“PERFORMANCE EVALUATION OF SELECTED MUTUAL FUNDS WITHIN THE FRAMEWORK OF RISK AND RETURNS.”

A Project ReportSubmitted to the

UNIVERSITY OF CALICUTIn Partial Fulfillment of the requirement for the award of the

Degree of MASTER OF BUSINESS ADMINISTRATION

Submitted By

DEEPAK.K.DReg. No: JLAKMBA009Under the Guidance of

Mrs. NIMMI.C.R, MBA,

DEPARTMENT OF MANAGEMENT STUDIESJawaharlal College of Engineering & Technology, Lakkidi

Mangalam (p o), Ottapalam, Palakkad -679 301

DEPARTMENT OF MANAGEMENT STUDIES

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Jawaharlal College of Engineering & Technology, LakkidiMangalam (p o), Ottapalam, Palakkad -679 301

DECLARATION

I, Deepak.K.D ,hereby declare that the project report entitled “Performance evaluation of selected mutual funds within the framework of risk and returns.” submitted to the University of Calicut in partial fulfillment of the requirements for the award of the degree of the Master of Business Administration is a record of original work done by me during 01-04-2012 to 15-05-2012 at Capstock securities Ltd Coimbatore., under the guidance of Mrs. Nimmi. C.R , Department Of Management Studies.

I also hereby declare that this project has not been submitted at any time to any other University or institute for the award of any degree/diploma/fellowship or other titles.

Place: Signature

Date:

FORWARDED(Guide)

ADVISOR PRINCIPAL

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DEPARTMENT OF MANAGEMENT STUDIES Jawaharlal College of Engineering & Technology,

Lakkidi Mangalam (p o), Ottapalam, Palakkad -679 301

Dr.M Rajan, MBA, MA, LLB, PhD Date:

CERTIFICATE

This is to certify that this Project report submitted in partial fulfillment of the requirement of the degree of Master of Business Administration of the University of Calicut is a record of Bonafide project work conducted by Mr. Deepak.K.D at Capstock Securities Ltd Coimbatore, under my supervision and guidance and no part of this project report has been submitted earlier for the award of any degree of any University and this report has not been published in part or full in any other magazine or journal.

Signature of the Project Guide

ACKNOWLEDGEMENT

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I take this opportunity to express my gratitude to all persons who have guided and supported me till the successful completion of my Project work.

First and foremost, I thank God for having bestowed his blessing on me to complete this project Work.

It is my privilege and great pleasure to express my sincere and heart full thanks to Adv.P.KRISHNADAS, B.A., L.L.B., MBA, DEM.., Managing Trustee, Nehru Group of Institutions Kerala and Tamilnadu, for giving me the opportunity to study in this prestigious institution and do the project work.

I express my thanks to prof. LASER JOHN, Director of Jawaharlal collage of engineering and technology for the help and valuable support in the completion if the project.

I express my sincere gratitude to Dr.A.S.DEVARAJA. B.E, M.Tec. PhD., HINDI RATNA the Principal of Jawaharlal College of Engineering and Technology, for all facilities extended to me in accomplishing this project work.

I would like to express my thanks to ADVISOR Prof. K.P.C. NAIR, and Prof.Dr.M.RAJAN. LLB. MA. MBA. PhD. for their guidance and help.

I am extremely thankful to Mrs. Nimmi.C.R , MBA of MBA Department, who gave me guidance and suggestions for the project work.

I would like to express my gratitude to Capstock Securities Limited, especially to Mrs Santha (Manager) and all other staffs for their co-operation and providing me the necessary information.

I would like to express my gratitude to all the faculty member of MBA Department for their help and valuable support in the completion of the work.

I extend my profound gratitude to my loving parents, friends as well as my well-wishers whose limitless love, affection, care, prayer and suggestions helped me throughout my project work.

Deepak.K.D

TABLE OF CONTENTS

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CHAPTER NO TITLE PAGE NOChapter 1 1.1 Introduction 1

1.2 Introduction to capital market 2-5

1.3 Statement of the problem 6

1.4 Objective of the study 7

1.5 Research methodology 8-9

1.6 Scope of the study 10

1.7 Limitations of the study 11

Chapter 2 Review of literature 12-40Chapter 3 Company and Industry Profile 41-50Chapter 4 Data analysis and interpretations 51-80Chapter 5 Findings, Suggestions, Conclusions 81-85Chapter 6 Appendix 85-105Chapter 7 Bibliography 106

1.1 INTRODUCTION

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Investment refers to the process of commitment of funds with the

objective of earning additional income or capital appreciation or both. Savings form an

important part of the economy of any nation. With savings invested in various options

available to the people, the money act as driver for growth of the country. Indian financial

scene too presents the multiple avenues to the investors. Though certainly not the best or

deepest of markets in the world, it has ignited the growth rate in mutual fund industry to

provide reasonable options for an ordinary person to invest his savings. Investment goals vary

from person to person. While somebody wants security, others might give more weightage to

returns alone. Somebody else might want to plan for his Child’s education, while somebody

might be savings for life after retirement. With the objectives defying any range, it is obvious

that the products required will vary as well. Today an investor has a lot of investment

alternatives to choose from the market such as shares, debentures, mutual funds, Government

securities etc.

The investors has to make a wise choice keeping in mind various

factors such as objectives of investment, risk associated with the investment, tax benefits,

liquidity ,marketability etc. But it is not an easy task for the investors to identify the right

avenue for investment due to many investment constraints such as lack of resources’ and time

to conduct research etc. Mutual Fund is a trust that pools the savings of a number of investors

who share a common financial goal. The money thus collected invested in capital market

instruments such as shares, debentures and other securities according to funds objectives. The

income earned through these investments and capital appreciations realize are shared by its

unit holders in proportion to the number of units owned by them. Thus a Mutual Fund is the

most suitable investment for the common man as it offers an opportunity to invest in a

diversified professionally managed basket of securities at a relatively low cost.

A mutual fund is the ideal investment vehicle for today’s complex

and modern financial scenario. The concept of mutual funds gained momentum because of

the increasing complexities of the capital market. It is difficult for individual investors to

create his portfolio of investments, due to the lack of knowledge and experience about the

stock market. Mutual fund provides the benefit of diversification to unit holders as a result of

which risk of investment gets minimised.

1.2 INTRODUCTION TO INDIAN CAPITAL MARKET

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Capital is often defined as  “wealth used in the production of further

wealth.” In simple words, it comprises the money value invested in a business unit. Market is

that place where buyer and sellers are contact to each other and when these two words are

merging together make capital market. A business enterprise can raise capital from various

sources long-term funds can be raised either through issue of securities or by borrowing from

certain institutions. Short-term funds can also be borrowed from various agencies. Thus

business units can raise capital from issue of securities or by borrowings (long-term and

short-term).The borrowers and lenders are brought together through the financial markets.

The term ‘financial market’ collectively refers to all those organizations and institutions

which lend funds to business enterprises and public authorities.

A capital market is a market for securities (both debt and equity),

where business enterprises (companies) and governments can raise long-term funds. It is

defined as a market in which money is lent for periods longer than a year, as the raising of

short-term funds takes place on other markets (e.g., the money market). The capital market

includes the stock market (equity securities) and the bond market (debt).

GROWTH OF CAPITAL MARKET IN INDIA

Government securities market

Since 1991, the investor base for government securities has expanded rapidly. Besides banks

and insurance corporations, finance companies, corporates and financial institutions have also

begun to invest in government securities. The maturity structure of debt has significantly

shifted in favour of medium-term and short-term borrowings. The amount of market - based

primary issuance of government securities which was about Rs. 12.000 crore in 1991-92 rose

to as high as Rs. 99,630 crore in 1999-2000. The gross market borrowings of the Central and

State governments rose to Rs. 1,81,747 crore during 2005-06.

As far as secondary market is concerned, a deep, wide and vibrant gilt-edged market has

emerged as a result of a series of structural and institutional reforms. The secondary market

turnover of government securities registered spectacular increase since mid-1990s. This is

due to a substantial rally in the government securities market.

Corporate Securities Market

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Consequent upon the policy of liberalization adopted by the government in July 1991 and the

subsequent abolition of Capital Issues Control with effect form May 29, 1992, the corporate

securities market got a tremendous boost in the first three-four years of the post-liberalization

phase.

Primary Market or the New Issues Market.

Capital issues consist of two parts - shares and debentures. Prior to 1992-93, debentures were

a more popular means of raising long-term funds and provided almost 70 per cent or more

resources raised through new capital issues.

The persons who hold shares are known as shareholders or members and are part owners of

the company. So, they enjoy certain rights like voting power, receipt of profits in the form of

dividends etc. A company can issue two types of shares, namely equity shares and preference

shares.

Debt Market. The Indian debt market is composed of government bonds and corporate

bonds. Debt Market is however dominated by government bonds. Bonds issued by the

Central government, i.e., the Government of India are the predominant and most liquid

component of the bond market. Government bonds are usually much less volatile than

equities and far more liquid than equities.

Mutual Funds. The mutual funds (MFs) have proved to be important conduits of mobilizing

resources particularly since 1987-88 when the public sector banks were allowed to set up

subsidiaries to undertake mutual fund business. The impressive growth in the Indian Mutual

fund industry in recent years can largely be attributed to various factors such as rising

household savings, comprehensive regulatory framework, favorable tax policies, introduction

of several new products, investor education campaign and role of distributors.

Secondary Market

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Secondary market refers to stock exchanges where existing securities can be regularly

purchased and sold. These markets are an important element in mobilisation of resources.

They enhance the efficiency of the flow of savings. The existence of these markets fulfils a

basic need of the investors namely the liquidity. In these markets, holders of securities can

easily dispose of their securities and obtain cash. Thus viable secondary markets by providing

marketability to securities encourage savers to take risk and make investments in the existing

securities.

NSE AND SSE. The biggest stock exchange of India is the National Stock Exchange (NSE)

which was set up in November 1992. It started its trading operations effective June 30, 1994.

Only the debt market segment of the NSE was put into operation initially

The second largest stock exchange in India is the Bombay Stock Exchange (BSE). It was the

first organised stock exchange established in India at Mumbai as far back as 1887. Presently

NSE and BSE account for almost the entire trading of scrips on Indian stock markets and

most of the regional stock exchanges have been rendered redundant.

International Comparison. In 2003, 2004 and 2005 NSE and BSE ranked third and fifth

respectively in the world on the basis of the number of transactions. In 2006, BSE slipped by

one position to sixth while NSE retained its third position. Table 47.3 shows 10 biggest stock

exchanges by number of transactions in 2003, 2004, 2005 and 2006.

ROLE OF CAPITAL MARKET IN INDIA’S INDUSTRIAL GROWTH

1. Mobilization of savings and acceleration of capital formation. In developing countries

like India plagued by paucity of resources and increasing demand for investments by

industrial organizations and governments, the importance of the capital market is self evident.

2. Promotion of industrial growth. The capital market is a central market through which

resources are transferred to the industrial sector of the economy. The existence of such an

institution encourages people to invest in productive channels rather than in the unproductive

sectors like real estate, bullion etc. Thus it stimulates industrial growth and economic

development of the country by mobilising funds for investment in the corporate securities.

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3. Raising long-term capital. The existence of a stock exchange enables companies to raise

permanent capital. The investors cannot commit their funds for a permanent period but

companies require funds permanently. The stock exchange resolves this clash of interests by

offering an opportunity to investors to buy or sell their securities while permanent capital

with the company remains unaffected.

4. Ready and continuous market. The stock exchange provides a central convenient place

where buyers and sellers can easily purchase and sell securities. The element of easy

marketability makes investment in securities more liquid as compared to other assets.

5. Proper channelization of funds. An efficient capital market not only creates liquidity

through its pricing mechanism but also functions to allocate resources to the most efficient

industries. The prevailing market price of a security and relative yield are the guiding factors

for the people to channelize their funds in a particular company. This ensures effective

utilization of funds in the public interest.

6. Provision of a variety of services. The financial institutions functioning in the capital

market provide a variety of services, the more important ones being the following: (I) grant of

long-term and medium-term loans to entrepreneurs to enable them to establish, expand or

modernize business units; (II) provision of underwriting facilities; (III) assistance in the

promotion of companies (this function is done by the development banks like the IDBI); (IV)

participation in equity capital; and (v) expert advice on management of investment in

industrial securities.

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1.3STATEMENT OF THE PROBLEM

Every individual investor who invests in the equity market wants to minimize

his risk, reduce his transaction expenses and wants to pick up the right stock so that he makes

good money either through capital appreciation or dividends. There are various investment

avenues available to an in investor today. The stock market is volatile and therefore selecting

the right & profitable investment is a real challenge to an investor. He may see mutual funds

as his best bet because mutual funds are special type of companies which provide all the

above stated services in an unique way i.e. they pool money from many investors under a

scheme and invests it on behalf of the group, in accordance with the stated set of objective

and the investors are given units of that particular scheme or fund. The foremost

consideration in selecting a scheme is its performance. Mutual funds are to be analysed in

terms of assets and liabilities in the portfolio, return of the fund, risk return portfolio and

investment objective.

A hypothetical situation is considered where an investor wants long term growth in his

capital and thus invests in the growth or capital appreciation scheme of the mutual funds. It

seems rational that any ordinary investor would try and invest in the best performing scheme

which would suit his objectives. Therefore this study aims at identifying the right mutual

fund schemes for investment with regard to returns & performance.

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1.4 OBJECTIVES OF THE STUDY

Primary objective

To analyse the risk and return of selected equity diversified funds and Large cap funds.

Secondary objectives

To evaluate the performance of selected equity diversified funds and Large cap funds.

To identify the growth potential of funds

To suggest the best performing funds to the varying investment needs of investors.

1.5 RESEARCH METHODOLOGY

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Research methodology is the way to systematically solve the research problem.

1. Type of research

Type of research is analytical where the available information or data are analysed

and critical evaluations are made to solve any problems Under this study then NAV data of

the Mutual fund schemes over a period of 3 year has been used for evaluating their

performance.

2. Population

Equity Based mutual fund schemes offered by 42 Asset Management Companies in India.

3. Sampling design

Stratified sampling is used for the study. The funds are selected from the equity diversified

scheme based on the best return percentages for the last 3year were selected for the study.

4. Sample size

10 mutual fund schemes in Equity diversified funds

1. CANARA ROBECO EQUITY DIVERSIFIED FUND (G)

2. TATA CONTRA FUND (G)

3. KOTAK CONTRA FUND (G)

4. AIG INDIA EQUITY FUND(G

5. UTI MNC FUND (G)

6. TEMPLTON INDIA EQUITY (G)

7. TATA CAPITAL BUILDER FUND (G)

8. BIRLA SUNLIFE NAXT GENERATION FUND (G)

9. SBI MAGNUM CONTRA (G)

10. ESCORTS OPPORTUNITIES FUND (G)

10 Mutual funds from Large cap Funds.

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1. ICICI PRUDENTIAL FOCUSED BLUE CHIP FUND

2. UTI OPPORTUNITIES FUND G)

3. FIDELITY EQUITY FUND

4. FRANKLIN INDIA BLUE CHIP FUND (G)

5. HDFC Top 200 FUND (G)

6. JP MORGAN INDIA EQUITY FUND

7. RELLIANCE QUANT PLUS FUND RETAIL PLAN [G]

8. ING CORE EQUITY FUND

9. HSBC INDIA OPPORTUNITIES FUND

10. BNP PARIBAS EQUITY FUND

5. Data Source

Secondary data

Secondary data are those which are already available being collected and analyzed by

someone else. The study is based on NAV data of the fund which was readily available on the

website www.amfiindia.com other information collected from records, books, magazines,

and various other websites.

6. Data Analysis Tools

The performance evaluations of the selected equity based mutual funds have been done on

the basis of NAV data by using the following analytical tools.

Risk Analysis

Total risk : Mean, Standard Deviation, Variance, Co Variance

Market Risk : Beta , Alpha

Risk Adjusted Return: Sharpe’s Performance Index, Treynor’s Performance

Growth Rate Analysis: Compounded Annual Growth Rate

4. Ranking of funds : Weighted Average Method

7. Presentation Tools: Tables & charts

1.6 SCOPE OF THE STUDY

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The study is focused on the performance of the selected equity

growth mutual funds available and invested in Indian stock market .performance of the

various types of equity diversified mutual funds for a period one year from 1st May 2009 to

31st March 2011 along with 3year Compounded Annual Growth Rate from 1st April 2012 to

31st March 2011 bring out the best performing fund during the current market situation to the

investors.

1.7 LIMITATIONS OF THE STUDY

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The study is based on the historical data may not project the future performance of the

funds.

Tools used for analysis has its own limitations. E.g. the result may vary significantly

when applied under different market situations.

The study is based on a few of selected equity diversified and sector mutual funds

only. So the result does not reflect the performance of the entire mutual fund industry.

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REVIEW OF LITERATURE

MUTUAL FUNDS:

Mutual funds, as the name indicates is the fund where in numerous investors

come together to invest in various schemes of mutual fund. Mutual funds are dynamic

institution, which plays a crucial role in an economy by mobilizing savings and investing

them in the capital market, thus establishing a link between savings and the capital market. A

mutual fund is an institution that invests the pooled funds of public to create a diversified

portfolio of securities. Pooling is the key to mutual fund investing. Each mutual fund has a

specific investment objective and tries to meet that objective through active portfolio

management.

Mutual fund as an investment company combines or collects money of its

shareholders and invests those funds in variety of stocks, bonds, and money market

instruments. The latter include securities, commercial papers, certificates of deposits, etc.

Mutual funds provide the investor with professional management of funds and diversification

of investment

Investors who invest in mutual funds are provided with units to participate in stock markets.

These units are investment vehicle that provide a means of participation in the stock market

for people who have neither the time, nor the money, nor perhaps the expertise to undertake

the direct investment in equities. On the other hand they also provide a route into specialist

markets where direct investment often demands both more time and more knowledge than an

investor may possess.

The price of units in any mutual fund is governed by the value of underlying

securities. The value of an investor’s holding in a unit can therefore, like an investment in

share, can go down as well as up. Hence it is said that mutual funds are subjected to market

risk. Mutual fund cannot guarantee a fixed rate of return. It depends on the market condition.

If the particular scheme is performing well then more return can be expected.

It also depends on the fund manager expertise knowledge. It is also seen that people invest

in particular funds depending on who the fund manager is.

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When an investor subscribes for the units of a mutual fund, he becomes part owner of

the assets of the fund in the same proportion as his contribution amount put up with the

corpus (the total amount of the fund). Mutual Fund investor is also known as a mutual fund

shareholder or a unit holder.

Mutual Fund Operation Flow Chart

Any change in the value of the investments made into capital market instruments (such

as shares, debentures etc) is reflected in the Net Asset Value (NAV) of the scheme. NAV is

defined as the market value of the Mutual Fund scheme's assets net of its liabilities. NAV of a

scheme is calculated by dividing the market value of scheme's assets by the total number of

units issued to the investors.

For example:

If the market value of the assets of a fund is Rs. 100,000

A. The total number of units issued to the investors is equal to 10,000.

B. Then the NAV of this scheme = (A)/(B), i.e. 100,000/10,000 or 10.00

C. Now if an investor 'X' owns 5 units of this scheme

Then his total contribution to the fund is Rs. 50 (i.e. Number of units held multiplied by the

NAV of the scheme).

Thus a mutual fund is the most suitable investment for the common person as it offers an

opportunity to invest in a diversified, professionally managed basket of securities at a

relatively low cost.

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Since small investors generally do not have adequate time, knowledge, experience &

resources for directly accessing the capital market, they have to rely on an intermediary,

which undertakes informed investment decisions & provides consequential benefits of

professional expertise.

A collected corpus can be used to procure a diversified portfolio indicating greater

returns has also create economies of scale through cost reduction. This principle has been

effective worldwide as more & more investors are going the mutual fund way. This portfolio

diversification ensures risk minimization. The criticality such a measure comes in when you

factor in the fluctuations that characterize stock markets. The interest of the investors is

protected by the SEBI, which acts as a watchdog. Mutual funds are governed by SEBI

(Mutual Funds) regulations, 1996.

TYPES OF MUTUAL FUNDS

BY Structure : On the basis of the structure the funds can be classified as ,

1.Open-end funds

Funds that can sell and purchase units at any point in time are classified as Open-end

Funds. The fund size (corpus) of an open-end fund is variable (keeps changing) because of

continuous selling (to investors) and repurchases (from the investors) by the fund. An open-

end fund is not required to keep selling new units to the investors at all times but is required

to always repurchase, when an investor wants to sell his units. The NAV of an open-end fund

is calculated every day.

2.Closed-end Funds

Funds that can sell a fixed number of units only during the New Fund Offer (NFO)

period are known as Closed-end Funds. The corpus of a Closed-end Fund remains unchanged

at all times. After the closure of the offer, buying and redemption of units by the investors

directly from the Funds is not allowed. However, to protect the interests of the investors,

SEBI provides investors with two avenues to liquidate their positions:

1. Closed-end Funds are listed on the stock exchanges where investors can buy/sell units

from/to each other. The trading is generally done at a discount to the NAV of the scheme.

The NAV of a closed-end fund is computed on a weekly basis (updated every Thursday).

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2. Closed-end Funds may also offer "buy-back of units" to the unit holders. In this case,

the corpus of the Fund and its outstanding units do get changed.

3. Interval Scheme

It is a type of close ended scheme with a peculiar feature that it remains open during a

particular period for the benefit of the investors either to offload their holdings or to

undertake purchase of units at the NAV.

Under the SEBI (MF) Regulations, every mutual fund is free to launch any or both

types of schemes, including interval scheme.

BY INVESTMENT OBJECTIVE :

On the basis of investor’s objective ,the funds can be classified as,

1. Equity Funds /Growth funds

Equity funds are considered to be the more risky funds as compared to other fund

types, but they also provide higher returns than other funds. It is advisable that an investor

looking to invest in an equity fund should invest for long term i.e. for 3 years or more. There

are different types of equity funds each falling into different risk bracket. In the order of

decreasing risk level, there are following types of equity funds:

A. Aggressive Growth Funds –

In Aggressive Growth Funds, fund managers aspire for maximum capital appreciation and

invest in less researched shares of speculative nature. Because of these speculative

investments Aggressive Growth Funds become more volatile and thus, are prone to higher

risk than other equity funds.

