Hierarchical multiple clustering using agglomeration method

Figure 1: Dendogram of the hierarchical clustering

53

Performanceevaluationofindianmutualfunds 090708154941-phpapp02

Economy & Finance

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