B. Growth Funds –

Growth Funds also invest for capital appreciation (with time horizon of 3 to 5 years)

but they are different from Aggressive Growth Funds in the sense that they invest in

companies that are expected to outperform the market in the future. Without entirely adopting

speculative strategies, Growth Funds invest in those companies that are expected to post

above average earnings in the future.

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C. Speciality Funds –

Speciality Funds have stated criteria for investments and their portfolio comprises of

only those companies that meet their criteria. Criteria for some speciality funds could be to

invest/not to invest in particular regions/companies. Speciality funds are concentrated and

thus, are comparatively riskier than diversified funds.. There are following types of speciality

funds:

i. Sector Funds:

Equity funds that invest in a particular sector/industry of the market are known

as Sector Funds. The exposure of these funds is limited to a particular sector (say Information

Technology, Auto, Banking, Pharmaceuticals or Fast Moving Consumer Goods) which is

why they are more risky than equity funds that invest in multiple sectors.

ii. Foreign Securities Funds:

Foreign Securities Equity Funds have the option to invest in one or more foreign

companies. Foreign securities funds achieve international diversification and hence they are

less risky than sector funds. However, foreign securities funds are exposed to foreign

exchange rate risk and country risk.

iii Mid-Cap or Small-Cap Funds:

Funds that invest in companies having lower market capitalization than large

capitalization companies are called Mid-Cap or Small-Cap Funds. Market capitalization of

Mid-Cap companies is less than that of big, blue chip companies (less than Rs. 2500 crores

but more than Rs. 500 crores) and Small-Cap companies have market capitalization of less

than Rs. 500 crores. Market Capitalization of a company can be calculated by multiplying the

market price of the company's share by the total number of its outstanding shares in the

market. The shares of Mid-Cap or Small-Cap Companies are not as liquid as of Large-Cap

Companies which gives rise to volatility in share prices of these companies and consequently,

investment gets risky.

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D. Equity Income or Dividend Yield Funds

The objective of Equity Income or Dividend Yield Equity Funds is to generate high

recurring income and steady capital appreciation for investors by investing in those

companies which issue high dividends (such as Power or Utility companies whose share

prices fluctuate comparatively lesser than other companies' share prices). Equity Income or

Dividend Yield Equity Funds are generally exposed to the lowest risk level as compared to

other equity funds.

D. Diversified Equity Funds

Except for a small portion of investment in liquid money market, diversified

equity funds invest mainly in equities without any concentration on a particular sector(s).

These funds are well diversified and reduce sector-specific or company-specific risk.

However, like all other funds diversified equity funds too are exposed to equity market risk.

E. Equity Linked Savings Schemes (ELSS)

As per the mandate, a minimum of 90% of investments by ELSS should be in equities at all

times. ELSS investors are eligible to claim deduction from taxable income (up to Rs 1 lakh)

at the time of filing the income tax return. ELSS usually has a lock-in period and in case of

any redemption by the investor before the expiry of the lock-in period makes him liable to

pay income tax on such income(s) for which he may have received any tax exemption(s) in

the past.

F. Equity Index Funds

Equity Index Funds have the objective to match the performance of a specific stock market

index. The portfolio of these funds comprises of the same companies that form the index and

is constituted in the same proportion as the index. Equity index funds that follow broad

indices (like S&P CNX Nifty, Sensex) are less risky than equity index funds that follow

narrow sectoral indices (like BSEBANKEX or CNX Bank Index etc). Narrow indices are less

diversified and therefore, are more risky.

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2. Debt / Income Funds

Funds that invest in medium to long-term debt instruments issued by private companies,

banks, financial institutions, governments and other entities belonging to various sectors (like

infrastructure companies etc.) are known as Debt / Income Funds. Debt funds are low risk

profile funds that seek to generate fixed current income (and not capital appreciation) to

investors. In order to ensure regular income to investors, debt (or income) funds distribute

large fraction of their surplus to investors. Although debt securities are generally less risky

than equities, they are subject to credit risk (risk of default) by the issuer at the time of

interest or principal payment.

A. Diversified Debt Funds

Debt funds that invest in all securities issued by entities belonging to all sectors of the

market are known as diversified debt funds. The best feature of diversified debt funds is that

investments are properly diversified into all sectors which results in risk reduction. Any loss

incurred, on account of default by a debt issuer, is shared by all investors which further

reduces risk for an individual investor.

B. Focused Debt Funds

Unlike diversified debt funds, focused debt funds are narrow focus funds that are confined to

investments in selective debt securities, issued by companies of a specific sector or industry

or origin. Some examples of focused debt funds are sector, specialized and offshore debt

funds, funds that invest only in Tax Free Infrastructure or Municipal Bonds. Because of their

narrow orientation, focused debt funds are more risky as compared to diversified debt funds.

Although not yet available in India, these funds are conceivable and may be offered to

investors very soon.

C. High Yield Debt funds

As we now understand that risk of default is present in all debt funds, and therefore, debt

funds generally try to minimize the risk of default by investing in securities issued by only

those borrowers who are considered to be of "investment grade". But, High Yield Debt Funds

adopt a different strategy and prefer securities issued by those issuers who are considered to

be of "below investment grade".

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D. Assured Return Funds

Although it is not necessary that a fund will meet its objectives or provide assured returns to

investors, but there can be funds that come with a lock-in period and offer assurance of

annual returns to investors during the lock-in period. Any shortfall in returns is suffered by

the sponsors or the Asset Management Companies (AMCs). These funds are generally debt

funds and provide investors with a low-risk investment opportunity. However, the security of

investments depends upon the net worth of the guarantor (whose name is specified in advance

on the offer document). To safeguard the interests of investors, SEBI permits only those

funds to offer assured return schemes whose sponsors have adequate net-worth to guarantee

returns in the future. In the past, UTI had offered assured return schemes (i.e. Monthly

Income Plans of UTI) that assured specified returns to investors in the future. UTI was not

able to fulfill its promises and faced large shortfalls in returns. Eventually, government had to

intervene and took over UTI's payment obligations on itself. Currently, no AMC in India

offers assured return schemes to investors, though possible.

E. Fixed Term Plan Series

Fixed Term Plan Series usually are closed-end schemes having short term maturity period

(of less than one year) that offer a series of plans and issue units to investors at regular

intervals. Unlike closed-end funds, fixed term plans are not listed on the exchanges. Fixed

term plan series usually invest in debt / income schemes and target short-term investors. The

objective of fixed term plan schemes is to gratify investors by generating some expected

returns in a short period

1. Money Market / Liquid Funds

Money market / liquid funds invest in short-term (maturing within one year) interest

bearing debt instruments. These securities are highly liquid and provide safety of investment,

thus making money market / liquid funds the safest investment option when compared with

other mutual fund types. However, even money market / liquid funds are exposed to the

interest rate risk. The typical investment options for liquid funds include Treasury Bills

(issued by governments), Commercial papers (issued by companies) and Certificates of

Deposit (issued by banks).

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2 . Hybrid Funds

As the name suggests, hybrid funds are those funds whose portfolio includes a

blend of equities, debts and money market securities. Hybrid funds have an equal proportion

of debt and equity in their portfolio. There are following types of hybrid funds in India:

A. Balanced Funds -

The portfolio of balanced funds include assets like debt securities, convertible securities, and

equity and preference shares held in a relatively equal proportion. The objectives of balanced

funds are to reward investors with a regular income, moderate capital appreciation and at the

same time minimizing the risk of capital erosion. Balanced funds are appropriate for

conservative investors having a long term investment horizon.

B. Growth-and-Income Funds

Funds that combine features of growth funds and income funds are known as Growth-and-

Income Funds. These funds invest in companies having potential for capital appreciation and

those known for issuing high dividends. The level of risks involved in these funds is lower

than growth funds and higher than income funds.

OTHER SCHEMES

1. Gilt Funds

Also known as Government Securities in India, Gilt Funds invest in government papers

(named dated securities) having medium to long term maturity period. Issued by the

Government of India, these investments have little credit risk (risk of default) and provide

safety of principal to the investors. However, like all debt funds, gilt funds too are exposed to

interest rate risk. Interest rates and prices of debt securities are inversely related and any

change in the interest rates results in a change in the NAV of debt/gilt funds in an opposite

direction.

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2.Asset Allocation Funds

Mutual funds may invest in financial assets like equity, debt, money market or non-financial

(physical) assets like real estate, commodities etc.. Asset allocation funds adopt a variable

asset allocation strategy that allows fund managers to switch over from one asset class to

another at any time depending upon their outlook for specific markets. It should be noted that

switching over from one asset class to another is a decision taken by the fund manager on the

basis of his own judgment and understanding of specific markets, and therefore, the success

of these funds depends upon the skill of a fund manager in anticipating market trends.

3.Commodity Funds

Those funds that focus on investing in different commodities (like metals, food grains, crude

oil etc.) or commodity companies or commodity futures contracts are termed as Commodity

Funds. A commodity fund that invests in a single commodity or a group of commodities is a

specialized commodity fund and a commodity fund that invests in all available commodities

is a diversified commodity fund and bears less risk than a specialized commodity fund.

"Precious Metals Fund" and Gold Funds (that invest in gold, gold futures or shares of gold

mines) are common examples of commodity funds.

4. Real Estate Funds

Funds that invest directly in real estate or lend to real estate developers or invest in

shares/securitized assets of housing finance companies, are known as Specialized Real Estate

Funds. The objective of these funds may be to generate regular income for investors or

capital appreciation.

5 Exchange Traded Fund

Exchange Traded Funds provide investors with combined benefits of a closed-end and an

open-end mutual fund. Exchange Traded Funds follow stock market indices and are traded on

stock exchanges like a single stock at index linked prices. The biggest advantage offered by

these funds is that they offer diversification, flexibility of holding a single share (tradable at

index linked prices) at the same time. Recently introduced in India, these funds are quite

popular abroad.

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6.Fund of funds

Mutual funds that do not invest in financial or physical assets, but do invest in other mutual

fund schemes offered by different AMCs, are known as Fund of Funds. Fund of Funds

maintain a portfolio comprising of units of other mutual fund schemes, just like conventional

mutual funds maintain a portfolio comprising of equity/debt/money market instruments or

non financial assets. Fund of Funds provide investors with an added advantage of

diversifying into different mutual fund schemes with even a small amount of investment,

which further helps in diversification of risks. However, the expenses of Fund of Funds are

quite high on account of compounding expenses of investments into different mutual fund

schemes

The Advantages of investing in a Mutual Fund are:

Professional Management –

The primary advantage of funds (at least theoretically) is the professional management of

your money. Investors purchase funds because they do not have the time or the expertise to

manage their own portfolio. A mutual fund is a relatively inexpensive way for a small

investor to get a full-time manager to make and monitor investments.

Diversification –

By owning shares in a mutual fund instead of owning individual stocks or bonds, your risk is

spread out. The idea behind diversification is to invest in a large number of assets so that a

loss in any particular investment is minimized by gains in others. In other words, the more

stocks and bonds you own, the less any one of them can hurt you (think about Enron). Large

mutual funds typically own hundreds of different stocks in many different industries. It

wouldn't be possible for an investor to build this kind of a portfolio with a small amount of

money.

Economies of Scale –

Because a mutual fund buys and sells large amounts of securities at a time, its transaction

costs are lower than you as an individual would pay.

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Convenient Administration–

Investing in a Mutual Fund reduces paperwork and helps you avoid many problems such as

bad deliveries, delayed payments and follow up with brokers and companies. Mutual Funds

save your time and make investing easy and convenient.

Return Potential–

Over a medium to long-term, Mutual Funds have the potential to provide a higher return as

they invest in a diversified basket of selected securities.

Low Costs–

Mutual Funds are a relatively less expensive way to invest compared to directly investing in

the capital markets because the benefits of scale in brokerage, custodial, Demat costs,

depository costs etc and other fees translate into lower costs for investors.

Liquidity–

In open-end schemes, the investor gets the money back promptly at net asset value related

prices from the Mutual Fund. In closed-end schemes, the units can be sold on a stock

exchange at the prevailing market price or the investor can avail of the facility of direct

repurchase at NAV related prices by the Mutual Fund.

Transparency–

You get regular information on the value of your investment in addition to disclosure on the

specific investments made by your scheme, the proportion invested in each class of assets and

the fund manager's investment strategy and outlook

Flexibility–

Through features such as regular investment plans, regular withdrawal plans and dividend

reinvestment plans, you can systematically invest or withdraw funds according to your needs

and convenience.

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Affordability–

Investors individually may lack sufficient funds to invest in high-grade stocks. A mutual fund

because of its large corpus allows even a small investor to take the benefit of its investment

strategy.

Choice of Schemes–

Mutual Funds offer a family of schemes to suit your varying needs over a lifetime.

Well-Regulated–

All Mutual Funds are registered with SEBI and they function within the provisions of strict

regulations designed to protect the interests of investors. The operations of Mutual Funds are

regularly monitored by SEBI. AMFI is the supervisory body of Mutual Fund Industry.

Simplicity –

Buying a mutual fund is easy! Pretty well any bank has its own line of mutual funds, and the

minimum investment is small. Most companies also have automatic purchase plans whereby

as little as $100 can be invested on a monthly basis.

The Disadvantages of Mutual Funds are:

The Disadvantages of investing in a Mutual Fund are:

• Professional Management-

Many investors debate over whether or not the so-called professionals are any better than you

or I at picking stocks. Management is by no means infallible, and, even if the fund loses

money, the manager still takes his/her cut. We'll talk about this in detail in a later section.

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• Costs –

Mutual funds don't exist solely to make your life easier--all funds are in it for a profit. The

mutual fund industry is masterful at burying costs under layers of jargon. These costs are so

complicated that in this tutorial have devoted an entire section to the subject.

• Dilution –

It's possible to have too much diversification (this is explained in our article entitled "Are

You Over-Diversified?". Because funds have small holdings in so many different companies,

high returns from a few investments often don't make much difference on the overall return.

Dilution is also the result of a successful fund getting too big. When money pours into funds

that have had strong success, the manager often has trouble finding a good investment for all

the new money.

• Taxes –

When making decisions about your money, fund managers don't consider your personal tax

situation. For example, when a fund manager sells a security, a capital-gain tax is triggered,

which affects how profitable the individual is from the sale. It might have been more

advantageous for the individual to defer the capital gains liability.

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PERFORMANCE EVALUATION OF MUTUAL FUNDS

Performance evaluation is a critical and often poorly handled part of

the portfolio management process. The principal problem with the performance evaluation is

the human tendency to focus on the return a portfolio earned over a period of time with little

regard to the risk taken in achieving that return. Proper performance evaluation should

involve a recognition of both return and riskiness of the investment.

Return alone should not be considered as the basis of

measurement of the performance of a mutual fund scheme, it should also include the risk

taken by the fund manager because different funds will have different levels of risk attached

to them. Risk associated with a fund, in a general, can be defined as variability or fluctuations

in the returns generated by it. The higher the fluctuations in the returns of a fund during a

given period, higher will be the risk associated with it. These fluctuations in the returns

generated by a fund are resultant of two guiding forces. First, general market fluctuations,

which affect all the securities present in the market, called market risk or systematic risk and

second, fluctuations due to specific securities present in the portfolio of the fund, called

unsystematic risk. The Total Risk of a given fund is sum of these two and is measured in

terms of standard deviation of returns of the fund. Systematic risk, on the other hand, is

measured in terms of Beta, which represents fluctuations in the NAV of the fund vis-à-vis

market. The more responsive the NAV of a mutual fund is to the changes in the market;

higher will be its beta. Beta is calculated by relating the returns on a mutual fund with the

returns in the market. While unsystematic risk can be diversified through investments in a

number of instruments, systematic risk can not. By using the risk return relationship, we try

to assess the competitive strength of the mutual funds vis-à-vis one another in a better way.

In order to determine the risk-adjusted returns of investment portfolios, several eminent

authors have worked since 1960s to develop composite performance indices such as to

evaluate a portfolio by comparing alternative portfolios within a particular risk class.

Sharpe’s index ands Treynor’s index are important among them.

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Measurement of return on mutual funds

A mutual fund's return is the rate of increase or decrease in its value over a specific

period of time usually expressed in the following increments: one, three, five, and ten year,

year to date, and since the inception of the fund.  Since return is a common measure of

performance, you can use it to evaluate and compare mutual funds within the same fund

category.  Generally expressed as an annualized percentage rate, return is calculated

assuming that all distributions from the fund are reinvested.

Performance evaluation of mutual funds starts with measurement of return on mutual

funds . Return on mutual funds can be primarily measured in terms of NAV (Net Asset

Value) of the funds.

NAV is the current market value of a fund’s holdings, less the fund’s liabilities, usually

expressed as a per unit amount. For most funds, the NAV is determined daily, after the close

of the trading on some specified stock exchange. But some funds update their NAV multiple

times during the trading day.

Market value of assets- Liabilities

NAV=

No of units outstanding

Change in NAV method

Here the return on mutual fund is calculated by change in NAV method. According to this

method ,

[ Value of holding at the _ [Value of holding at the

end of the period] beginning of the period]

Return(%) = _________________________________________________ * 100

[ Value of holding at the beginning of the period]

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Risk Measurement of Mutual Funds

Every type of investment, including mutual funds, involves risk.  Risk refers

to the possibility that you will lose money (both principal and any earnings) or fail to make

money on an investment.  A fund's investment objective and its holdings are influential

factors in determining how risky a fund is.

Risk is the possibility of loss or variation of the actual return from the

expected one. Risk arises when actual returns are different from expected returns . Risk is

caused by numerous factors such as social, political, economic and managerial factors. Risk

is actually a qualitative concept that is impossible to measure completely. Research has

discovered , however, that a quantitative measure of dispersion is a very good proxy. So the

accuracy of measurements cannot be assured cent per cent. Measurements provides an

approximate quantification of risk. Expressing the risk of a fund in quantitative terms makes

it comparable with other funds.

1. Standard deviation(SD)

It is a statistical tool used to measure the risk. Formulated by Galton in the late 1860s, the

standard deviation remains the most common measure of statistical dispersion, measuring

how widely spread the values in a data sets are.

If many data points are close to the mean the standard deviation is very small.

If many data points are far from the mean the standard deviation is very large.

If all values are equal then Standard deviation is zero.

Standard deviation(SD) = N∑x2- (∑x)2

N2

Investors prefer Standard Deviation because it provides a precise measure of how varied a

funds return have been over a particular period of time-both on the upside and down side.

With this information, an investor can judge the range of returns his or her fund is likely to

generate in future.

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2.Beta coefficient (β)

Beta of a fund indicates it’s systematic risk or market risk which is non-diversifiable in

nature. Beta shows how the price of a fund responds to market forces. ie. it describes the

relationship between the stock/fund’s return and index return.

( n∑XY) – (∑X)(∑Y)

Beta =

(n∑X2)-(∑X)2

Where,

X represents stock market index return

Y represents stock or fund return

By definition, the market itself has an underlying beta of 1.0, and individual fund are

ranked according to how much they deviate from the macro market.

A fund that swings more than the market (i.e. more volatile) over time has a beta whose

absolute value is greater than 1.0.

If a fund moves less than the market, the absolute value of the stock's beta is less than 1.0.

Betas can also be negative, meaning the fund moves in the opposite direction of the

market: fund with a beta of -3 would decline 9% when the market goes up 3% and conversely

would climb 9% if the market fell by 3%.

Higher-beta fund mean greater volatility and are therefore considered to be riskier, but are

in turn supposed to provide a potential for higher returns low-beta fund pose less risk but also

lower returns

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3. Alpha(α)

Alpha is a measure of performance on a risk adjusted basis. Alpha takes the volatility or price

risk of a mutual fund and compares its risk adjusted performance to its benchmark index. The

excess return of the fund relative to the benchmark index is the fund’s index. It is the distance

between intersection of market return and fund return.

Alpha (α) = Ȳ - βX ,

Where

Ȳ = ∑Y/n ie Mean return of the fund

X = ∑X/n ie. Mean return of the market

β= Beta of the fund

A positive value would yield profitable return. It is a healthy sign. In a well diversified

portfolio, the average value of alpha of funds turns out to be zero.

Measurement of Risk Adjusted Returns

Two methods of measuring the return per unit of risk have been proposed by Jack Treynor

and William Sharpe. The methods are discussed below.

1.Treynor’s Index

The Treynor’s Index owes its origin to Jack Treynor. This index is the ratio of return

generated by the fund over and above risk free rate of return, during a given period and

systematic risk(Beta) associated with it. The risk free rate of return is generally taken as the

return on government securities as there is no credit risk associated with them. The Treynor’s

index can be represented as: -

Treynor’s Index (Ti) = (Ri – Rf) / β i

Where’ Ri represents average return on fund ,

Rf is the risk free rate of return and

β i is the Beta of the fund

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1. Sharpe’s Index

The Sharpe ratio is a risk-adjusted measure of return that is often used to evaluate

the performance of a portfolio or fund .Sharpe index measures the risk premium of the

portfolio relative to the total amount of risk in the portfolio. The risk premium is the

difference between the portfolio’s average rate of return and risk free rate of return. The

standard deviation of the portfolio indicates the risk. According to Sharpe, it is the total risk

of the fund that the investors are concerned about. So, the model evaluates funds on the basis

of reward per unit of total risk.

The sharpe index is given by the formula:

Sharpe Ratio (Si) = (Ri - Rf) / SD

Where, Ri represents average return on fund .

Rf is the risk free rate of return.

SD is the Standard Deviation of the Fund .

Sharpe’s ratio gives a single value to be used for ranking the performance of various funds or

portfolios. The highest values to the assets that have best risk adjusted rate of return. While a

high and positive Sharpe Ratio shows a superior risk-adjusted performance of a fund, a low

and negative Sharpe Ratio is an indication of unfavorable performance.

Comparison of Sharpe and Treynor Measures

Sharpe and Treynor measures are similar in a way, since they both divide the risk premium

by a numerical risk measure. The total risk is appropriate when we are evaluating the risk

return relationship for well-diversified portfolios. On the other hand, the systematic risk is the

relevant measure of risk when we are evaluating less than fully diversified portfolios or

individual stocks. For a well-diversified portfolio the total risk is equal to systematic risk.

Rankings based on total risk (Sharpe measure) and systematic risk (Treynor measure) should

be identical for a well-diversified portfolio, as the total risk is reduced to systematic risk.

Therefore, a poorly diversified fund that ranks higher on Treynor measure, compared with

another fund that is highly diversified, will rank lower on Sharpe Measure.

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Growth Rate Analysis

Compound Annual Growth Rate (CAGR):

Compound Annual Growth Rate (CAGR) is a business and investing specific term for

the smoothed annualized gain of an investment over a given time period.

CAGR is the rate at which the investment has grown from its beginning to the end

point , on an annual compounding basis. It is the year over year growth rate applied to an

investment over a multiple-year period. One of the benefits of CAGR over other calculations

is that it decrease the effects of volatility. CAGR is not an accounting term, but remains

widely used, particularly in growth industries or to compare the growth rates of two

investments because CAGR dampens the effect of volatility of periodic returns that can

render arithmetic means irrelevant. CAGR is often used to describe the growth over a period

of time of some element of the business, for example revenue, units delivered, registered

users, etc.

Formula is,

CAGR (t0,tn) =( [V(tn)/V(t0) ] 1/n)-1 * 100

Where ,V(t0) =start value,

V(tn) = finish value,

n = tn − t0 = number of years

Ranking the Schemes

In order to arrive at the best fund in each category of funds under study , it is essential to

rank them on an appropriate basis. Here the funds are ranked using the Weighted Average

Method by assigning weights to CAGR, SHARPE Ratio and Treynor Ratio as 3,2,1

respectively.

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Weighted Average Method

The weighted mean is similar to an arithmetic mean (the most common type of average),

where instead of each of the data points contributing equally to the final average, some data

points contribute more than others. The notion of weighted mean plays a role in descriptive

statistics and also occurs in a more general form in several other areas of mathematics.

An average in which each quantity to be averaged is assigned a weight. These weightings

determine the relative importance of each quantity on the average. Therefore data elements

with a high weight contribute more to the weighted mean than do elements with a low

weight. The weights cannot be negative. Some may be zero, but not all of them (since

division by zero is not allowed).

∑Wi *Xi

Formula is = ____________

∑Wi

Where, Wi=Weight of value ‘ Xi’ and Xi = Value

Steps :

1. Assign weight to each value on the basis of its importance.

2. Multiply each value by its weight.

3. Add up the products of value times weight to get the total value.

4 Add the weight themselves to get the total weight.

5. Divide the total value by the total weight.

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Factors to be considered while comparing mutual funds

Picking and choosing a mutual fund is appear to have turned out to be a multi-sided

matter. As there are plenty of funds available in the market, the most crucial factor in

determining which one is better than the rest is to look at the returns.

1. Absolute returns- measure how much the fund has gained over a certain period

The return that an asset achieves over a period of time. This measure simply looks at the

appreciation or depreciation (expressed as a percentage) that an asset - usually a stock or a

mutual fund - faces over a period of time.

2. Funds Benchmark- This will provide the standard by which we can make the assessment.

It indicates what the fund has earned against what it should have earned. The benchmark

index selected for this study is S&P CNX Nifty

The S&P CNX Nifty is the headline index on the National Stock Exchange of India Ltd.

(NSE). It is a diversified 50 stock index comprising large and highly liquid securities,

covering 25 sectors of the economy. The index was created for those interested in trading and

investing in Indian equities. In addition to ensuring that Nifty is a true reflection of the stock

market, it was also designed for applications such as index funds and index derivatives.

3.Time period-The period over which the return should be compared and assessed has to be

the same over which that type of fund is meant to be invested in.

4. Market Conditions -It is important to see whether the funds return history is long enough

to have seen all kinds of market conditions

5..When returns are compared ,make sure that the time period is equal.

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Sharpe (1966) in order to evaluate the risk-adjusted performance of mutual funds introduced the

measure known as reward-to-variability ratio (Currently Sharpe Ratio). With the help of this ratio he

evaluated the return of 34 open-end mutual funds in the period 1945-1963. The results showed that

to a major extent the capital market was highly efficient due to which majority of the sample had

lower performance as compared to the Dow Jones Index. Sharpe (1966) found that from 1954 to

1963 only 11 funds outperformed the Dow-Jones Industrial Average (DJIA) while 23 funds were

outperformed by the DJIA. Study concluded that the mutual funds were inferior investments during

the period. Results also showed that good managers concentrate on evaluating risk and providing

diversification.

Jensen (1968) developed own measure known as Jensen’s Alpha to examine the risk- portfolios’

risk-adjusted performance and estimate the predictive ability of mutual fund managers. The measure

was based on the theory of the pricing of capital assets. For this purpose a sample of 115 open end

mutual funds (for which net asset and dividend information was available) was taken for the period

1955-1964. After applying the Jensen measure he concluded that stock prices could not be forecasted

accurately with the help of mutual funds therefore buy and hold strategy could not be used to take

any advantage. Similarly there is slight evidence that an individual mutual fund can achieve returns

higher than a portfolio comprised of randomly selected shares.

Carlson (1970) conducted a research to analyze the predictive value of past results in forecasting

future performance of mutual funds for the period 1948-1667. The author also examined the

efficiency of market and identified the factors related to the fund performance. First of all he

constructed indices for three types of mutual funds (Diversified common stock, Balanced, Income)

and compared these indices with the market indices. In order to analyze the performance regression

was used. The results provide empirical support to the return-risk postulate of the capital asset

pricing model and concluded that whether mutual funds outperform the market depends on the

selection of both the time period and market proxy. The author also concluded that past performance

showed little predictive value and that the performance was positively related to the availability of

new cash resources for investment purposes.

Arditti (1971) criticized the reward-to-variability criterion proposed by Sharpe (1966) on the

grounds that it utilized only the first two moments of the probability distribution of returns. Author

proposed that the third moment, a measure of the direction and size of the distribution’s tail, be

included in the analysis.  Arditti (1971) further argued that investors preferred positive skewness

40

because positive skewness implied greater probability of higher return. Therefore assets with

relatively low reward-to-variability ratios would not be inferior investments if ratios also have

relatively high third moments (high positive skewness). Furthermore author reexamined the Sharpe

(1966) data with this additional requirement and found that average fund performance was not

inferior to Dow Jones Industrial Average (DJIA) performance because the skewness of the Dow

Jones Industrial Average (DJIA) return distribution was significantly less than fund skewness.

Deepak Agrawal (2010) “Measuring Performance of Indian Mutual funds”. This paper is a process

to analyze the Indian Mutual Fund Industry pricing mechanism with empirical studies on its

valuation. It also analyzes data at both the fund-manager and fund-investor levels. The study reveled

that the performance is affected saving and investment habits of the people at the second side the

confidence and loyalty of the fund Manager and rewards affects the performance of the MF industry

in India.

Mcdonald (1973) developed a model to evaluate the investment performance of funds holding

securities in two countries. For this purpose a sample of eight of the oldest French mutual funds was

taken. The monthly returns of these funds were calculated and analyzed for the period 1964-1969.

The results showed that the funds generally produced superior risk-adjusted returns and that the

French market was inefficient with respect to the completeness and speed of dissemination of

information. The author concluded that those funds which invested in the French market in 1964-69

generally achieved lower return at a given level of variance than that reflected in the U.S. market

returns. Mcdonald (1973) also found that the funds were generally able to attain superior returns

relative to naive portfolio strategy.

McDonald (1974) conducted a research to examine the objectives and performance (risk and return)

of American mutual funds in the period 1960-1669. Sample of 123 American mutual funds was

analyzed by using Treynor (1965) and Sharpe (1966) indexes. The results indicated that stated

objectives were significantly related to subsequent measures of systematic risk and total variability.

Therefore the funds with aggressive objectives generally produced better performance. The results

also showed that 67 funds perform better than the stock market average in case of Treynor’s (1965)

index while in case of Sharpe’s (1966) index only 39 mutual funds showed higher performance than

the stock market average. The author concluded that Average fund return increases with increase in

risk.

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Miller and Nicholas (1980) conducted a research to examine the risk-return relationships in the

presence of nonstationarity in order to obtain more precise estimates of alpha and beta. For this

purpose this study applied partition regression and a partition selection rule for estimating the

traditional CAPM in case of nonstationarity. Study applied these procedures to price appreciation

data for the market and 28 mutual funds for the period of 1973-1974. The results indicated a good

deal of noncosistency in the risk-return relationships. The results showed some weak positive

relationships and some weak negative relationships between betas and the rate of return for the

market. On the other hand results showed some weak positive relationships and some weak negative

relationships between betas and alphas. However, no general, statistically significant relationships of

either type were found.

Jonathan B. Berk &Richard C. Green(December 9, 2002 ); ‘Mutual Fund Flows and Performance

in Rational Markets’. From the study they derived that a number of empirical predictions of a

rational model for active portfolio management when managerial talent is a scarce resource and is

dissipated as the scale of operations increases. Many of these predictions reproduce empirical

regularities that often have been taken as evidence of investor irrationality or agency costs between

managers and investors. Not only is the rational model consistent with much of the empirical

evidence, but it is also consistent with a surprisingly high level of skill amongst active managers.

In order to analyze the market-timing performance of mutual funds a study was conducted by

Henriksson (1984). For this purpose a sample of 116 open-end mutual funds from February 1968 to

June1980 was taken.  By using parametric and nonparametric techniques author examined the

performance of these open-end mutual funds using monthly data. The returns data included all

dividends paid by the fund and were net of all management costs and fees. Both the parametric and

nonparametric tests showed that mutual fund managers were unable to follow a successful

investment strategy. The results also showed that no evidence was found that forecasters were more

successful in the market-timing activity with respect to predicting large changes in the value of the

market portfolio relative to smaller changes.

Ippolito (1989) conducted a research to analyze the efficiency in capital markets when information

is costly to obtain. Sample of 143 mutual funds were reported in the 1965 edition of Wiesenberger.

The analysis was done for the period of 1965-1984. Ippolito (1989) employed CAPM model and

made a comparison of results to those reported in Jenson (1968). The results showed that Risk-

42

adjusted returns in the mutual fund industry, net of fees and expenses, were comparable to returns

available in index funds. Results also indicated that portfolio turnover and management fees were

unrelated to fund performance. The researcher concluded that mutual funds with higher turnover fees

and expenses, earn rates of return sufficiently high to offset the higher charges. Research also

concluded that the mutual funds were efficient in the trading and information-gathering activities.

A research was conducted by Cumby and Jack (1990) to compare the performance of

internationally diversified mutual funds with international equity index and Morgan Stanley Index

for the United States. In this study a sample of fifteen U.S.-based internationally diversified mutual

funds between 1982 and 1988 was used. The performance was then compared with the help of

Jensen (1968) measure and Positive Period Weighting Measure. The results concluded that the

performance of funds individually or as a whole was not higher than the performance of international

equity index. The authors also examined the performance of the funds relative to the Morgan Stanley

index for the United States and found some evidence that the funds outperform the U.S. index.

Doron Avramov and Russ Wermers (2004); ‘Investing in Mutual Funds when Returns are

Predictable’ From the study it found that predictability in mutual fund returns and the overall value

of active Management in an investment based framework. They form optimal portfolios of no-load,

open-end U.S. domestic-equity mutual funds in the presence of predictability (based on business

cycle variables) in (i) manager selectivity and benchmark-timing skills, (ii) mutual fund risk-

loadings, and (iii) benchmark returns. The proposed framework is quite general and applicable to real

investment strategies. Overall, our findings indicate that industries are important in locating

outperforming mutual funds, and that active management adds much more value than documented by

prior studies.

Grinblatt and Sheridan (1992) conducted a research to analyze whether mutual fund performance

relates to past performance. For this purpose a sample of 279 funds was taken. Study divided the

sample into two five year sub periods and calculated the abnormal returns of each fund for each five

year sub period. Similarly the slope coefficient of abnormal returns was computed in a cross-

sectional regression. The results indicated a positive persistence in mutual fund performance and

fund managers were able to earn abnormal returns. Therefore study concluded that the past

performance of a fund provides useful information for investors who were considering an investment

in mutual funds.

43

A research was conducted by Martin et al. (1993) to examine the performance of bond mutual

funds. Samples of bond fund: first sample was designed to eliminate survivorship bias and was

comprised of the 46 non-municipal bond funds for the 10-year period from the beginning of 1979 to

the end of 1988. The second sample consisted of all bond funds that existed at the end of 1991.

Researcher used linear and nonlinear models in order to examine the two samples. The results

showed that bond funds underperform relevant indexes post expenses.

Malkiel (1995) conducted a research to analyze the performance of equity mutual funds for the

period 1971 to 1991. For this purpose study involved a data set that included the returns from all

mutual funds in existence in each year of the period. After analyzing the returns from all funds he

found that mutual funds underperformed the market. Survivorship bias was considered to be the

important part of the analysis. Study also examined the fund returns in the context of the capital asset

pricing framework and neither found any evidence of excess return nor observed any risk return

relationship stated by the capital asset pricing model. Study concluded that it was better for the

investors to purchase a low expense index fund than to select an active fund manager.

Cai et al. (1996) evaluated the performance of Japanese open-type equity funds from 1981 to 1992.

For this purpose a sample of 800 open-type mutual funds run by 9 management companies was

taken. Two benchmarks (value-weighted single-index benchmark and three-factor benchmark) were

used in the analysis. This research used Jensen Measure, Positive Period Weighting (PPW) Measure

and Conditional Jensen Measure in order to evaluate the performance of these funds. The results

showed that value-weighted and equal-weighted portfolios of 800 mutual funds underperform the

single-index benchmark by approximately 7.0% and 6.0%. The results also showed that most of the

funds were inclined to invest more in large stocks.

Otten and Dennis (1999) analyzed the performance of European mutual funds from 1991 through

December 1998. Study also investigated the performance of fund managers along with the influence

of fund characteristics on risk-adjusted performance. For this purpose a sample of 506 funds was

taken and 4-factor model was used. The results indicated that the European mutual funds especially

small cap funds were able to add value and 4 out of 5 countries exhibit significant outperformance at

an aggregate level. The results also revealed positive relation between risk-adjusted return and fund

size and negative relation between risk-adjusted and funds’ expense ratio.

44

Redman (2000) analyzed the risk adjusted returns for five portfolios of international mutual funds.

The study was conducted for three periods: 1985-1994, 1985-1989, and 1990-1994. The performance

was measured by using Treynor (1965) Index Sharpe (1966)’s Index and Jensen’s Alpha and

comparison was made with the U. S. market. Results showed that under Sharpe (1966)’s and Treynor

(1965) indices the performance of portfolios of international mutual funds was higher than the U. S.

market from 1985-1994 and 1985-1989. On the other hand performance of U.S equity portfolio and

the market index was higher than global portfolios from 1990-1994.

Stehle and Olaf (2001) conducted a research to evaluate the open-ended mutual funds risk-adjusted

performance. Study used a data set that included all German funds sold to the public in 1972. The

research analyzed covers the time period of 1973 to 1998. DAX, which included the 30 largest

German stocks and DAX100, which included the 100 largest German stocks were used as

benchmarks for comparison. First of all researchers examined the rates of return of individual funds

with the help of Sharpe (1966) and Jensen measures and then applied the same measures to evaluate

the unweighted average rates of return of all funds. In case of the rates of return of individual funds,

results showed that the funds underperform the appropriate benchmarks by approximately 1.5 % per

year. On the other hand underperformance was reduced by 40 % in case of unweighted average rates

of return. Study also concluded that the large German stock mutual funds, on the average, performed

better than the small ones.

A study was conducted by Otten, and Mark (2002) to compare the performance of European

mutual fund industry with performance of United States fund industry. Sample of 506 European

open-ended mutual funds and 2096 American open-ended mutual funds was taken from January

1991 to December 19979. Study was restricted the sample to purely domestic equity funds with at

least 24 months of data. Results also indicated that European mutual funds had on average a better

performance than the American counterparts and that the small cap mutual funds in both Europe and

the United States outperformed the benchmark and all other mutual funds.

Noulas, John and John (2005) evaluated the risk adjusted performance of Greek equity funds

during the period 1997-2000. This study is based on weekly data for equity mutual funds and

includes 23 equity funds that existed for the whole period under consideration. Mutual funds were

ranked on the techniques used by Treynor (1965), Sharpe (1966) and Jensen. Results showed

positive returns of the stock market for the first three years and negative returns for the fourth year.

The results also indicated that the beta of all funds is smaller than 1 for four-year period.

45

Company profile

Capstocks is a professionally managed stock broking company having an unblemished and

unparalleled service history of more than 23 years and a vibrant tradition of trust, loyalty and

reliability. Capstocks was started by Rajendran.V, the present Managing Director of the company, in

the year 1989. Capstocks is having both online and offline trading facilities. It is the first ISO

9001:2008 certified stock broking firm in India for all services in stock broking and allied activities.

Capstocks has about 180 outlets in various states of India and an international office in

Sharjah,UAE . Capstocks is a member of the National Stock Exchange of India (NSE), Bombay

Stock Exchange (BSE), MCX Stock Exchange (MCX-SX), Depository Participant with the Central

Depository Services (CDSL) and a SEBI-registered Portfolio Manager. Capstocks also offers

commodity services through its subsidiary company Capstocks Finanacial Services Ltd which is a

member of the Multi-Commodity Exchange of India (MCX) and National Commodity Derivative

Exchange (NCDEX).

Management

The Company's Management rests on:

Rajendran. V. (Chairman & Managing Director) Engineer by profession, with in-depth knowledge

and experience in market analysis.

Leela Jeyakumar (Director) Post Graduate with over 18 years experience in stock broking and the in

charge of company's Tamil Nadu operation since 1992.

Meera Sahib. B (Director) Post Graduate with LLB & CAIIB and 28 years of experience in officer /

executive cadre in a major Public Sector Bank

Amjad Hydari (Assistant Vice President) Post Graduate with more than 12 years experience in

various functions of the equity market brokerage.

46

Other Directors

Srinivasan S.IAS. (Director) Former Labor Commissioner and District Collector. Presently,

Chairman and Managing Director, ODEPEC. Prema Rajendran (Director) Graduate in Commerce

with more than 12 years experience. Rajeev Pillai (Executive Director) Engineer By Profession with

wide exposure to International business organisations and consulting firms. Currently heading the

North & West India Operations of Capstocks with head quarter at Mumbai.

ISO Certification

Capstocks has become the first ISO 9001:2008 brokerage in India to get certification for all stock

broking and related financial service activities including Cash Markets, Derivatives, Internet

Trading, Depository Services, Portfolio Management Services, Equity Research and Analysis, NRI

Client Cell and Mutual Funds. The certification was obtained from the renowned United Kingdom

Accreditation Services (UKAS), based on the Assessment by Moody International Certification

Group through ICL Certifications Ltd.

The certificate was handed over at a function held in Trivandrum. Mr. Ashok Kumar Rout, Chief

Operating Officer of the Bombay Stock Exchange Ltd., was the Guest of Honour on the occasion.

Mr. Rajendran V, our Managing Director, received the certificate from Mr. Uwe Saelzle, Director of

Moody International Certification Group, Germany, in the presence of Mr. Sanjeev Chadha, CEO,

ICL Certifications Ltd., handling the Indian operations of the Moody International Certification

Group.

Mr. Dilip Jacob Mathew, our Vice President, handled ISO 9001:2008 implementation as the

Management Representative with assistance from Ms. Sangeetha, Sr. Executuve (QMS), and Mr. M.

Pradeep Kumar, Management Systems Consultant and Trainer. A dedicated team of Managers and

Executives, trained as Internal Quality Auditors in Capstocks, was involved in the Internal

Assessments and improvement processes.

47

Commenting on the certification, Rajendran V, our Managing Director said “We spent nearly 15

months to complete the ISO 9001:2008 certification process. There is a sea change in the

organizational efficiency and day-to-day operations in our Company. The process flow and our

organizational structure from top to bottom have been totally streamlined and the benefits will

definitely be reflected in offering better services with the utmost satisfaction to our clients. As a

result of ISO 9001:2008 implementation programme, Capstocks - having 75 branches covering India

and else where - has been able to improve continually its systems, processes and procedures at the

Head Office and its Branches with better review mechanisms.

With the ISO 9001:2008 recognition under our belt, Quality of Documentation and Communication

has improved. Capstocks will maintain the Quality Management System and also continually

improve the quality of service through regular Management Reviews and Internal Quality Audits. As

part of this project, emphasis is being given to imparting effective training and retraining for

Capstocks Team Members and systematic analysis of activities.

Quality policy

CAPSTOCKS is committed to render the best knowledge-based personalized services in stock

broking and related financial services, complying with all relevant requirements, by continually

improving the competence of manpower and effectiveness of quality management systems,

optimizing technology and infrastructure, thereby enhancing customer satisfaction.

48

Services

1. Online trading

Capstocks has a network of branches with online terminals of NSE and BSE in the Capital market

and Derivative segments. Our clients are assured of prompt order execution through dedicated

phones and expert dealers at our offices.

2. Internet trading

Capstocks offers Internet trading through this site. You can trade through the Internet from the

comforts of your office or home, anywhere in the world. Our dedicated IT systems ensure service up

time and speed, making Internet broking through Capstocks hassle-free. Using the 'easiest' facility

provided by CDSL, our clients can transfer the shares sold by them online without delivery

instruction slips. Additionally, digitally signed contract notes can be sent to clients through E-mail.

3. Depository Services

Capstocks is a member of the Central Depository Services Limited (CDSL), offer depository services

with minimum Annual Maintenance Charges and transaction charges. Account holders can view

their holding position through the Internet. We also offer the " e asi est " facility provided by CDSL

(electronic access to securities information and execution of secured transaction ) through which

clients can give delivery instructions via the Internet.

4. Derivative Trading

We offer trading in the futures and options segment of the National Stock Exchange(NSE). Through

the present derivative trading an investor can take a short-term view on the market for upto a three

months’ perspective by paying a small margin on the futures segment and a small premium in the

options segment. In the case of options, if the trade goes in the opposite direction the maximum loss

will be limited to the premium paid.

49

5. Knowledge Centre

Knowledge Centre activities are intended to provide systematic and structured services mainly to

new investors and also to young aspirant aiming for a career in financial markets. The centre has

three functional areas: the publication Division, the Training centre, and wealth management

advisory service which provide complete investment solutions to investors through knowledge based

personalized service.

6. Equity Research Department

We have a full-fledged Investment Research & Analysis Department to help our clients to make

investment decisions. Our clients can get information on any share they hold or plan to purchase. We

publish a monthly newsletter' CAPSTOCKS INFOLINE ' , which contains our views on the latest

trends in the markets, scrip recommendation, tutorials, news items etc. We also issue a daily

newsletter, ' CAPS TREND ' , which is available in our site . Besides we give intraday calls by SMS,

chat, etc. You can avail yourself of this service by calling :+91-471-2468160, 4013887

7. Portfolio Management services

Capstocks is a SEBI-approved portfolio manager offering discretionary and non-discretionary

schemes to its clients. Capstocks’ portfolio management team keeps track of the markets on a daily

basis and is exposed to a lot of information and analytic tools which an investor would not normally

have access to. Other technicalities pertaining to shares like dividends, rights, bonus, buy-back,

Mergers and Acquisitions are also taken care of by us. Maximize your returns by opting for our PMS

scheme. Please Call +91-471- 4013887,4013882

8. Commodity Trading *

You can trade in commodity futures like gold , silver, crude oil , rubber etc. and take advantage of

the extended trading hours (10 am to 11 pm ) in commodities trading. Do, please Call +91-471-

4013891,9847917187.

9. Mutual Funds, Bonds etc.

We also offer Mutual Funds and Bonds. You can select from a wide range of Mutual Funds and

Bonds available in the markets today. You can get the service by Calling : +91-471-

4013885,4013886,98473 19187.

50

10. NRI CELL

We have a well-organized NRI Cell functioning exclusively to meet the requirements of our clients

residing outside India. We are committed to provide them timely assistance by placing their orders,

giving them valuable suggestions concerning their investments etc. Also we help those NRI’s who

desire to open accounts on repatriation basis. Facilities are offered to those clients who are interested

in Internet trading by activating it, in co-ordination with the e-trading department.

11. Currency Trading

Capstocks is a member of currency derivatives segment of National Stock Exchange (NSE) and

MCX Stock Exchange (MCX-SX). Currency Derivatives are a new asset class which was earlier not

permitted for trading to all Indian residents. Currently the trading is based on four underlying

currencies viz., US Dollar, Euro, Pound sterling, Japanese Yen. Please Call +91-471-4093343,

09961886876.

12. Pan Service Agent of UTI

Capstocks & Securities (India) Pvt. Ltd. has become authorized PAN card service agent (PSA) of

UTI. Now pan applications can be submitted to any of the following offices, in addition to Head

office.( Sasthamangalam, Sreekaryam, Technopark, and Pattom, in Trivandrum) Kollam, Alappuzha,

Thiruvalla, Ernakulam, Thrissur, Irinjalakkuda, Thodupuzha, Calicut, Chennai RO, Mangalore, Navi

Mumbai, and Nagercoil RO. Capstocks offers this value added service to our privileged customers,

existing as well as new customers at nominal processing charges.

51

INDUSTRY PROFILE

The trading on stock exchanges in India used to take place through open outcry without use of

information technology for immediate matching or recording of trades. This was time consuming and

inefficient. This imposed limits on trading volumes and efficiency. In order to provide efficiency,

liquidity and transparency, NSE introduced a nation-wide on-line fully-automated screen based

trading system (SBTS) where a member can punch into the computer quantities of securities and the

prices at which he likes to transact and the transaction is executed as soon as it finds a matching sale

or buy order from a counter party. SBTS electronically matches orders on a strict price/time priority

and hence cuts down on time, cost and risk of error, as well as on fraud resulting in improved

operational efficiency. It allows faster incorporation of price sensitive information into prevailing

prices, thus increasing the informational efficiency of markets. It enables market participants,

irrespective of their geographical locations, to trade with one another simultaneously, improving the

depth and liquidity of the market. It provides full anonymity by accepting orders, big or small, from

members without revealing their identity, thus providing equal access to everybody. It also provides

a perfect audit trail, which helps to resolve disputes by logging in the trade execution process in

entirety. This sucked liquidity from other exchanges and in the very first year of its operation, NSE

became the leading stock exchange in the country, impacting the fortunes of other exchanges and

forcing them to adopt SBTS also.

Today India can boast that almost 100% trading take place through electronic order

matching. Technology was used to carry the trading platform from the trading hall of stock

exchanges to the premises of brokers. NSE carried the trading platform further to the PCs at the

residence of investors through the Internet and to handheld devices through WAP for convenience of

mobile investors. This made a huge difference in terms of equal access to investors in a

geographically vast country like India. NSE has main computer which is connected through Very

Small Aperture Terminal (VSAT) installed at its office. The main computer runs on a fault tolerant

STRATUS mainframe computer at the Exchange. Brokers have terminals (identified as the PCs in

the Figure 1) installed at their premises which are connected through VSATs/leased lines/modems.

An investor informs a broker to place an order on his behalf. The broker enters the order through his

PC, which runs under Windows NT and sends signal to the Satellite via VSAT/leased line/modem.

52

Indian stock market marks to be one of the oldest stock market in Asia. It dates back to the

close of 18th century when the East India Company used to transact loan securities. In the 1830s,

trading on corporate stocks and shares in Bank and Cotton presses took place in Bombay. Though the

trading was broad but the brokers were hardly half dozen during 1840and 1850.In 1860, the exchange

flourished with 60 brokers. In fact the 'Share Mania' in India began with the American Civil War

broke and the cotton supply from the US to Europe stopped.

Further, the brokers increased to 250. At the end of the war in 1874, the market found a place

in a street (now called Dalal Street). In 1887, "Native Share and Stock Brokers' Association" was

established. In 1895, the exchange acquired a premise in the street, which was inaugurated in 1899.

National Stock Exchange (NSE)

The National Stock Exchange of India (NSE) was incorporated in November 1992 as a tax-paying

company. It is recognized under Securities Contracts (Regulation) Act, 1956 in 1993 as a stock

exchange. In June 1994, it commenced operations in the Wholesale Debt Market (WDM). In

November, the same year, the Capital Market (Equities) segment commenced operations and the

Derivatives segment in June 2000.

Bombay Stock Exchange (BSE)

A very common name for all traders in the stock market, BSE, stands for Bombay Stock

Exchange. The oldest market not only in the country, but also in Asia. The early days of BSE was

known as "The Native Share & Stock Brokers Association." It was established in the year 1875 and

became the first stock exchange in the country to be recognized by the government. In 1956, BSE

obtained a permanent recognition from the Government of India under the Securities Contracts

(Regulation) Act, 1956.

53

THE MAIN PLAYERS IN THE INDUSTRY

The financials and investment industry is a highly competitive in nature with almost well

established firms diversifying and entering into this industry. As of today there are Over 2000

brokers, 10000 sub brokers and 1 crore investors. It is highly competitive with entry of new

aggressive players. Retail broking is highly fragmented industry with falling brokerages Value added

services and Online trading, the new fad.

INDIABULLS FINANCIAL SERVICES LTD.

Indiabulls is India’s leading Financial Services and Real Estate Company having presence

over 414 locations in more than 124 cities. Indiabulls serves the financial needs of more than

3,00,000 customers with its wide range of financial services and products from securities, derivatives

trading, depositary services, research & advisory services, insurance, consumer secured & unsecured

credit, loan against shares and mortgage & housing finance. The market capitalization of Indiabulls

is around USD 800 million, and the consolidated net worth of the company is around USD 500

million.

KARVY SECURITIES LTD

KARVY, is a premier integrated financial services provider, and ranked among the top five

in the country in all its business segments, services over 16 million individual investors in various

capacities, and provides investor services to over 300 corporates, comprising the who is who of

Corporate India. The birth of Karvy was on a modest scale in 1981. Karvy Consultants Limited.

Thus over the last 20 years Karvy has traveled the success route, towards building a reputation as an

integrated financial services provider, offering a wide spectrum of services.

INDIAINFOLINE

IndiaInfoline was founded by a group of professionals in 1995, a seemingly distant past in

the Internet age. Their meticulous research was published and distributed in printed form to a client

base comprising the who's who of Indian business including leading MNCs, investment banks and

consulting firms. The quality of research was highly acclaimed and soon became the industry

benchmark. Over the last few years, their research coverage has grown to cover practically all

companies, sectors, economy and financial markets. The breadth and depth of their content is

unmatched - stock markets, mutual funds, personal finance, taxation and economy.

54

SHARE KHAN

Share khan is a pioneer in equity market. Share khan is among the top 3 branded retail service

providers. Largest network of branded broking outlets in the country servicing 100,000 clients.

Sharekhan not only has a strong offline presence but also provides automated online trading

services. To sum up, Sharekhan brings to you a user- friendly online trading facility, coupled with a

wealth of content that will help you stalk the right shares. In fact Sharekhan runs India's largest chain

of share shops with around 250 outlets in 113 cities!

GEOJIT FINANCIAL SERVICES LTD

Today Geojit Financial Services Ltd is one of the largest and most respected retail brokerage

companies from India where Kerala state Industrial Development Corporation (KSIDC) has taken

equity participation making it the only brokerage company in India where a state financial

corporation has taken equity participation. Geojit serves more than 250,000 clients who are serviced

through 350 branch offices and handles trading turnover of more than US$ 3000 million per year. It

is also the first company to offer Internet based broking service in India.

SHAREWEALTH SECURITIES LTD

Share wealth Securities Ltd is the first corporate member of National Stock Exchange of India

Ltd, Bombay Stock Exchange Ltd and MCX Stock Exchange Ltd (MCX-SX) from THRISSUR, the

Cultural Capital of Kerala. Share wealth is also a Depository Participant with CDSL (Central

Depository Services (India) Ltd). Share wealth Securities Ltd has two group companies, Share

wealth Commodities Pvt Ltd (Member: MCX, NCDEX, NMCE, ICEX & NSEL) and Share wealth

Financial Services Ltd (AMFI Registered Mutual Fund Distributor). Share wealth has a group

(Overseas Joint Venture) company at Abu Dhabi, Share wealth Financial Consultancy LLC.

Registered & Corporate offices of Share wealth Group of companies are at Thrissur.

55

NET ASSET VALUE OF EQUITY DIVERSIFIED FUND

Graph No : 1

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

10

20

30

40

50

60

70

NAV of Canara Robeco equity diversified (G)

NAV

Interpretation

From the chart it shows the NAV of the Canara Robeco equity diversified (G) based on the past performance of the last three years. The lowest NAV is 30.27 and the largest value is 58.10.

Graph No : 2

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

kotak contra fund(G)

NAV

Interpretation

From the chart it shows the NAV of the kotak contra fund(G) based on the past performance of the last three years. The lowest NAV is 12.668 and the largest value is 24.82.

Graph No : 3

56

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

2

4

6

8

10

12

14

NAV of AIG India equity fund(G)

NAV

Interpretation

From the chart it shows the NAV of AIG India equity fund(G) based on the past performance of the last three years. The lowest NAV is 6.953 and the largest value is 13.27.

Graph No : 4

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

NAV of Templeton india equity (G)

NAV

Interpretation

From the chart it shows the NAV of Templeton india equity (G) based on the past performance of the last three years. The lowest NAV is 13.52 and the largest value is 22.09.

Graph No : 5

57

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

2

4

6

8

10

12

14

16

18

NAV of Tata capital builder fund (G)

NAV

Interpretation

From the chart it shows the NAV of Tata capital builder fund (G) based on the past performance of the last three years. The lowest NAV is 7.961and the largest value is 16.46.

Graph No : 6

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

NAV of birla sunlife next generation fund(G)

NAV

Interpretation

From the chart it shows the NAV of Birla Sunlife next generation fund (G) based on the past performance of the last three years. The lowest NAV is 13.31 and the largest value is 26.88.

Graph No : 7

58

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

10

20

30

40

50

60

70

NAV of sbi magnum contra fund(G)

NAV

Interpretation

From the chart it shows the NAV of SBI magnum contra fund(G) based on the past performance of the last three years. The lowest NAV is 36.66 and the largest value is 65.58.

Graph No : 8

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

10

20

30

40

50

60

70

80

NAV of UTI MNC fund (G)

NAV

Interpretation

From the chart it shows the NAV of UTI MNC fund (G) based on the past performance of the last three years. The lowest NAV is 32.98 and the largest value is 70.06.

Graph No : 9

59

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

23

24

25

26

27

28

29

30

NAV of escorts oppertunities fund(G)

NAV

Interpretation

From the chart it shows the NAV of Escorts opportunities fund(G) based on the past

performance of the last three years. The lowest NAV is 25.114 and the largest value is 29.26.

Graph No : 10

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

NAV of Tata contra fund (G)

NAV

Interpretation

From the chart it shows the NAV of Tata contra fund (G) based on the past performance of

the last three years. The lowest NAV is 9.49 and the largest value is 19.56.

60

NET ASSE VALUE OF LARGE CAP FUNDS

Graph no:1

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

2

4

6

8

10

12

14

16

18

NAV of ICICI Prudential focused blue chip Equity fund

NAV

Interpretation

The graph shows the NAV of ICICI Prudential focused blue chip Equity fund . the lowest NAV is 9.16 and largest NAV is 17.09.

Graph No: 2

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

35

NAV of UTI Oppertunities fund(G)

NAV

Interpretation

The graph shows the NAV of UTI Opportunities fund(G). the lowest NAV is 15.43 and largest NAV is 29.78.

61

Graph No:3

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

35

40

45

NAV of Fidelity Equity fund

NAV

Interpretation

The graph shows the NAV of Fidelity Equity fund. the lowest NAV is 19.07 and largest NAV is 39.31.

Graph No:4

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

50

100

150

200

250

NAV of Franklin Indian blue chip fund (G)

NAV

Interpretation

The graph shows the NAV of Franklin Indian blue chip fund (G). the lowest NAV is 127.15 and largest NAV is 232.39.

62

Graph No:5

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

50

100

150

200

250

NAV of HDFC Top 200 fund (G)

NAV

Interpretation

The graph shows the NAV of HDFC Top 200 fund (G). the lowest NAV is 115.48 and largest NAV is 236.07.

Graph No:6

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

2

4

6

8

10

12

14

16

NAV of JP MORGAN INDIA EQUITY FUND

NAV

Interpretation

The graph shows the NAV of JP MORGAN INDIA EQUITY FUND, the lowest NAV is 7.75 and largest NAV is 15.02.

Graph No:3

63

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

2

4

6

8

10

12

14

16

18

NAV of RELLIANCE QUANT PLUS FUND RETAIL PLAN [G]

NAV

Interpretation

The graph shows the NAV of RELLIANCE QUANT PLUS FUND RETAIL PLAN [G], the lowest NAV is 7.79 and largest NAV is 15.60.

Graph No:3

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

35

40

45

50

NAV of ING Core EQUITY FUND

NAV

Interpretation

The graph shows the NAV of ING Core Equity fund , the lowest NAV is 23.18 and largest NAV is 43.18.

Graph No:3

64

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

35

40

45

NAV of HSBC INDIA OPPORTUNITIES FUND

NAV

Interpretation

The graph shows the NAV of HSBC INDIA OPPORTUNITIES FUND , the lowest NAV is 22.84 and largest NAV is 39.12.

Graph No:3

May

-09

Jul-0

9

Sep-0

9

Nov-09

Jan-1

0

Mar

-10

May

-10

Jul-1

0

Sep-1

0

Nov-10

Jan-1

1

Mar

-11

May

-11

Jul-1

1

Sep-1

1

Nov-11

Jan-1

2

Mar

-12

0

5

10

15

20

25

30

35

40

45

NAV of BNP PARIBAS EQUITY FUND

NAV

Interpretation

The graph shows the NAV of BNP PARIBAS EQUITY FUND , the lowest NAV is 22.64 and largest NAV is 38.74.

65

1.Risk Analysis- Mean return of Equity Diversified Funds

Table no : 1

Graph No : 1

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India

equity

fund(G

)

UTI MNC fu

nd (G)

Templet

on india

equity

(G)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

0

0.5

1

1.5

2

2.5

Risk Analysis- Mean return of Equity Diversified Funds

Mean

Interpretation of data

From the above table it is understood that , UTI MNC fund (G) having the high return(2.271), and

Templeton India equity (G) (.3782) considered to be the poorest according to their return.

2. Variance of equity diversified funds

Table No : 2

66

Schemes MeanCanara Robeco equity diversified (G) 1.9091Tata contra fund (G) 1.9954Kotak contra fund(G) 1.6222AIG India equity fund(G) 1.832UTI MNC fund (G) 2.271Templeton India equity (G) 0.3782Tata capital builder fund (G) 1.8488Birla sunlife next generation fund(G) 2.0243SBI magnum contra fund(G) 1.2234Escorts oppertunities fund(G) 0.41807

Graph No : 2

canar

a robec

o equity

dive

rsifi

ed (G

)

Tata

contra

fund (G

)

kota

k contra

fund(G

)

AIG In

dia eq

uity fu

nd(G)

UTI M

NC fund (G

)

Tem

pleton in

dia eq

uity (G

)

tata

capita

l build

er fu

nd (G)

birla s

unlife n

ext g

ener

ation fu

nd(G)

sbi m

agnum

contra

fund(G

)

esco

rts o

ppertu

nities

fund(G

)0

10

20

30

40

50

60

Variance of equity diversified funds

Variance

Interpretation

From the table it shows that the Tata capital builder fund having the highest variance (52.697) and Escorts opportunities fund shows the lowest variance (5.2) during the period of the study.

3.Covariance of equity diversified funds

67

schemes VarianceCanara Robeco equity diversified (G) 29.309Tata contra fund (G) 36.969Kotak contra fund(G) 46.511AIG India equity fund(G) 34.8278UTI MNC fund (G) 19.33Templeton India equity (G) 47.57Tata capital builder fund (G) 52.697Birla sunlife next generation fund(G) 32.682SBI magnum contra fund(G) 44.73Escorts oppertunities fund(G) 5.2

Table No : 3

Graph No: 3

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India

equity

fund(G

)

UTI MNC fu

nd (G)

Templet

on india

equity

(G)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

-1

-0.5

0

0.5

1

1.5

2

Covariance

Covariance

Interpretation

Co-variance helps in finding out the interactive risk. From the graph it shows that the co-variance

except Templeton India equity funds are positive. It reveals that the interactive risk of Templeton is

negative and all others are positive.

4.Standard Deviation of equity diversified funds

68

schemes CovarianceCanara Robeco equity diversified (G) 1.217Tata contra fund (G) 0.4759Kotak contra fund(G) 1.339AIG India equity fund(G) 1.231UTI MNC fund (G) 0.7063Templeton India equity (G) -0.631Tata capital builder fund (G) 1.498Birla sunlife next generation fund(G) 1.242SBI magnum contra fund(G) 1.376Escorts oppertunities fund(G) 0.244

Table No : 4

Graph No: 4

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India

equity

fund(G

)

UTI MNC fu

nd (G)

Templet

on india

equity

(G)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

012345678

Standard Deviation

standard Deviation

Interpretation of data

Escorts Oppertunities fund is having the least SD (2.281) in this category, so the return tends to

stable.Tata Capital buider fund is having the highest SD (7.225). So it is the most risky fund in this

category.

5.Beta of equity diversified funds

69

schemes Standard DeviatioCanara Robeco equity diversified (G) 5.413Tata contra fund (G) 6.08Kotak contra fund(G) 6.8198AIG India equity fund(G) 5.901UTI MNC fund (G) 4.397Templeton India equity (G) 6.897Tata capital builder fund (G) 7.225Birla sunlife next generation fund(G) 5.71SBI magnum contra fund(G) 6.668Escorts oppertunities fund(G) 2.281

Table No : 5

Graph No: 4

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India

equity

fund(G

)

UTI MNC fu

nd (G)

Templet

on india

equity

(G)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

-0.02-0.01

00.010.020.030.040.050.06

Beta

Beta

Interpretation of data

Beta of a fund indicates the market risk ie., volatility of return in relation to market return. Tata

contra fund is having the a lower beta value (-0.0132) shows opposite movement with the

market..Hence the market risk is low. Sbi magnum having highest beta value (.0468). So market

movements are more reflected in this fund’s return.

CAGR of equity diversified funds

70

schemes BetaCanara Robeco equity diversified (G) 0.0415Tata contra fund (G) 0.0128Kotak contra fund(G) 0.0288AIG India equity fund(G) 0.0354UTI MNC fund (G) 0.0365Templeton India equity (G) -0.0132Tata capital builder fund (G) 0.0273Birla sunlife next generation fund(G) 0.038SBI magnum contra fund(G) 0.0308Escorts oppertunities fund(G) 0.0468

Table No : 6

Graph No: 6

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India e

quity fu

nd(G)

UTI MNC fu

nd (G)

Templet

on india e

quity (G

)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

0.00%5.00%

10.00%15.00%20.00%25.00%30.00%

CAGR

CAGR

Interpretation of data

From the table it is understood that UTI MNC fund is having the high growth rate of 28.55%,

and Escorts opportunities fund having the lower growth rate of 4.68% during the period of study.

Alpha of equity diversified funds

Table No : 7

71

schemes CAGRCanara Robeco equity diversified (G) 22.75%Tata contra fund (G) 23.44%Kotak contra fund(G) 17.64%AIG India equity fund(G) 21.35%UTI MNC fund (G) 28.55%Templeton India equity (G) 1.39%Tata capital builder fund (G) 20.48%Birla sunlife next generation fund(G) 24.09%SBI magnum contra fund(G) 12.51%Escorts oppertunities fund(G) 4.68%

schemes alphacanara robeco equity diversified (G) 0.009722Tata contra fund (G) 0.063409kotak contra fund(G) 0.042231AIG India equity fund(G) 0.024097UTI MNC fund (G) 0.006059Templeton india equity (G) 0.093942tata capital builder fund (G) 0.038478birla sunlife next generation fund(G) 0.012027sbi magnum contra fund(G) 0.051269escorts oppertunities fund(G) 0.069384

Graph No : 7

canara

robeco

equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG India

equity

fund(G

)

UTI MNC fu

nd (G)

Templet

on india

equity

(G)

tata c

apita

l build

er fund (G

)

birla su

nlife nex

t gen

eration fu

nd(G)

sbi m

agnum co

ntra fu

nd(G)

escorts

oppertunities

fund(G)

0

0.02

0.04

0.06

0.08

0.1

Alpha of equity diversified funds

alpha

Interpretation of data

Among the funds Templeton India Equity fund is having high positive alpha (.0939), shows it

earned more than the rate of market risk. Templeton shows the lowest Alpha, it reveals that the fund

earned good return to the market risk involved in it .

Sharp Ratio of Equity diversified fund

Table No : 8

72

schemes Mean Risk free rate

standard Deviation

Sp

canara robeco equity diversified (G) 1.9091 0.26 5.413 0.304655Tata contra fund (G) 1.9954 0.26 6.08 0.285428kotak contra fund(G) 1.6222 0.26 6.8198 0.199742AIG India equity fund(G) 1.832 0.26 5.901 0.266396UTI MNC fund (G) 2.271 0.26 4.397 0.457357Templeton india equity (G) 0.3782 0.26 6.897 0.017138tata capital builder fund (G) 1.8488 0.26 7.225 0.219903birla sunlife next generation fund(G) 2.0243 0.26 5.71 0.308984sbi magnum contra fund(G) 1.2234 0.26 6.668 0.144481escorts oppertunities fund(G) 0.41807 0.26 2.281 0.069299

Graph No : 8

canara

robeco

equity

diversi

fied (G

)

Tata c

ontra fu

nd (G)

kotak

contra

fund(G)

AIG India e

quity fu

nd(G)

UTI MNC fu

nd (G)

Templet

on india e

quity (G

)

tata c

apita

l build

er fund (G

)

birla su

nlife next

genera

tion fund(G)

sbi magn

um contra

fund(G)

escorts

oppertunities

fund(G)

0

0.1

0.2

0.3

0.4

0.5

Sharp Ratio

Sp

Interpretation of data

Sharpe Ratio indicates the excess return per unit of total risk (Standard Deviation) assumed by the

investor over some risk free rate of return.

UTI MNC fund (0.45) is having the highest Sharpe ratio. Hence it is the best fund. Templeton India Equity

fund is considered to be worst performers with this ratio.

Treynor Ratio of Equity Diversified fund

Table No : 9

schemes Mean Rf Beta Treynor

73

RatioCanara robeco equity diversified (G) 1.9091 0.26 0.0415 39.73735Tata contra fund (G) 1.9954 0.26 0.0128 135.5781Kotak contra fund(G) 1.6222 0.26 0.0288 47.29861AIG India equity fund(G) 1.832 0.26 0.0354 44.40678UTI MNC fund (G) 2.271 0.26 0.0365 55.09589Templeton india equity (G) 0.3782 0.26 -0.0132 -8.95455Tata capital builder fund (G) 1.8488 0.26 0.0273 58.1978Birla sunlife next generation fund(G) 2.0243 0.26 0.038 46.42895SBI magnum contra fund(G) 1.2234 0.26 0.0308 31.27922Escorts opportunities fund(G) 0.41807 0.26 0.0468 3.377564

Graph No : 9

canar

a robec

o equity

diversi

fied (G

)

Tata

contra

fund (G

)

kotak

contra

fund(G

)

AIG In

dia eq

uity fu

nd(G)

UTI M

NC fund (G

)

Templet

on india

equity

(G)

tata c

apita

l build

er fu

nd (G)

birla s

unlife nex

t gen

erati

on fund(G

)

sbi m

agnum co

ntra fu

nd(G)

esco

rts opper

tunities

fund(G

)-20

020406080

100120140160

Treynor Ratio

Treynor Ratio

Interpretation

Treynor Ratio indicates the excess return per unit of market risk (beta) assumed by the investor over some risk

free rate of return. Here risk free rate of return is 9.5%.

Tata contra fund has the highest Treynor ratio (135.57) & Templeton India Equity fund is having negative

ratio of 8.95.

Analysis of Large cap fund

Table No :1

74

Schemes MeanICICI Prudential focused blue chip Equity fund 1.735UTI Oppertunities fund(G) 1.96Fedelity Equity fund 1.836Franklin Indian blue chip fund (G) 1.593HDFC Top 200 fund (G) 1.832JP MORGAN INDIA EQUITY FUND 1.545RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 1.676ING Core Equity Fund 1.474HSBC INDIA OPPORTUNITIES FUND 1.316BNP PARIBAS EQUITY FUND 1.431

Graph No : 1

ICIC

I Pru

dential

focu

sed b

lue

chip

Equity

fund

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUIT

Y FUND0

0.51

1.52

2.5

Mean

Mean

Interpretation of data

From the above table it is understood that , UTI Opportunities fund(G)having the high return(1.96), and

HSBC INDIA OPPORTUNITIES FUND (1.431) considered to be the poorest according to their return.

Variance Of Large cap fund

Table No : 2

75

Schemes Variance

ICICI Prudential focused blue chip Equity fund 25.573UTI Oppertunities fund(G) 36.434Fedelity Equity fund 31.474Franklin Indian blue chip fund (G) 34.779HDFC Top 200 fund (G) 44.097JP MORGAN INDIA EQUITY FUND 30.399RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 73.315ING Core Equity Fund 35.342HSBC INDIA OPPORTUNITIES FUND 22.44BNP PARIBAS EQUITY FUND 54.7

Graph No : 2

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0

20

40

60

80

Variance

Variance

Interpretation

From the table it shows that the RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] having the

highest variance (73.315) and HSBC INDIA OPPORTUNITIES FUND shows the lowest variance

(5.2) during the period of the study.

Table No: 3

Standard Deviation of Large cap fund

Schemes SDICICI Prudential focused blue chip Equity fund 5.056

76

UTI Oppertunities fund(G) 6.036Fedelity Equity fund 5.61Franklin Indian blue chip fund (G) 5.897HDFC Top 200 fund (G) 6.641JP MORGAN INDIA EQUITY FUND 5.514RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 8.56ING Core Equity Fund 5.95HSBC INDIA OPPORTUNITIES FUND 4.738BNP PARIBAS EQUITY FUND 7.396

Graph No : 3

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0

2

4

6

8

Standard Deviation

SD

Interpretation of data

HSBC INDIA OPPORTUNITIES FUND fund is having the least SD (4.738) in this category, so the

return tends to stable. RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] is having the highest SD (8.56).

So it is the most risky fund in this category.

Covariance of Large cap fund

Table No:4

77

schemes CovarianceICICI Prudential focused blue chip Equity fund 1.0669UTI Oppertunities fund(G) 1.293Fedelity Equity fund 0.9903Franklin Indian blue chip fund (G) 0.888HDFC Top 200 fund (G) 1.268JP MORGAN INDIA EQUITY FUND 1.138RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 1.206ING Core Equity Fund 1.27HSBC INDIA OPPORTUNITIES FUND 0.998BNP PARIBAS EQUITY FUND 1.286

Graph No : 4

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0

0.20.40.60.8

11.21.4

Covariance

Covariance

Interpretation

Co-variance helps in finding out the interactive risk. From the graph it shows that the co-variance of

all funds are positive. It reveals that the interactive risk of all funds are positive.

Beta of Large cap fund

Table No:5

78

Graph No : 5

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0

0.010.020.030.040.05

Beta

Beta

Interpretation of data

Beta of a fund indicates the market risk ie., volatility of return in relation to market return.

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] is having the a lower beta value (.0165) shows opposite

movement with the market..Hence the market risk is low. HSBC INDIA OPPORTUNITIES FUND having

highest beta value (.0435). So market movements are more reflected in this fund’s return.

79

Schemes BetaICICI Prudential focused blue chip Equity fund 0.041

7UTI Oppertunities fund(G) 0.035

4Fedelity Equity fund 0.031

5Franklin Indian blue chip fund (G) 0.025

5HDFC Top 200 fund (G) 0.028

9JP MORGAN INDIA EQUITY FUND 0.037

1RELLIANCE QUANT PLUS FUND RETAIL PLAN [G]

0.0165

ING Core Equity Fund 0.0359

HSBC INDIA OPPORTUNITIES FUND 0.0435

BNP PARIBAS EQUITY FUND 0.0235

Table No :6

Alpha of Large Cap fund

Table no : 6

schemes alphaICICI Prudential focused blue chip Equity fund 0.016601UTI Oppertunities fund(G) 0.019566Fedelity Equity fund 0.031116Franklin Indian blue chip fund (G) 0.048329HDFC Top 200 fund (G) 0.036005JP MORGAN INDIA EQUITY FUND 0.031631RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 0.061296ING Core Equity Fund 0.036033HSBC INDIA OPPORTUNITIES FUND 0.031704BNP PARIBAS EQUITY FUND 0.055322

Graph No :6

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0

0.010.020.030.040.050.060.07

alpha

alpha

Interpretation of data

80

Among the funds RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] is having high positive alpha (.0612),

shows it earned more than the rate of market risk. ICICI Prudential focused blue chip Equity fund shows

the lowest Alpha (.0166) it reveals that the fund earned good return to the market risk involved in it .

Compounded Annual Growth Rate of Large Cap Fund

Table No :7

schemes CAGRICICI Prudential focused blue chip Equity fund 20.51

%UTI Oppertunities fund(G) 23.04

%Fedelity Equity fund 21.55

%Franklin Indian blue chip fund (G) 17.98

%HDFC Top 200 fund (G) 20.52

%JP MORGAN INDIA EQUITY FUND 17.59

%RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 17.90

%ING Core Equity Fund 16.35

%HSBC INDIA OPPORTUNITIES FUND 15.00

%BNP PARIBAS EQUITY FUND 14.47

%

Graph No : 7

81

ICIC

I Pru

dential

focu

sed b

lue c

hip Eq

uity fu

nd

UTI Opper

tuniti

es fu

nd(G)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian b

lue c

hip fu

nd (G)

HDFC To

p 200 fu

nd (G)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RET

AIL PLA

N [G]

ING C

ore Eq

uity Fu

nd

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIB

AS EQUITY

FUND0.00%

5.00%10.00%15.00%20.00%25.00%

CAGR

CAGR

Interpretation of data

From the table it is understood that UTI Opportunities fund is having the high growth rate of

23.04% and BNP Paribas having the lower growth rate of 14.47% during the period of the study.

Sharp ratio of Largecap funds

schemes Mean Rf SD SpICICI Prudential focused blue chip Equity fund 1.735 0.26 5.056 0.2917326UTI Oppertunities fund(G) 1.96 0.26 6.036 0.2816435Fedelity Equity fund 1.836 0.26 5.61 0.2809269Franklin Indian blue chip fund (G) 1.593 0.26 5.897 0.2260471HDFC Top 200 fund (G) 1.832 0.26 6.641 0.2367113JP MORGAN INDIA EQUITY FUND 1.545 0.26 5.514 0.2330432RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 1.676 0.26 8.56 0.1654206ING Core Equity Fund 1.474 0.26 5.95 0.2040336HSBC INDIA OPPORTUNITIES FUND 1.316 0.26 4.738 0.2228789BNP PARIBAS EQUITY FUND 1.431 0.26 7.396 0.1583288

Graph No:

82

ICICI Pru

dential

focu

sed blue c

hip Equity

fund

UTI Opper

tunities

fund(G

)

Fedeli

ty Eq

uity fu

nd

Fran

klin In

dian blue c

hip fund (G

)

HDFC To

p 200 fund (G

)

JP M

ORGAN INDIA

EQUITY

FUND

RELLIA

NCE QUANT P

LUS F

UND RETAIL

PLAN [G

]

ING Core

Equity

Fund

HSBC IN

DIA O

PPORTUNITI

ES FU

ND

BNP PARIBAS EQUITY

FUND

00.05

0.10.15

0.20.25

0.30.35

Sharp Ratio

Sharp Ratio

Interpretation of data

Sharpe Ratio indicates the excess return per unit of total risk (Standard Deviation) assumed by the

investor over some risk free rate of return. ICICI (0.291) is having the highest Sharpe ratio. Hence it is the

best fund. BNP Paribas fund is considered to be worst performers with this ratio.

Treynor Ratio of Large Cap funds.

schemes Mean Rf Beta TpICICI Prudential focused blue chip Equity fund 1.735 0.26 0.0417 35.3717UTI Oppertunities fund(G) 1.96 0.26 0.0354 48.0226Fedelity Equity fund 1.836 0.26 0.0315 50.03175Franklin Indian blue chip fund (G) 1.593 0.26 0.0255 52.27451HDFC Top 200 fund (G) 1.832 0.26 0.0289 54.39446JP MORGAN INDIA EQUITY FUND 1.545 0.26 0.0371 34.63612RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] 1.676 0.26 0.0165 85.81818ING Core Equity Fund 1.474 0.26 0.0359 33.81616HSBC INDIA OPPORTUNITIES FUND 1.316 0.26 0.0435 24.27586BNP PARIBAS EQUITY FUND 1.431 0.26 0.0235 49.82979

83

ICICI Pruden

tial focused

blue chip Eq

uity fu

nd

UTI Oppert

unities fund(G)

Fedelit

y Equity

fund

Franklin

Indian

blue chip fu

nd (G)

HDFC To

p 200 fund (G

)

JP MORGAN IN

DIA EQUITY

FUND

RELLIANCE Q

UANT PLU

S FUND RETA

IL PLA

N [G]

ING Core Eq

uity Fu

nd

HSBC IN

DIA OPPORTUNITIE

S FUND

BNP PARIBAS EQUITY

FUND

020406080

100

Treynor Ratio

Tp

Interpretation

Treynor Ratio indicates the excess return per unit of market risk (beta) assumed by the investor over some risk

free rate of return. Here risk free rate of return is 9.5%.

Reliance Quant fund has the highest Treynor ratio (85.81) & HSBC India Equity fund is having lowest ratio

of 24.27.

RANKING OF EQUITY DIVERSIFIED FUND

schemes

CAGR Mean Variance SD Covariance

Beta alpha Sharp ratio

Treynor ratio

Rank

canara robeco equity diversified (G)

22.75% 1.909 29.309 5.41 1.217 0.0415 0.0097 0.304 39.737 4

Tata contra fund (G)

23.44% 1.995 36.969 6.08 0.475 0.0128 0.0634 0.285 135.57 3

84

kotak contra fund(G)

17.64% 1.622 46.511 6.81 1.339 0.0288 0.0422 0.199 47.298 7

AIG India equity fund(G)

21.35% 1.832 34.827 5.9 1.231 0.0354 0.024 0.266 44.406 5

UTI MNC fund (G)

28.55% 2.271 19.33 4.39 0.706 0.0365 0.006 0.457 55.095 1

Templeton india equity (G)

1.39% 0.3782 47.57 6.89 -0.631 -0.013 0.0939 0.017 -8.954 10

tata capital builder fund (G)

20.48% 1.848 52.697 7.22 1.498 0.0273 0.0384 0.219 58.197 6

birla sunlife next generation fund(G)

24.09% 2.024 32.682 5.71 1.242 0.038 0.012 0.308 46.428 2

sbi magnum contra fund(G)

12.51% 1.223 44.73 6.66 1.376 0.0308 0.0512 0.144 31.279 8

escorts oppertunities fund(G)

4.68% 0.418 5.2 2.28 0.244 0.0468 0.0693 0.069 3.377 9

RANKING OF LARGE CAP FUNDS

schemes CAGR MEAN

VARI-ANCE

SD COVAR-IANCE

BETA ALPHA

SHARP RATIO

TEYNOR RATIO

RANK

ICICI Prudential focused blue chip Equity fund

20.51% 1.735 25.573 5.056 1.0669 0.0417 0.0166 0.291 35.371 4

UTI Oppertunities fund(G) 23.04% 1.96 36.434 6.036 1.293 0.0354 0.0195 0.281 48.022 1

85

Fedelity Equity fund 21.55% 1.836 31.474 5.61 0.9903 0.0315 0.0311 0.280

50.031 2

Franklin Indian blue chip fund (G) 17.98% 1.593 34.779 5.897 0.888 0.025 0.0483 0.226 52.274 5

HDFC Top 200 fund (G) 20.52% 1.832 44.097 6.641 1.268 0.028 0.0360 0.236 54.394

3

JP MORGAN INDIA EQUITY FUND

17.59% 1.545 30.399 5.514 1.138 0.0371 0.0316 0.23334.636 7

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G]

17.90% 1.676 73.315 8.56 1.206 0.0165 0.0612 0.16585.818

6

ING Core Equity Fund

16.35% 1.474 35.342 5.95 1.27 0.035 0.0360 0.204 33.816 8

HSBC INDIA OPPORT-UNITIES FUND

15.00% 1.316 22.44 4.738 0.998 0.043 0.0317 0.222 24.275 9

BNP PARIBAS EQUITY FUND

14.47% 1.431 54.7 7.396 1.286 0.023 0.0553 0.15849.829 10

FINDINGS

From the analysis of the data regarding the selected equity funds over a period of one year from 1-

May-2009 to 30-April-2011, the following things were found.

Risk Analysis

1.Total Risk (Standard Deviation):

Equity Diversified funds –

86

Escorts oppertunities fund(G) (2.281) , is having the least standard deviaton . Birla sun life fund(5.47)

shows highest volatility of returns.HDFC Equity Fund, Tata Contra fund, Templeton fund also have

SD higher than their mean returns.

Large cap funds

HSBC INDIA OPPORTUNITIES FUND is having the least SD(4.738) in this category, so the return

tends to stable. RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] is having the highest SD (8.56). So it is

the most risky fund in this category. No mutual fund investment is risk free. The degree of risk varies

from fund to fund irrespective of the category of fund.

2.Market Risk (Beta):

Equity Diversified funds-

Tata contra fund (G) is having the a lower beta value (0.0128).Hence the market risk is low.

Escorts opportunities fund(G) having highest beta value (0.0468). So market movements are more

reflected in this fund’s return.

Large cap fund

HSBC INDIA OPPORTUNITIES FUND shows high beta So the fund is more responsive to market

fluctuation and therefore market risk is high to this fund compared to other funds in the category

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G is the most defensive fund in this category as it is less

sensitive to market (0.0165).

3. Alpha:

Equity Diversified funds

A high value of alpha implies that the fund has performed better than the expectation given by its

beta. UTI MNC fund (G) having the least alpha and Templeton having the highest alpha under this category.

Large cap fund

87

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] (0.06129) having the highest alpha

and ICICI Prudential focused blue chip Equity fund (0.016601) having the lowest alpha indicates

these fund earned less than expectations.

Risk Adjusted Return of the Funds

4.Sharpe Ratio

Equity Diversified funds-

UTI MNC fund (G) (0.457) is having the highest sharpe ratio .hence it is the best fund. Templeton india

equity (G) having the lowest ratio (0.0171)and it is considered to be worst performers with this ratio.

Large cap fund

ICICI Prudential focused blue chip Equity fund (0.29) is the best performer ,and RELLIANCE

QUANT PLUS FUND RETAIL PLAN [G] (0.165) fund is the worst performer under this category

5.Treynor Ratio:

Equity Diversified funds-

Tata contra fund (G) has the highest Treynor ratio and Templeton india equity (G) fund

considered to be the worst performers in this category.

Large cap fund

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G] is the best performer and HSBC INDIA

OPPORTUNITIES FUND is the worst performer under this category.

6. Growth Rate Analysis (CAGR):

Equity Diversified funds-

UTI MNC fund is having the high growth rate of 28.55% . It is clear that all the fund

Templeton Equity fund having the lowest market growth rate of 1.39% during that period.

88

Large cap funds.

UTI Oppertunities fund(G) ( 23.04 ) is having the high growth rate , BNP PARIBAS

EQUITY FUND having the lowest growth rate of 14.47 %.

SUGGESTIONS

1. Investors who would like to invest in equity diversified mutual fund ,the best choice is UTI

MNC fund(G) which is ranked first in this category. Birla sunlife next generation fund(G)comes

second in ranking.

Investors who would like to invest in Largecap fund UTI Oppertunities fund(G) and Fidelity

Equity fund , as both funds ranked 1st & 2nd respectively.

89

2. If the investor is risk averse it is better to invest in diversified funds as they show less

volatility compared Large cap funds.

And if the investor is looking for high return sector specific fund is the avenue.

4 From the analysis it is found that no fund is risk free . Each fund has its own risk return

characteristics. So the choice of any scheme would depend on the investment objective, risk

affordability, financial capacity etc. of the investor. The reputation and management skill of the

Asset Management Company are also to be taken in to account.

5 Growth rate is more important than the size of NAV. A lower NAV scheme growing at faster

rate bring more benefit to an investor than a scheme with higher NAV growing at a lower rate.

CONCLUSION

The study entitled “Performance evaluation of selected mutual funds within the framework

of risk and return- – A study held at Capstock securities Ltd ,Coimbatore ” was done with an

objective of analysing the performance of the selected equity growth mutual funds for a period from

90

1st May 2009 to 30th March 2012. The objective of the study was to evaluate and compare the

performance of the selected schemes under 2 Category of Equity funds; Equity Diversified, Large

cap funds and suggest the best funds in each category by analyzing the return, risk and growth

aspects.

While evaluating the performance, Under Equity diversified funds UTI

Opportunities fund gives the highest mean returns (2.27) and having the higher growth rate (28.55%)

under this category. The riskiest fund under this category is Escorts opportunities fund which gives

lowest mean returns (.418) and having only 4.68% growth rate over the period of three years

performance.

Canara Robeco equity diversified (G)month NAV return

(X) dx dx^2Return (Y) dy dx*dy

May-09 30.27 Jun-09 37.44

123.6901

2 21.78099 474.41141.127349

1.034662322.5359663

5Jul-09 37.66

30.59293

3 -1.3162 1.732388-0.14652

-0.23920460.31484160

1Aug-09 39.82 5.72710

6 3.817971 14.57690.360529

0.267841721.02261196

7

91

Sep-09 43 7.98593 6.07680 36.9275 0.04141 -0.051275 -0.31159Oct-09 44.62 3.76744

2 1.858307 3.4533040.4381

0.3454130.64188334

8Nov-09 45.02 0.89645

9 -1.01268 1.0255130.3739

0.281213 -0.28477766Dec-09 46.72

3.7761 1.866965 3.4855560.3089

0.2162130.40366199

8Jan-10 48.92 4.70890

4 2.799769 7.8387070.01627

-0.076417 -0.21394996Feb-10 45.72

-6.54129 -8.45043 71.40971-0.1654

-0.2580872.18094532

9Mar-10 48.11 5.22747

2 3.318337 11.011360.0476

-0.045087 -0.14961384Apr-10 50.8 5.59135

3 3.682218 13.558730.3089

0.2162130.79614343

3May-10 50.52

-0.55118 -2.46032 6.0531550.01627

-0.0764170.18800997

6Jun-10 51.14 1.22723

7 -0.6819 0.464985-0.01644

-0.1091270.07441351

2Jul-10 53.34 4.30191

6 2.392781 5.7254020.20462

0.111933 0.26783119Aug-10 54.39 1.96850

4 0.059369 0.0035250.04885

-0.043837 -0.00260256Sep-10 58.1 6.82110

7 4.911972 24.127470.0316

-0.061087 -0.30005762Oct-10 57.77 -0.56799 -2.47712 6.13613 0.5275 0.434813 -1.07708451Nov-10 57.91

0.24234 -1.66679 2.778205-0.004

-0.0966870.16115737

8Dec-10 56.09

-3.14281 -5.05194 25.52213-0.1163

-0.2089871.05579037

1Jan-11 54.71 -2.46033 -4.36947 19.09224 0.21031 0.117623 -0.51394977Feb-11 52.33

-4.35021 -6.25935 39.1794-0.5325

-0.6251873.91326124

7Mar-11 52.58 0.47773

7 -1.4314 2.048899-0.075

-0.1676870.24002676

3Apr-11 55.72 5.97185

2 4.062717 16.505670.41605

0.3233631.31373249

2May-11 54.43

-2.31515 -4.22428 17.84456-0.0756

-0.1682870.71089177

3Jun-11 54.48 0.09186

1 -1.81727 3.302484-0.0146

-0.1072870.19496986

4Jul-11 56.03 2.84508

1 0.935946 0.8759940.07534

-0.017347 -0.01623585Aug-11 52.7

-5.94324 -7.85238 61.65987-0.1369

-0.2295871.80280429

6Sep-11 52.65

-0.09488 -2.00401 4.016063-0.4249

-0.5175871.03725038

3Oct-11 52.23

-0.79772 -2.70686 7.327068-0.0429

-0.1355870.36701445

7Nov-11 51.82 -0.78499 -2.69412 7.258307 0.46348 0.370793 -0.99896249

92

Dec-11 49.32-4.82439 -6.73353 45.34039

-0.4782-0.570887

3.844083101

Jan-12 50.63 2.656123 0.746988 0.557991

-0.198-0.290687 -0.21713978

Feb-12 56.04 10.68536 8.776229 77.0222

0.540180.447493

3.927301227

Mar-12 55.05 -1.7666 -3.67573 13.51099 0.18203 0.089343 -0.32840077Apr-12 55.99 1.70753

9 -0.2016 0.040641-0.0679

-0.1605870.03237376

1Mean=

1.909135

∑dx^21025.825 Average= 0.092687

∑ dx*dy=42.61260068

SD=5.4137

Variance= 29.30928

Covariance=1.217502876

Beta= 0.04154

Tata contra fund (G)month NAV dx dx^2 Return (Y) dy dx*dyMay-09 9.49 Jun-09 11.855 24.9209

722.9255

1 525.5791.127349

1.034662 23.72016Jul-09 12.66 6.79038

44.79492

4 22.99129-0.14652

-0.2392 -1.14697Aug-09 13.97 10.3475

58.35209

1 69.757430.360529

0.267842 2.237039Sep-09 15.023 7.53758

15.54212

1 30.71510.041412

-0.05128 -0.28417Oct-09 15.127 0.69227

2 -1.30319 1.6982990.4381

0.345413 -0.45014Nov-09 16.184 6.98750

64.99204

6 24.920520.3739

0.281213 1.403828Dec-09 15.27 -5.64755 -7.64301 58.41565 0.3089 0.216213 -1.65252Jan-10 15.78 3.33988

21.34442

2 1.8074710.01627

-0.07642 -0.10274Feb-10 16.216 2.76299

10.76753

1 0.589104-0.1654

-0.25809 -0.19809Mar-10 15.832 -2.36803 -4.36349 19.04006 0.0476 -0.04509 0.196737Apr-10 15.82 -0.0758 -2.07126 4.290101 0.3089 0.216213 -0.44783

May-10 16.79 6.131479

4.136019 17.10665

0.01627-0.07642 -0.31606

Jun-10 17.308 3.08517 1.08971 1.187467 -0.01644 -0.10913 -0.11892Jul-10 18.428 6.47099

64.47553

6 20.030420.20462

0.111933 0.50096Aug-10 19.03 3.26676

81.27130

8 1.6162240.04885

-0.04384 -0.05573Sep-10 19.56 2.78507

60.78961

6 0.6234940.0316

-0.06109 -0.04824

93

Oct-10 18.288 -6.50307 -8.49853 72.22497 0.5275 0.434813 -3.69527Nov-10 17.72 -3.10586 -5.10132 26.02348 -0.004 -0.09669 0.493231Dec-10 17.18 -3.0474 -5.04286 25.43048 -0.1163 -0.20899 1.053893Jan-11 16.81 -2.15367 -4.14913 17.21526 0.21031 0.117623 -0.48803Feb-11 17.9 6.48423

64.48877

6 20.14911-0.5325

-0.62519 -2.80632Mar-11 17.73 -0.94972 -2.94518 8.674089 -0.075 -0.16769 0.493869Apr-11 17.87 0.78962

2 -1.20584 1.4540450.41605

0.323363 -0.38992May-11 18.27 2.23838

80.24292

8 0.059014-0.0756

-0.16829 -0.04088Jun-11 16.63 -8.97646 -10.9719 120.3831 -0.0146 -0.10729 1.177145Jul-11 16.79 0.96211

7 -1.03334 1.0677980.07534

-0.01735 0.017925Aug-11 16.86 0.41691

5 -1.57855 2.491805-0.1369

-0.22959 0.362413Sep-11 16.63 -1.36418 -3.35964 11.28715 -0.4249 -0.51759 1.738904Oct-11 15.789 -5.05713 -7.05259 49.73896 -0.0429 -0.13559 0.956239Nov-11 16.82 6.52986

34.53440

3 20.560810.46348

0.370793 1.681325Dec-11 18.13 7.78834

75.79288

7 33.55754-0.4782

-0.57089 -3.30708Jan-12 18.18 0.27578

6 -1.71967 2.957279-0.198

-0.29069 0.499887Feb-12 17.005 -6.46315 -8.45861 71.54802 0.54018 0.447493 -3.78517Mar-12 17.08 0.44104

7 -1.55441 2.4162010.18203

0.089343 -0.13888Apr-12 17.85 4.50819

72.51273

7 6.313846-0.0679

-0.16059 -0.40351

Mean 1.99546

1

Variance=36.96918

SD=6.0802

Beta=0.01287 16.65708

Cov=0.475917

kotak contra fund(G)month NAV return X dx dx^2 Return (Y) dy dx*dyMay-09 12.668 Jun-09 15.84 25.03947 23.41737 548.3732 1.127349 1.034662 24.22907Jul-09 14.69 -7.2601 -8.8822 78.89349 -0.14652 -0.2392 2.124663

Aug-09 16.676 13.5194 11.8973 141.5458 0.360529 0.267842 3.186594Sep-09 17.827 6.902135 5.280035 27.87877 0.041412 -0.05128 -0.27074Oct-09 18.94 6.243339 4.621239 21.35585 0.4381 0.345413 1.596236Nov-09 19.08 0.739176 -0.88292 0.779554 0.3739 0.281213 -0.24829Dec-09 19.41 1.72956 0.10746 0.011548 0.3089 0.216213 0.023234Jan-10 20.367 4.930448 3.308348 10.94517 0.01627 -0.07642 -0.25281

94

Feb-10 18.852 -7.4385 -9.0606 82.09454 -0.1654 -0.25809 2.338424Mar-10 19.827 5.171865 3.549765 12.60083 0.0476 -0.04509 -0.16005Apr-10 20.605 3.923942 2.301842 5.298477 0.3089 0.216213 0.497688

May-10 19.968 -3.09148 -4.71358 22.21786 0.01627 -0.07642 0.360198Jun-10 20.682 3.575721 1.953621 3.816636 -0.01644 -0.10913 -0.21319Jul-10 21.537 4.13403 2.51193 6.30979 0.20462 0.111933 0.281168

Aug-10 22.123 2.720899 1.098799 1.207359 0.04885 -0.04384 -0.04817Sep-10 23.94 8.213172 6.591072 43.44223 0.0316 -0.06109 -0.40263Oct-10 23.729 -0.88137 -2.50347 6.267363 0.5275 0.434813 -1.08854Nov-10 24.82 4.59775 2.97565 8.85449 -0.004 -0.09669 -0.28771Dec-10 22.42 -9.66962 -11.2917 127.503 -0.1163 -0.20899 2.359823Jan-11 21.457 -4.29527 -5.91737 35.01529 0.21031 0.117623 -0.69602Feb-11 20.054 -6.53866 -8.16076 66.59798 -0.5325 -0.62519 5.102Mar-11 19.79 -1.31645 -2.93855 8.63505 -0.075 -0.16769 0.492756Apr-11 21.067 6.452754 4.830654 23.33522 0.41605 0.323363 1.562055

May-11 19.928 -5.40656 -7.02866 49.40206 -0.0756 -0.16829 1.182832Jun-11 20.28 1.766359 0.144259 0.020811 -0.0146 -0.10729 -0.01548Jul-11 20.438 0.779093 -0.84301 0.710661 0.07534 -0.01735 0.014624

Aug-11 18.596 -9.01262 -10.6347 113.0973 -0.1369 -0.22959 2.441594Sep-11 18.934 1.817595 0.195495 0.038218 -0.4249 -0.51759 -0.10119Oct-11 18.916 -0.09507 -1.71717 2.948663 -0.0429 -0.13559 0.232826Nov-11 18.402 -2.71728 -4.33938 18.83019 0.46348 0.370793 -1.60901Dec-11 17.666 -3.99957 -5.62167 31.60312 -0.4782 -0.57089 3.209336Jan-12 19.295 9.221103 7.599003 57.74484 -0.198 -0.29069 -2.20893Feb-12 21.035 9.01788 7.39578 54.69757 0.54018 0.447493 3.30956Mar-12 20.61 -2.02044 -3.64254 13.26811 0.18203 0.089343 -0.32544Apr-12 20.615 0.02426 -1.59784 2.553092 -0.0679 -0.16059 0.256592

∑dx^2=1627.894

∑ dx*dy=46.87309

Variance= 46.51126 SD=6.8198

Beta=0.028794

covariance 1.339231

95

96

AIG India equity fund(G)

month NAV Return (X) dx dx^2

Return (Y) dy dx*dy

May-09 6.953 Jun-09 8.753 25.88811 24.0560

2578.691

91.12734

91.03466

224.8898

5Jul-09 9.136 4.375643 2.54355

3 6.46966-0.14652

-0.2392 -0.60843Aug-09 9.647 5.593257 3.76116

714.1463

80.36052

90.26784

21.00739

8Sep-09 10.327 7.048823 5.21673

327.2143

10.04141

2 -0.05128 -0.26749Oct-09 11.04 6.904232 5.07214

225.7266

20.4381 0.34541

31.75198

4Nov-09 11.154 1.032609

-0.79948 0.639170.3739 0.28121

3 -0.22482Dec-09 11.181 0.242066

-1.590022.52817

80.3089 0.21621

3 -0.34378Jan-10 11.833 5.831321 3.99923

115.9938

50.01627

-0.07642 -0.30561Feb-10 11.27 -4.75788

-6.5899743.4277

1-0.1654

-0.258091.70078

6Mar-10 11.869 5.314996 3.48290

612.1306

30.0476

-0.04509 -0.15703Apr-10 12.288 3.530205 1.69811

52.88359

40.3089 0.21621

30.36715

4May-10 11.765 -4.25618

-6.0882737.0670

90.01627

-0.076420.46524

8Jun-10 12.126 3.068423 1.23633

3 1.52852-0.01644

-0.10913 -0.13492Jul-10 12.31 1.517401

-0.314690.09902

90.20462 0.11193

3 -0.03522Aug-10 12.226 -0.68237

-2.514466.32251

90.04885

-0.043840.11022

6Sep-10 12.73 4.122362 2.29027

25.24534

70.0316

-0.06109 -0.13991Oct-10 12.95 1.728201

-0.103890.01079

30.5275 0.43481

3 -0.04517Nov-10 13.272 2.486486 0.65439

60.42823

5-0.004

-0.09669 -0.06327Dec-10 12.718 -4.1742

-6.0062936.0755

4-0.1163

-0.208991.25523

7Jan-11 12.21 -3.99434

-5.8264333.9472

70.21031 0.11762

3 -0.68532Feb-11 11.58 -5.15971

-6.9918 48.8852-0.5325

-0.625194.37117

9Mar-11 11.414 -1.43351

-3.265610.6641

2-0.075

-0.167690.54759

8Apr-11 12.191 6.807429 4.97533

9 24.7540.41605 0.32336

31.60884

1May-11 12.151 -0.32811

-2.16024.66646

8-0.0756

-0.168290.36353

4Jun-11 12.314 1.341453

-0.490640.24072

4-0.0146

-0.107290.05263

9Jul-11 12.512 1.607926

-0.22416 0.050250.07534

-0.017350.00388

9Aug-11 12.074 -3.50064

-5.33273 28.438-0.1369

-0.229591.22432

5Sep-11 12.472 3.296339 1.46424

92.14402

6-0.4249

-0.51759 -0.75788Oct-11 12.08 -3.14304

-4.9751324.7519

2-0.0429

-0.135590.67456

3Nov-11 11.61 -3.89073 32.7506 0.46348 0.37079

escorts opportunities fund(G)

month NAV dx2 dx Return (Y)Dy dx*dy

May-09 25.114 Jun-09 25.339 0.895915 0.228335 0.47784463 1.127349 1.034662 0.494408Jul-09 25.174 -0.65117 1.143274 -1.0692401 -0.14652 -0.2392 0.255767

Aug-09 25.217 0.170811 0.061137 -0.2472588 0.360529 0.267842 -0.06623Sep-09 25.34 0.487766 0.004858 0.06969619 0.041412 -0.05128 -0.00357Oct-09 25.763 1.669298 1.56557 1.25122755 0.4381 0.345413 0.43219Nov-09 25.85 0.337694 0.00646 -0.0803764 0.3739 0.281213 -0.0226Dec-09 26.047 0.762089 0.118349 0.34401897 0.3089 0.216213 0.074381Jan-10 26.117 0.268745 0.022298 -0.149325 0.01627 -0.07642 0.011411Feb-10 25.994 -0.47096 0.79037 -0.8890276 -0.1654 -0.25809 0.229446Mar-10 26.036 0.161576 0.065789 -0.2564943 0.0476 -0.04509 0.011565Apr-10 27.03 3.817791 11.5581 3.39972075 0.3089 0.216213 0.735064

May-10 27.05 0.073992 0.11839 -0.3440781 0.01627 -0.07642 0.026293Jun-10 27.202 0.561922 0.020694 0.14385237 -0.01644 -0.10913 -0.0157Jul-10 27.46 0.94846 0.281313 0.53038967 0.20462 0.111933 0.059368

Aug-10 27.86 1.456664 1.078678 1.03859424 0.04885 -0.04384 -0.04553Sep-10 28.86 3.589375 10.05718 3.17130545 0.0316 -0.06109 -0.19373Oct-10 28.27 -2.04435 6.063522 -2.462422 0.5275 0.434813 -1.07069Nov-10 29.26 3.501946 9.510288 3.08387553 -0.004 -0.09669 -0.29817Dec-10 28.084 -4.01914 19.68882 -4.4372088 -0.1163 -0.20899 0.927319Jan-11 28.072 -0.04273 0.212336 -0.460799 0.21031 0.117623 -0.0542Feb-11 27.021 -3.74394 17.32236 -4.1620141 -0.5325 -0.62519 2.602037Mar-11 27.2 0.662448 0.05972 0.24437773 -0.075 -0.16769 -0.04098Apr-11 28.08 3.235294 7.936752 2.81722412 0.41605 0.323363 0.910986

May-11 27.93 -0.53419 0.906795 -0.952258 -0.0756 -0.16829 0.160253Jun-11 28.35 1.503759 1.178721 1.0856894 -0.0146 -0.10729 -0.11648Jul-11 28.67 1.128748 0.505063 0.7106778 0.07534 -0.01735 -0.01233

Aug-11 27.533 -3.96582 19.21847 -4.3838879 -0.1369 -0.22959 1.006484Sep-11 27.57 0.134384 0.080478 -0.2836858 -0.4249 -0.51759 0.146832Oct-11 27.135 -1.5778 3.983505 -1.995872 -0.0429 -0.13559 0.270614Nov-11 26.565 -2.10061 6.343739 -2.5186781 0.46348 0.370793 -0.93391Dec-11 25.675 -3.35027 14.20041 -3.7683429 -0.4782 -0.57089 2.151298Jan-12 27.005 5.180136 22.67728 4.76206632 -0.198 -0.29069 -1.38427Feb-12 28.47 5.424921 25.06856 5.00685131 0.54018 0.447493 2.240531Mar-12 28.7 0.807868 0.151942 0.38979793 0.18203 0.089343 0.034826Apr-12 28.801 0.351916 0.004376 -0.0661536 -0.0679 -0.16059 0.010623

Mean0.418072

182.2339 Variance=5.2 SD=5.206684 Sum = 8.533311

Covarience =0.243809

97

Birlasunlife next generation fund

month NAV dx dx^2 Return (Y) dy dx*dyMay-09 13.31 Jun-09 15.88 19.30879 17.28459 298.7571 1.127349 1.034662 17.88371Jul-09 15.57 -1.95214 -3.97634 15.81129 -0.14652 -0.2392 0.951159

Aug-09 17.39 11.68915 9.664946 93.41118 0.360529 0.267842 2.588676Sep-09 18.29 5.175388 3.151188 9.929987 0.041412 -0.05128 -0.16158Oct-09 19.18 4.866047 2.841847 8.076094 0.4381 0.345413 0.981611Nov-09 19.44 1.355579 -0.66862 0.447054 0.3739 0.281213 -0.18802Dec-09 19.23 -1.08025 -3.10445 9.637591 0.3089 0.216213 -0.67122Jan-10 20.39 6.032241 4.008041 16.06439 0.01627 -0.07642 -0.30628Feb-10 19.24 -5.64002 -7.66422 58.74026 -0.1654 -0.25809 1.978035Mar-10 19.96 3.742204 1.718004 2.951537 0.0476 -0.04509 -0.07746Apr-10 21.32 6.813627 4.789427 22.93861 0.3089 0.216213 1.035536

May-10 21.4 0.375235 -1.64897 2.719087 0.01627 -0.07642 0.126009Jun-10 21.53 0.607477 -1.41672 2.007105 -0.01644 -0.10913 0.154603Jul-10 22.89 6.316767 4.292567 18.42613 0.20462 0.111933 0.48048

Aug-10 24.43 6.727829 4.703629 22.12412 0.04885 -0.04384 -0.20619Sep-10 26.259 7.486697 5.462497 29.83887 0.0316 -0.06109 -0.33369Oct-10 26.11 -0.56742 -2.59162 6.716518 0.5275 0.434813 -1.12687Nov-10 26.88 2.949062 0.924862 0.855369 -0.004 -0.09669 -0.08942Dec-10 24.88 -7.44048 -9.46468 89.5801 -0.1163 -0.20899 1.977994Jan-11 23.59 -5.18489 -7.20909 51.97094 0.21031 0.117623 -0.84795Feb-11 22.2 -5.89233 -7.91653 62.6714 -0.5325 -0.62519 4.94931Mar-11 22.33 0.585586 -1.43861 2.069611 -0.075 -0.16769 0.241237Apr-11 24.58 10.07613 8.051931 64.83359 0.41605 0.323363 2.603696

May-11 24.01 -2.31896 -4.34316 18.86303 -0.0756 -0.16829 0.730897Jun-11 25.16 4.789671 2.765471 7.64783 -0.0146 -0.10729 -0.2967Jul-11 26.36 4.769475 2.745275 7.536537 0.07534 -0.01735 -0.04762

Aug-11 24.79 -5.95599 -7.98019 63.6835 -0.1369 -0.22959 1.832149Sep-11 24.24 -2.21864 -4.24284 18.00166 -0.4249 -0.51759 2.196037Oct-11 23.92 -1.32013 -3.34433 11.18456 -0.0429 -0.13559 0.453448Nov-11 23.94 0.083612 -1.94059 3.765882 0.46348 0.370793 -0.71956Dec-11 22.42 -6.34921 -8.37341 70.11393 -0.4782 -0.57089 4.780269Jan-12 22.84 1.873327 -0.15087 0.022763 -0.198 -0.29069 0.043857Feb-12 24.82 8.669002 6.644802 44.15339 0.54018 0.447493 2.973502Mar-12 24.66 -0.64464 -2.66884 7.122715 0.18203 0.089343 -0.23844Apr-12 25.43 3.122466 1.098266 1.206187 -0.0679 -0.16059 -0.17637

1143.882.024293 SD=5.71 Cov=1.242138 43.47484

Variance32.68228 Beta=0.038006

98

sbi magnum contra fund(G)

month NAV dx dx^2 Return (Y) dy dx*dyMay-09 36.66 Jun-09 46.31 26.32297 25.09862 629.9406 1.127349 1.034662 25.96859Jul-09 44 -4.98812 -6.21247 38.59483 -0.14652 -0.2392 1.486052

Aug-09 46.23 5.068182 3.843832 14.77504 0.360529 0.267842 1.029539Sep-09 51.142 10.62514 9.400785 88.37476 0.041412 -0.05128 -0.48203Oct-09 53.891 5.37523 4.15088 17.2298 0.4381 0.345413 1.433768Nov-09 53 -1.65334 -2.87769 8.281084 0.3739 0.281213 -0.80924Dec-09 53.58 1.09434 -0.13001 0.016903 0.3089 0.216213 -0.02811Jan-10 57.12 6.606943 5.382593 28.97231 0.01627 -0.07642 -0.41132Feb-10 53.25 -6.77521 -7.99956 63.99296 -0.1654 -0.25809 2.064582Mar-10 55.12 3.511737 2.287387 5.23214 0.0476 -0.04509 -0.10313Apr-10 56.16 1.886792 0.662442 0.43883 0.3089 0.216213 0.143229

May-10 54.04 -3.77493 -4.99928 24.99279 0.01627 -0.07642 0.38203Jun-10 55.4 2.516654 1.292304 1.67005 -0.01644 -0.10913 -0.14103Jul-10 57.42 3.646209 2.421859 5.865403 0.20462 0.111933 0.271086

Aug-10 58.092 1.170324 -0.05403 0.002919 0.04885 -0.04384 0.002368Sep-10 62.27 7.19204 5.96769 35.61333 0.0316 -0.06109 -0.36455Oct-10 63.17 1.445319 0.220969 0.048827 0.5275 0.434813 0.09608Nov-10 65.58 3.815102 2.590752 6.711996 -0.004 -0.09669 -0.25049Dec-10 59.58 -9.14913 -10.3735 107.6091 -0.1163 -0.20899 2.167923Jan-11 56.16 -5.74018 -6.96453 48.5047 0.21031 0.117623 -0.81919Feb-11 53.34 -5.02137 -6.24572 39.00899 -0.5325 -0.62519 3.904741Mar-11 52.48 -1.6123 -2.83665 8.046575 -0.075 -0.16769 0.475669Apr-11 56.76 8.155488 6.931138 48.04067 0.41605 0.323363 2.241274

May-11 54.34 -4.26357 -5.48792 30.11722 -0.0756 -0.16829 0.923545Jun-11 54 -0.62569 -1.85004 3.422648 -0.0146 -0.10729 0.198485Jul-11 55.01 1.87037 0.64602 0.417342 0.07534 -0.01735 -0.01121

Aug-11 50.6 -8.01672 -9.24107 85.39745 -0.1369 -0.22959 2.121631Sep-11 49.82 -1.5415 -2.76585 7.649937 -0.4249 -0.51759 1.431569Oct-11 49.88 0.120434 -1.10392 1.218632 -0.0429 -0.13559 0.149677Nov-11 47.42 -4.93184 -6.15619 37.89863 0.46348 0.370793 -2.28267Dec-11 47.38 -0.08435 -1.3087 1.712702 -0.4782 -0.57089 0.747121Jan-12 46.35 -2.17391 -3.39826 11.54819 -0.198 -0.29069 0.987831Feb-12 52.74 13.78641 12.56206 157.8053 0.54018 0.447493 5.621433Mar-12 52.23 -0.96701 -2.19136 4.80205 0.18203 0.089343 -0.19578Apr-12 52.21 -0.03829 -1.26264 1.594265 -0.0679 -0.16059 0.202764

1.2243491565.549

V=44.72997 48.15224

SD=6.688Βeta=

0.030757

Covariance

1.375778

99

tata capital builder fund (G)month NAV

dx dx^2Return (Y) dy dx*dy

May-09 7.961 Jun-09 10.567 32.73458 30.88583 953.9346 1.127349 1.034662 31.95641Jul-09 11.18 5.801079 3.952329 15.6209 -0.14652 -0.2392 -0.94542

Aug-09 11.468 2.576029 0.727279 0.528934 0.360529 0.267842 0.194796Sep-09 12.736 11.05685 9.208104 84.78918 0.041412 -0.05128 -0.47215Oct-09 13.462 5.700377 3.851627 14.83503 0.4381 0.345413 1.330402Nov-09 13.689 1.686228 -0.16252 0.026413 0.3739 0.281213 -0.0457Dec-09 13.595 -0.68668 -2.53543 6.428419 0.3089 0.216213 -0.54819Jan-10 14.383 5.796249 3.947499 15.58275 0.01627 -0.07642 -0.30166Feb-10 13.745 -4.43579 -6.28454 39.49547 -0.1654 -0.25809 1.621959Mar-10 14.324 4.212441 2.363691 5.587035 0.0476 -0.04509 -0.10657Apr-10 14.57 1.717397 -0.13135 0.017254 0.3089 0.216213 -0.0284

May-10 14.48 -0.61771 -2.46646 6.083413 0.01627 -0.07642 0.188479Jun-10 14.085 -2.7279 -4.57665 20.94573 -0.01644 -0.10913 0.499436Jul-10 14.809 5.14022 3.29147 10.83378 0.20462 0.111933 0.368424

Aug-10 15.304 3.342562 1.493812 2.231474 0.04885 -0.04384 -0.06548Sep-10 15.34 0.235233 -1.61352 2.603438 0.0316 -0.06109 0.098565Oct-10 15.354 0.091265 -1.75749 3.088755 0.5275 0.434813 -0.76418Nov-10 16.46 7.203335 5.354585 28.67158 -0.004 -0.09669 -0.51772Dec-10 16.05 -2.49089 -4.33964 18.83245 -0.1163 -0.20899 0.906928Jan-11 15.47 -3.61371 -5.46246 29.83844 0.21031 0.117623 -0.64251Feb-11 14.41 -6.85197 -8.70072 75.70256 -0.5325 -0.62519 5.439578Mar-11 14.18 -1.59611 -3.44486 11.86709 -0.075 -0.16769 0.577659Apr-11 15.122 6.643159 4.794409 22.98636 0.41605 0.323363 1.550335

May-11 14.464 -4.35128 -6.20003 38.44033 -0.0756 -0.16829 1.043384Jun-11 14.715 1.735343 -0.11341 0.012861 -0.0146 -0.10729 0.012167Jul-11 14.82 0.713558 -1.13519 1.288662 0.07534 -0.01735 0.019692

Aug-11 13.599 -8.23887 -10.0876 101.76 -0.1369 -0.22959 2.315986Sep-11 13.48 -0.87506 -2.72381 7.419165 -0.4249 -0.51759 1.409811Oct-11 13.55 0.519288 -1.32946 1.76747 -0.0429 -0.13559 0.180258Nov-11 13.41 -1.03321 -2.88196 8.305695 0.46348 0.370793 -1.06861Dec-11 12.047 -10.1641 -12.0128 144.3075 -0.4782 -0.57089 6.857955Jan-12 12.667 5.14651 3.29776 10.87522 -0.198 -0.29069 -0.95862Feb-12 13.97 10.28657 8.437821 71.19683 0.54018 0.447493 3.775866Mar-12 13.08 -6.37079 -8.21954 67.56091 0.18203 0.089343 -0.73436Apr-12 13.92 6.422018 4.573268 20.91478 -0.0679 -0.16059 -0.73441

1.84875 t 1844.38 52.41411var 52.69658 1.497546SD 7.2551 0.0273

100

UTI MNC fund (G)month NAV dx dx^2 Return(Y) dy dx*dy

May-09 32.98 Jun-09 36.18 9.70285 7.43185 55.2324 1.127349 1.034662 7.689455Jul-09 36.21 0.08291

9 -2.18808 4.7877-0.14652

-0.2392 0.523399Aug-09 38.13 5.30240

3 3.031403 9.1894020.360529

0.267842 0.811936Sep-09 41.88 9.83477

6 7.563776 57.21070.041412

-0.05128 -0.38784Oct-09 45.18 7.87965

6 5.608656 31.457020.4381

0.345413 1.937303Nov-09 45.69 1.12881

8 -1.14218 1.304580.3739

0.281213 -0.3212Dec-09 47.03 2.93280

8 0.661808 0.437990.3089

0.216213 0.143092Jan-10 49.27 4.76291

7 2.491917 6.2096520.01627

-0.07642 -0.19042Feb-10 46.33 -5.96712 -8.23812 67.86662 -0.1654 -0.25809 2.126152Mar-10 49.15 6.08676

9 3.815769 14.560090.0476

-0.04509 -0.17204Apr-10 50.85 3.4588 1.1878 1.410868 0.3089 0.216213 0.256818

May-10 50.78 -0.13766 -2.40866 5.801642 0.01627 -0.07642 0.184063Jun-10 53.6 5.55336

7 3.282367 10.77394-0.01644

-0.10913 -0.35819Jul-10 55.2 2.98507

5 0.714075 0.5099030.20462

0.111933 0.079929Aug-10 56.35 2.08333

3 -0.18767 0.0352190.04885

-0.04384 0.008227Sep-10 58.15 3.19432

1 0.923321 0.8525220.0316

-0.06109 -0.0564Oct-10 61.07 5.02149

6 2.750496 7.5652290.5275

0.434813 1.195951Nov-10 61.38 0.50761

4 -1.76339 3.109529-0.004

-0.09669 0.170496Dec-10 58.38 -4.88759 -7.15859 51.24535 -0.1163 -0.20899 1.496051Jan-11 58.08 -0.51387 -2.78487 7.755527 0.21031 0.117623 -0.32757Feb-11 55.65 -4.18388 -6.45488 41.66553 -0.5325 -0.62519 4.03551Mar-11 54.91 -1.32974 -3.60074 12.96532 -0.075 -0.16769 0.603797Apr-11 58.94 7.33928

2 5.068282 25.687490.41605

0.323363 1.638895May-11 59.76 1.39124

5 -0.87975 0.773968-0.0756

-0.16829 0.148051Jun-11 62.12 3.94913 1.67813 2.81612 -0.0146 -0.10729 -0.18004Jul-11 63.91 2.88152 0.61052 0.372734 0.07534 -0.01735 -0.01059

Aug-11 61.07 -4.44375 -6.71475 45.08785 -0.1369 -0.22959 1.541619Sep-11 60.96 -0.18012 -2.45112 6.007995 -0.4249 -0.51759 1.268668Oct-11 60.85 -0.18045 -2.45145 6.009588 -0.0429 -0.13559 0.332384

101

Nov-11 56.58 -7.01726 -9.28826 86.27169 0.46348 0.370793 -3.44402Dec-11 57.84 2.22693

5 -0.04406 0.001942-0.4782

-0.57089 0.025156Jan-12 57.66 -0.3112 -2.5822 6.667774 -0.198 -0.29069 0.750613Feb-12 64.15 11.2556

4 8.984636 80.723690.54018

0.447493 4.020562Mar-12 65.37 1.90179

3 -0.36921 0.1363140.18203

0.089343 -0.03299Apr-12 70.06 7.17454

5 4.903545 24.04475-0.0679

-0.16059 -0.78745

2.271011 676.5487 24.71938

19.32996 SD=4.397 Beta=0.03654 0.706268Templeton india equity (G)month NAV Return

dx dx^2Return (Y) dy dx*dy

May-09 18.661

Jun-09 13.51 -27.603-27.9812

782.9482

1.127349 1.034662 -28.9511

Jul-09 13.6 0.666173 0.287983

0.082934

-0.14652-0.2392 -0.06889

Aug-09 15.23 11.9852911.6071

134.7249

0.360529 0.267842 3.108867

Sep-09 16.28 6.894288 6.516098

42.45953

0.041412 -0.05128 -0.33412

Oct-09 16.88 3.685504 3.307314

10.93832

0.43810.345413 1.142389

Nov-09 16.76 -0.7109-1.08909

1.186118

0.37390.281213 -0.30627

Dec-09 17.45 4.116945 3.738755

13.97829

0.30890.216213 0.808367

Jan-10 18.59 6.532951 6.154761

37.88109

0.01627-0.07642 -0.47033

Feb-10 17.36 -6.61646-6.99465

48.92514

-0.1654-0.25809 1.805228

Mar-10 17.95 3.398618 3.020428

9.122982

0.0476-0.04509 -0.13618

Apr-10 18.58 3.509749 3.131559

9.806664

0.30890.216213 0.677084

May-10 17.59 -5.32831-5.7065

32.56414

0.01627-0.07642 0.436074

Jun-10 17.85 1.478113 1.099923 1.20983

-0.01644-0.10913 -0.12003

Jul-10 18.53 3.809524 3.431334

11.77405

0.204620.111933 0.384079

Aug-10 19.33 4.317323 3.939133

15.51677

0.04885-0.04384 -0.17268

Sep-10 21.31 10.24315 9.86495 97.3173 0.0316 -0.06109 -0.60262

102

5 4Oct-10 22.09 3.660253 3.28206

310.7719

40.5275

0.434813 1.427084Nov-10 21.76 -1.49389

-1.872083.50467

8-0.004

-0.09669 0.181006Dec-10 21.91 0.689338 0.31114

80.09681

3-0.1163

-0.20899 -0.06503Jan-11 21.5 -1.87129

-2.249485.06016

80.21031

0.117623 -0.26459Feb-11 20.55

8-4.3814

-4.7595922.6536

5-0.5325

-0.62519 2.975631Mar-11 19.88

6-3.2688

-3.6469913.3005

4-0.075

-0.16769 0.611553Apr-11 21.12 6.205371 5.82718

133.9560

30.41605

0.323363 1.884295May-11 20.21 -4.30871

-4.686921.9670

5-0.0756

-0.16829 0.788745Jun-11 20.44 1.13805

0.759860.57738

8-0.0146

-0.10729 -0.08152Jul-11 18.56 -9.19765

-9.5758491.6967

40.07534

-0.01735 0.166112Aug-11 18.14

9-2.21444

-2.592636.72172

9-0.1369

-0.22959 0.595234Sep-11 18.04

4-0.57854

-0.95673 0.91534-0.4249

-0.51759 0.495193Oct-11 17.60

8-2.41632

-2.794517.80926

2-0.0429

-0.13559 0.378899Nov-11 17.21

8-2.2149

-2.593096.72412

80.46348

0.370793 -0.9615Dec-11 17.86 3.728656 3.35046

611.2256

2-0.4782

-0.57089 -1.91274Jan-12 20.2 13.1019 12.7237

1161.892

9-0.198

-0.29069 -3.69862Feb-12 19.6 -2.9703

-3.3484911.2123

70.54018

0.447493 -1.49842Mar-12 19.27

1-1.67857

-2.056764.23026

80.18203

0.089343 -0.18376Apr-12 19.45 0.928857 0.55066

70.30323

4-0.0679

-0.16059 -0.08843

0.378187to

1665.056 tot -22.051

var47.5730

3 cov -0.63003SD 6.897 beta -0.01324

ICICI Prudential focused blue chip Equity fundmonth NAV Return dx dx^2 Return (Y) dy dx*dyMay-09 9.16 Jun-09 10.59 15.61135 13.87635 192.5532 1.127349 1.034662 14.3573

103

4Jul-09 10.73 1.322002

-0.413 0.170567-0.14652

-0.23920.09879

1Aug-09 11.25 4.846226

3.111226 9.6797240.360529

0.2678420.83331

6Sep-09 12.64 12.35556 10.62056 112.7962 0.041412 -0.05128 -0.54457Oct-09 13.18 4.272152

2.537152 6.437140.4381

0.3454130.87636

5Nov-09 13.25 0.531108 -1.20389 1.449357 0.3739 0.281213 -0.33855Dec-09 13.48 1.735849

0.000849 7.21E-070.3089

0.2162130.00018

4Jan-10 13.92 3.264095 1.529095 2.338131 0.01627 -0.07642 -0.11685Feb-10 13.14 -5.60345

-7.33845 53.85282-0.1654

-0.258091.89395

8Mar-10 14.02 6.697108 4.962108 24.62252 0.0476 -0.04509 -0.22373Apr-10 14.23 1.49786 -0.23714 0.056235 0.3089 0.216213 -0.05127

May-10 14.1 -0.91356-2.64856 7.014885

0.01627-0.07642

0.202395

Jun-10 14.44 2.411348 0.676348 0.457446 -0.01644 -0.10913 -0.07381Jul-10 15.03 4.085873 2.350873 5.526602 0.20462 0.111933 0.26314

Aug-10 15.39 2.39521 0.66021 0.435877 0.04885 -0.04384 -0.02894Sep-10 16.44 6.822612 5.087612 25.8838 0.0316 -0.06109 -0.31079Oct-10 17.09 3.953771

2.218771 4.9229460.5275

0.4348130.96475

1Nov-10 17.07 -0.11703

-1.85203 3.430006-0.004

-0.096690.17906

7Dec-10 16.84 -1.34739 -3.08239 9.501147 -0.1163 -0.20899 0.64418Jan-11 16.45 -2.31591 -4.05091 16.40991 0.21031 0.117623 -0.47648Feb-11 15.73 -4.3769 -6.1119 37.35532 -0.5325 -0.62519 3.82108Mar-11 15.76 0.190718

-1.54428 2.384806-0.075

-0.167690.25895

6Apr-11 16.78 6.472081

4.737081 22.439940.41605

0.3233631.53179

7May-11 15.99 -4.70799

-6.44299 41.51206-0.0756

-0.168291.08427

1Jun-11 15.96 -0.18762

-1.92262 3.696457-0.0146

-0.107290.20627

2Jul-11 16.56 3.759398 2.024398 4.098189 0.07534 -0.01735 -0.03512

Aug-11 15.34 -7.36715-9.10215 82.84913

-0.1369-0.22959

2.089735

Sep-11 15.4 0.391134-1.34387 1.805975

-0.4249-0.51759

0.695567

Oct-11 15.41 0.064935-1.67006 2.789117

-0.0429-0.13559

0.226439

Nov-11 15.65 1.55743 -0.17757 0.031531 0.46348 0.370793 -0.06584Dec-11 14.65 -6.38978

-8.12478 66.01199-0.4782

-0.570894.63832

9Jan-12 14.99 2.320819 0.585819 0.343184 -0.198 -0.29069 -0.17029

104

Feb-12 16.86 12.4749810.73998 115.3472

0.540180.447493

4.806067

Mar-12 16.31 -3.26216 -4.99716 24.9716 0.18203 0.089343 -0.44646Apr-12 16.03 -1.71674

-3.45174 11.9145-0.0679

-0.160590.55430

4

mean

1.735084 ∑dx^2 895.0895 ∑dx*dy

37.34361

variance 25.57399 covariance 1.06696

SD 5.0569 beta0.04172

4UTI Oppertunities fund(G)month NAV Dx dx^2 Return (Y) dy dx*dyMay-09 15.43 Jun-09 19.54 26.63642

24.67612255 608.9111.127349

1.03466225.5314

5Jul-09 19.1 -2.25179

-4.212091198 17.74171-0.14652

-0.23921.00755

2Aug-09 19.77 3.507853

1.547553403 2.3949220.360529

0.2678420.41449

9Sep-09 22.48 13.70764 11.74733784 137.9999 0.041412 -0.05128 -0.60235Oct-09 23.41 4.137011

2.176710676 4.7380690.4381

0.3454130.75186

4Nov-09 23.11 -1.2815 -3.241803631 10.50929 0.3739 0.281213 -0.91164Dec-09 23.39 1.211597 -0.748703289 0.560557 0.3089 0.216213 -0.16188Jan-10 22.67 -3.07824 -5.038538563 25.38687 0.01627 -0.07642 0.38503Feb-10 23.64 4.278783 2.318482532 5.375361 -0.1654 -0.25809 -0.59837Mar-10 23.36 -1.18443

-3.144733164 9.8893470.0476

-0.045090.14178

7Apr-10 24.111 3.214897 1.25459726 1.574014 0.3089 0.216213 0.27126

May-10 23.86 -1.04102-3.001318622 9.007913

0.01627-0.07642

0.229352

Jun-10 23.91 0.209556-1.750744258 3.065105

-0.01644-0.10913

0.191053

Jul-10 24.72 3.3877041.42740389 2.037482

0.204620.111933

0.159774

Aug-10 25.72 4.045307 2.085007443 4.347256 0.04885 -0.04384 -0.0914Sep-10 27.36 6.376361 4.416060809 19.50159 0.0316 -0.06109 -0.26976Oct-10 28.14 2.850877

0.890577193 0.7931280.5275

0.4348130.38723

5Nov-10 29.78 5.828003 3.867702843 14.95913 -0.004 -0.09669 -0.37396Dec-10 28.04 -5.84285

-7.803147549 60.88911-0.1163

-0.208991.63075

6Jan-11 27.28 -2.71041 -4.670713695 21.81557 0.21031 0.117623 -0.54938Feb-11 25.94 -4.91202

-6.87232346 47.22883-0.5325

-0.625194.29648

7Mar-11 26.08 0.539707

-1.420592984 2.018084-0.075

-0.167690.23821

5

105

Apr-11 27.75 6.4033744.443074233 19.74091

0.416050.323363

1.436726

May-11 26.94 -2.91892-4.879218919 23.80678

-0.0756-0.16829

0.821109

Jun-11 27.26 1.187825-0.772475204 0.596718

-0.0146-0.10729

0.082877

Jul-11 27.55 1.06383-0.896470213 0.803659

0.07534-0.01735

0.015551

Aug-11 27.67 0.435572-1.524728312 2.324796

-0.1369-0.22959

0.350058

Sep-11 26.37 -4.69823-6.658529129 44.33601

-0.4249-0.51759

3.446368

Oct-11 26.3 -0.26545-2.225753166 4.953977

-0.0429-0.13559

0.301783

Nov-11 26.71 1.558935 -0.401364639 0.161094 0.46348 0.370793 -0.14882Dec-11 26.64 -0.26207

-2.22237413 4.938947-0.4782

-0.570891.26872

4Jan-12 24.56 -7.80781

-9.768107808 95.41593-0.198

-0.290692.83946

2Feb-12 26.15 6.473941

4.513641368 20.372960.54018

0.4474932.01982

3Mar-12 28.44 8.75717

6.796870172 46.197440.18203

0.0893430.60725

3Apr-12 28.74 1.054852

-0.905447679 0.819835-0.0679

-0.160590.14540

3

1.960356∑dx^2 1275.213 ∑dx*dy

45.26389

variance 36.43467 covarian1.29325

4

SD 6.036 Beta0.03549

7

Fedelity Equity fundmonth NAV dx dx^2 Return (Y) dy dx*dyMay-09 19.07 Jun-09 22.78 19.45464 17.61774 310.3848 1.127349 1.034662 18.22841Jul-09 22.68 -0.43898 -2.27588 5.179637 -0.14652 -0.2392 0.544401

Aug-09 24.24 6.878307 5.041407 25.41578 0.360529 0.267842 1.350299Sep-09 26.78 10.47855 8.641648 74.67808 0.041412 -0.05128 -0.4431Oct-09 28.7 7.169529 5.332629 28.43694 0.4381 0.345413 1.84196Nov-09 29.21 1.777003 -0.0599 0.003588 0.3739 0.281213 -0.01684Dec-09 29.03 -0.61623 -2.45313 6.017834 0.3089 0.216213 -0.5304Jan-10 30.43 4.822597 2.985697 8.914388 0.01627 -0.07642 -0.22816Feb-10 29.06 -4.50214 -6.33904 40.18338 -0.1654 -0.25809 1.636023Mar-10 30.11 3.613214 1.776314 3.155292 0.0476 -0.04509 -0.08009Apr-10 31.68 5.214215 3.377315 11.40625 0.3089 0.216213 0.730219

May-10 31.29 -1.23106 -3.06796 9.412382 0.01627 -0.07642 0.234444

106

Jun-10 34.4 9.939278 8.102378 65.64852 -0.01644 -0.10913 -0.88419Jul-10 34.69 0.843023 -0.99388 0.987791 0.20462 0.111933 -0.11125

Aug-10 36.9 6.370712 4.533812 20.55545 0.04885 -0.04384 -0.19875Sep-10 37.84 2.547425 0.710525 0.504846 0.0316 -0.06109 -0.0434Oct-10 39.31 3.884778 2.047878 4.193804 0.5275 0.434813 0.890444Nov-10 36.84 -6.28339 -8.12029 65.93908 -0.004 -0.09669 0.785126Dec-10 35.36 -4.01737 -5.85427 34.27251 -0.1163 -0.20899 1.223467Jan-11 34.23 -3.1957 -5.0326 25.32708 0.21031 0.117623 -0.59195Feb-11 34.57 0.993281 -0.84362 0.711693 -0.5325 -0.62519 0.52742Mar-11 36.07 4.339022 2.502122 6.260616 -0.075 -0.16769 -0.41957Apr-11 34.97 -3.04963 -4.88653 23.87813 0.41605 0.323363 -1.58012

May-11 35.07 0.285959 -1.55094 2.405417 -0.0756 -0.16829 0.261003Jun-11 35.55 1.368691 -0.46821 0.219219 -0.0146 -0.10729 0.050233Jul-11 34.01 -4.33193 -6.16883 38.05442 0.07534 -0.01735 0.107011

Aug-11 33.19 -2.41106 -4.24796 18.04513 -0.1369 -0.22959 0.975275Sep-11 32.9 -0.87376 -2.71066 7.347662 -0.4249 -0.51759 1.403001Oct-11 33.14 0.729483 -1.10742 1.226372 -0.0429 -0.13559 0.150151Nov-11 32.89 -0.75438 -2.59128 6.714708 0.46348 0.370793 -0.96083Dec-11 30.4 -7.57069 -9.40759 88.50275 -0.4782 -0.57089 5.370671Jan-12 31.39 3.256579 1.419679 2.015488 -0.198 -0.29069 -0.41268Feb-12 35.55 13.25263 11.41573 130.3189 0.54018 0.447493 5.108458Mar-12 34.17 -3.88186 -5.71876 32.70418 0.18203 0.089343 -0.51093Apr-12 34.25 0.234124 -1.60278 2.568893 -0.0679 -0.16059 0.257385

mean 1.836997 ∑dx^2 1101.591 ∑dx*dy 34.66314

Variance 31.47403covariance 0.990375

SD 5.61 beta 0.031466

Franklin Indian blue chip fund (G)month NAV dx dx^2 Return (Y) dy dx*dyMay-09 127.1

5

Jun-09 149.36

17.4675615.87556 252.0333

1.1273491.034662 16.42584

Jul-09 149.32

-0.02678-1.61878 2.620452

-0.14652-0.2392 0.38722

Aug-09 155.29

3.9981252.406125 5.789437

0.3605290.267842 0.644461

Sep-09 168.26

8.3521156.760115 45.69916

0.041412-0.05128 -0.34663

Oct-09 177.52

5.5033883.911388 15.29895

0.43810.345413 1.351044

Nov-09 178.21

0.388689-1.20331 1.447958

0.37390.281213 -0.33839

107

Dec-09 160.96

-9.67959-11.2716 127.0488

0.30890.216213 -2.43706

Jan-10 189.8 17.9175 16.3255 266.5218 0.01627 -0.07642 -1.24755Feb-10 180.1

2-5.10011

-6.69211 44.78427-0.1654

-0.25809 1.727145Mar-10 190.4

85.751721

4.159721 17.303280.0476

-0.04509 -0.18755Apr-10 194.7

72.252205

0.660205 0.4358710.3089

0.216213 0.142745May-10 191.8

3-1.50947

-3.10147 9.6191330.01627

-0.07642 0.237005Jun-10 194.1

41.204191

-0.38781 0.150396-0.01644

-0.10913 0.04232Jul-10 199.3 2.657876 1.065876 1.136091 0.20462 0.111933 0.119307

Aug-10 204.58

2.6492721.057272 1.117825

0.04885-0.04384 -0.04635

Sep-10 222.08

8.5541116.962111 48.47099

0.0316-0.06109 -0.42529

Oct-10 224.22

0.963617-0.62838 0.394866

0.52750.434813 -0.27323

Nov-10 232.39

3.6437432.051743 4.209648

-0.004-0.09669 -0.19838

Dec-10 222.74

-4.1525-5.7445 32.99931

-0.1163-0.20899 1.200526

Jan-11 214.38

-3.75325-5.34525 28.57175

0.210310.117623 -0.62872

Feb-11 208.87

-2.5702-4.1622 17.32393

-0.5325-0.62519 2.602155

Mar-11 208.4 -0.22502 -1.81702 3.301563 -0.075 -0.16769 0.304691Apr-11 217.7 4.462572 2.870572 8.240183 0.41605 0.323363 0.928237

May-11 210.46

-3.32568-4.91768 24.18355

-0.0756-0.16829 0.827581

Jun-11 211.94

0.703222-0.88878 0.789927

-0.0146-0.10729 0.095354

Jul-11 215.86

1.849580.25758 0.066347

0.07534-0.01735 -0.00447

Aug-11 202.33

-6.26795-7.85995 61.77884

-0.1369-0.22959 1.804543

Sep-11 201.94

-0.19275-1.78475 3.185348

-0.4249-0.51759 0.923766

Oct-11 204 1.020105 -0.5719 0.327064 -0.0429 -0.13559 0.077542Nov-11 200.7

5-1.59314

-3.18514 10.14510.46348

0.370793 -1.18103Dec-11 191.2

2-4.7472

-6.3392 40.18543-0.4782

-0.57089 3.618966Jan-12 195.5

42.259178

0.667178 0.445126-0.198

-0.29069 -0.19394Feb-12 219.0

812.03846

10.44646 109.12850.54018

0.447493 4.674717Mar-12 215.4 -1.63867 -3.23067 10.43723 0.18203 0.089343 -0.28864

108

9Apr-12 208.7

9-3.10919

-4.70119 22.10122-0.0679

-0.16059 0.75495

1.592734 ∑dx^2 1217.293 ∑dx*dy 31.0929variance 34.77979 cov 0.888368SD 5.897 beta 0.025543

HDFC Top 200 fund (G)month NAV dx dx^2 Return (Y) dy dx*dyMay-09 115.4

8

Jun-09 142.33

23.2507821.42858 459.184

1.1273491.034662 22.17134

Jul-09 135.88

-4.53172-6.35392 40.37233

-0.14652-0.2392 1.519887

Aug-09 154.28

13.5413611.71916 137.3387

0.3605290.267842 3.13888

Sep-09 167.18

8.3614216.539221 42.76141

0.041412-0.05128 -0.3353

Oct-09 177.36

6.0892454.267045 18.20767

0.43810.345413 1.473893

Nov-09 178.11

0.422869-1.39933 1.958128

0.37390.281213 -0.39351

Dec-09 176.4 -0.96008 -2.78228 7.741087 0.3089 0.216213 -0.60157Jan-10 185.2

55.017007

3.194807 10.206790.01627

-0.07642 -0.24414Feb-10 171.2

6-7.55196

-9.37416 87.87482-0.1654

-0.25809 2.419348Mar-10 181.5

86.025925

4.203725 17.671310.0476

-0.04509 -0.18953Apr-10 184.3

11.50347

-0.31873 0.1015890.3089

0.216213 -0.06891May-10 185.8

60.840974

-0.98123 0.9628040.01627

-0.07642 0.074982Jun-10 196.3 5.617131 3.794931 14.4015 -0.01644 -0.10913 -0.41413Jul-10 197.3

40.529801

-1.2924 1.6702940.20462

0.111933 -0.14466Aug-10 203.9

33.339414

1.517214 2.3019390.04885

-0.04384 -0.06651Sep-10 218.4

97.139705

5.317505 28.275860.0316

-0.06109 -0.32483Oct-10 225.1

73.057348

1.235148 1.5255910.5275

0.434813 0.537058Nov-10 236.0

74.840787

3.018587 9.111867-0.004

-0.09669 -0.29186Dec-10 221.6

3-6.11683

-7.93903 63.02819-0.1163

-0.20899 1.659154Jan-11 216.1

1-2.49064

-4.31284 18.600570.21031

0.117623 -0.50729

109

Feb-11 204.32

-5.45556-7.27776 52.96572

-0.5325-0.62519 4.549958

Mar-11 202.41

-0.93481-2.75701 7.601094

-0.075-0.16769 0.462314

Apr-11 213.41

5.4345143.612314 13.04881

0.416050.323363 1.168089

May-11 206.21

-3.37379-5.19599 26.99829

-0.0756-0.16829 0.874417

Jun-11 205.49

-0.34916-2.17136 4.714798

-0.0146-0.10729 0.232959

Jul-11 209.29

1.8492380.027038 0.000731

0.07534-0.01735 -0.00047

Aug-11 185.63

-11.3049-13.1271 172.3204

-0.1369-0.22959 3.013809

Sep-11 191.49

3.1568171.334617 1.781203

-0.4249-0.51759 -0.69078

Oct-11 192.03

0.281999-1.5402 2.372219

-0.0429-0.13559 0.208831

Nov-11 181.63

-5.41582-7.23802 52.38894

0.463480.370793 -2.68381

Dec-11 170.98

-5.86357-7.68577 59.07104

-0.4782-0.57089 4.387705

Jan-12 184.54

7.9307526.108552 37.31441

-0.198-0.29069 -1.77568

Feb-12 208.64

13.059511.2373 126.2769

0.540180.447493 5.028613

Mar-12 205.01

-1.73984-3.56204 12.68812

0.182030.089343 -0.31824

Apr-12 202.09

-1.42432-3.24652 10.5399

-0.0679-0.16059 0.521349

1.822202 ∑dx^2 1543.379 ∑dx*dy 44.39137Variance 44.09654 cov 1.268325SD 6.641 Beta 0.028762

JP MORGAN INDIA EQUITY FUNDmonth NAV dx dx^2 Return (Y) dy dx*dy

May-09 7.75 Jun-09 9.25 19.35484 17.80984 317.1904 1.127349 1.034662 18.42717Jul-09 9.32 0.756757 -0.78824 0.621327 -0.14652 -0.2392 0.188551

Aug-09 9.6 3.004292 1.459292 2.129533 0.360529 0.267842 0.390859Sep-09 10.77 12.1875 10.6425 113.2628 0.041412 -0.05128 -0.5457Oct-09 11.34 5.292479 3.747479 14.0436 0.4381 0.345413 1.294428Nov-09 11.29 -0.44092 -1.98592 3.943867 0.3739 0.281213 -0.55847Dec-09 11.18 -0.97431 -2.51931 6.346941 0.3089 0.216213 -0.54471Jan-10 11.27 0.805009 -0.73999 0.547587 0.01627 -0.07642 0.056548Feb-10 11.09 -1.59716 -3.14216 9.873173 -0.1654 -0.25809 0.810951Mar-10 11.74 5.861136 4.316136 18.62903 0.0476 -0.04509 -0.1946

110

Apr-10 11.8 0.511073 -1.03393 1.069005 0.3089 0.216213 -0.22355May-10 12.14 2.881356 1.336356 1.785847 0.01627 -0.07642 -0.10212Jun-10 12.67 4.365733 2.820733 7.956535 -0.01644 -0.10913 -0.30782Jul-10 13.36 5.445935 3.900935 15.2173 0.20462 0.111933 0.436643

Aug-10 13.86 3.742515 2.197515 4.829072 0.04885 -0.04384 -0.09633Sep-10 14.49 4.545455 3.000455 9.002727 0.0316 -0.06109 -0.18329Oct-10 15.02 3.657695 2.112695 4.46348 0.5275 0.434813 0.918627Nov-10 14.1 -6.12517 -7.67017 58.83145 -0.004 -0.09669 0.741605Dec-10 14.12 0.141844 -1.40316 1.968847 -0.1163 -0.20899 0.293241Jan-11 13.37 -5.31161 -6.85661 47.01317 0.21031 0.117623 -0.8065Feb-11 12.84 -3.9641 -5.5091 30.35017 -0.5325 -0.62519 3.444217Mar-11 12.71 -1.01246 -2.55746 6.540607 -0.075 -0.16769 0.428853Apr-11 13.37 5.192762 3.647762 13.30616 0.41605 0.323363 1.179551

May-11 12.96 -3.06657 -4.61157 21.26655 -0.0756 -0.16829 0.776067Jun-11 13.16 1.54321 -0.00179 3.2E-06 -0.0146 -0.10729 0.000192Jul-11 13.49 2.507599 0.962599 0.926596 0.07534 -0.01735 -0.0167

Aug-11 12.41 -8.00593 -9.55093 91.22027 -0.1369 -0.22959 2.192769Sep-11 12.21 -1.6116 -3.1566 9.964146 -0.4249 -0.51759 1.633817Oct-11 12.44 1.883702 0.338702 0.114719 -0.0429 -0.13559 -0.04592Nov-11 12.46 0.160772 -1.38423 1.916088 0.46348 0.370793 -0.51326Dec-11 11.15 -10.5136 -12.0586 145.4109 -0.4782 -0.57089 6.884123Jan-12 11.6 4.035874 2.490874 6.204455 -0.198 -0.29069 -0.72406Feb-12 12.83 10.60345 9.058448 82.05549 0.54018 0.447493 4.053592Mar-12 12.9 0.545596 -0.9994 0.998808 0.18203 0.089343 -0.08929Apr-12 12.6 -2.32558 -3.87058 14.9814 -0.0679 -0.16059 0.621565

mean 1.545072 ∑dx^2 1063.982 ∑dx*dy 39.82105Var 30.39949 Cov 1.137744SD 5.514 Beta 0.037426

RELLIANCE QUANT PLUS FUND RETAIL PLAN [G]month NAV dx dx^2 Return (Y)

May-09 7.97 dy dx*dyJun-09 10.09 26.59975 24.92375 621.1933 1.127349Jul-09 9.73 -3.56789 -5.24389 27.49837 -0.14652 1.034662 25.78766

Aug-09 10.27 5.549846 3.873846 15.00668 0.360529 -0.2392 1.254362Sep-09 13.32 29.69815 28.02215 785.2409 0.041412 0.267842 1.037578Oct-09 11.71 -12.0871 -13.7631 189.4226 0.4381 -0.05128 -1.43685Nov-09 11.48 -1.96413 -3.64013 13.25057 0.3739 0.345413 -4.75395Dec-09 11.31 -1.48084 -3.15684 9.965615 0.3089 0.281213 -1.02365Jan-10 11.77 4.067197 2.391197 5.717824 0.01627 0.216213 -0.68255Feb-10 11.16 -5.18267 -6.85867 47.04132 -0.1654 -0.07642 -0.18273Mar-10 11.69 4.749104 3.073104 9.443968 0.0476 -0.25809 1.770133Apr-10 11.85 1.368691 -0.30731 0.094439 0.3089 -0.04509 -0.13856

111

May-10 11.5 -2.95359 -4.62959 21.43307 0.01627 0.216213 -0.06644Jun-10 12.03 4.608696 2.932696 8.600704 -0.01644 -0.07642 0.353779Jul-10 12.36 2.743142 1.067142 1.138792 0.20462 -0.10913 -0.32004

Aug-10 12.66 2.427184 0.751184 0.564278 0.04885 0.111933 0.119448Sep-10 13.72 8.372828 6.696828 44.8475 0.0316 -0.04384 -0.03293Oct-10 14.43 5.174927 3.498927 12.24249 0.5275 -0.06109 -0.40909Nov-10 15.6 8.108108 6.432108 41.37201 -0.004 0.434813 1.521379Dec-10 14.43 -7.5 -9.176 84.19898 -0.1163 -0.09669 -0.6219Jan-11 13.63 -5.54401 -7.22001 52.12848 0.21031 -0.20899 1.917665Feb-11 13.21 -3.08144 -4.75744 22.63322 -0.5325 0.117623 -0.84924Mar-11 13.23 0.1514 -1.5246 2.324404 -0.075 -0.62519 2.974288Apr-11 13.82 4.459562 2.783562 7.748215 0.41605 -0.16769 0.255656

May-11 13.03 -5.71635 -7.39235 54.64688 -0.0756 0.323363 0.900101Jun-11 12.97 -0.46048 -2.13648 4.564529 -0.0146 -0.16829 1.244037Jul-11 13.58 4.703161 3.027161 9.163705 0.07534 -0.10729 0.229216

Aug-11 12.2 -10.162 -11.838 140.1383 -0.1369 -0.01735 -0.05251Sep-11 11.69 -4.18033 -5.85633 34.29658 -0.4249 -0.22959 2.717852Oct-11 12.32 5.389222 3.713222 13.78801 -0.0429 -0.51759 3.031159Nov-11 12.05 -2.19156 -3.86756 14.95801 0.46348 -0.13559 -0.50346Dec-11 11.28 -6.39004 -8.06604 65.06103 -0.4782 0.370793 -1.43406Jan-12 11.75 4.166667 2.490667 6.20342 -0.198 -0.57089 4.604798Feb-12 13.43 14.29787 12.62187 159.3117 0.54018 -0.29069 -0.724Mar-12 12.94 -3.64855 -5.32455 28.35081 0.18203 0.447493 5.6482Apr-12 12.7 -1.85471 -3.53071 12.46594 -0.0679 0.089343 -0.47571

-0.16059 0.5669871.676281 ∑dx^2 2566.057

Variance 73.3159 ∑dx*dy 42.22662SD 8.56 Cov 1.206475

Beta 0.016456

ING Core Equity Fundmonth NAV dx dx^2 Return (Y) dy dx*dy

May-09 23.18 Jun-09 28.22 21.74288 20.26888 410.8276 1.127349 1.034662 20.97145Jul-09 28.28 0.212615 -1.26138 1.591092 -0.14652 -0.2392 0.301729

Aug-09 29.09 2.864215 1.390215 1.932698 0.360529 0.267842 0.372358Sep-09 32.35 11.2066 9.7326 94.72351 0.041412 -0.05128 -0.49904Oct-09 33.41 3.276662 1.802662 3.249589 0.4381 0.345413 0.622663Nov-09 32.99 -1.25711 -2.73111 7.458954 0.3739 0.281213 -0.76802Dec-09 33.78 2.394665 0.920665 0.847624 0.3089 0.216213 0.19906Jan-10 34.69 2.693902 1.219902 1.48816 0.01627 -0.07642 -0.09322Feb-10 32.5 -6.31306 -7.78706 60.63828 -0.1654 -0.25809 2.009739Mar-10 34.37 5.753846 4.279846 18.31708 0.0476 -0.04509 -0.19297Apr-10 35.35 2.851324 1.377324 1.897021 0.3089 0.216213 0.297795

May-10 34.39 -2.7157 -4.1897 17.55359 0.01627 -0.07642 0.320164

112

Jun-10 35.11 2.093632 0.619632 0.383944 -0.01644 -0.10913 -0.06762Jul-10 36.81 4.841925 3.367925 11.34292 0.20462 0.111933 0.376982

Aug-10 37.15 0.923662 -0.55034 0.302872 0.04885 -0.04384 0.024125Sep-10 39.5 6.325707 4.851707 23.53906 0.0316 -0.06109 -0.29638Oct-10 41.87 6 4.526 20.48468 0.5275 0.434813 1.967964Nov-10 43.18 3.128732 1.654732 2.738137 -0.004 -0.09669 -0.15999Dec-10 40.29 -6.69291 -8.16691 66.69847 -0.1163 -0.20899 1.706779Jan-11 38.5 -4.44279 -5.91679 35.0084 0.21031 0.117623 -0.69595Feb-11 37.58 -2.38961 -3.86361 14.92749 -0.5325 -0.62519 2.415479Mar-11 36.75 -2.20862 -3.68262 13.5617 -0.075 -0.16769 0.617528Apr-11 39.2 6.666667 5.192667 26.96379 0.41605 0.323363 1.679116

May-11 38.4 -2.04082 -3.51482 12.35393 -0.0756 -0.16829 0.591498Jun-11 37.75 -1.69271 -3.16671 10.02804 -0.0146 -0.10729 0.339747Jul-11 39.13 3.655629 2.181629 4.759506 0.07534 -0.01735 -0.03784

Aug-11 38.76 -0.94557 -2.41957 5.8543 -0.1369 -0.22959 0.555501Sep-11 35.39 -8.69453 -10.1685 103.399 -0.4249 -0.51759 5.263099Oct-11 35.36 -0.08477 -1.55877 2.429763 -0.0429 -0.13559 0.211349Nov-11 33.95 -3.98756 -5.46156 29.8286 0.46348 0.370793 -2.02511Dec-11 31.93 -5.94993 -7.42393 55.11468 -0.4782 -0.57089 4.238223Jan-12 33.71 5.574695 4.100695 16.8157 -0.198 -0.29069 -1.19202Feb-12 38.11 13.05251 11.57851 134.0618 0.54018 0.447493 5.181301Mar-12 37.3 -2.12543 -3.59943 12.95587 0.18203 0.089343 -0.32158Apr-12 36.51 -2.11796 -3.59196 12.90219 -0.0679 -0.16059 0.576822

1.474309 ∑dx^2 1236.98 ∑dx*dy 44.49072Variance 35.34229 Cov 1.271164SD 5.95 beta 0.035967

HSBC INDIA OPPORTUNITIES month NAV dx dx^2 Return (Y) dy dx*dyMay-09 22.84 Jun-09 26.37 15.45534 14.13864 199.9012 1.127349 1.034662 14.62872Jul-09 27.22 3.22336 1.90666 3.635352 -0.14652 -0.2392 -0.45608

Aug-09 28.51 4.739162 3.422462 11.71325 0.360529 0.267842 0.916678Sep-09 30.2 5.927745 4.611045 21.26173 0.041412 -0.05128 -0.23643Oct-09 31.28 3.576159 2.259459 5.105155 0.4381 0.345413 0.780446Nov-09 31.6 1.023018 -0.29368 0.086249 0.3739 0.281213 -0.08259Dec-09 31.84 0.759494 -0.55721 0.310479 0.3089 0.216213 -0.12048Jan-10 32.49 2.041457 0.724757 0.525273 0.01627 -0.07642 -0.05538Feb-10 30.62 -5.75562 -7.07232 50.01767 -0.1654 -0.25809 1.825273Mar-10 31.68 3.46179 2.14509 4.60141 0.0476 -0.04509 -0.09672Apr-10 31.64 -0.12626 -1.44296 2.082141 0.3089 0.216213 -0.31199

May-10 31.39 -0.79014 -2.10684 4.438771 0.01627 -0.07642 0.160998Jun-10 32.14 2.389296 1.072596 1.150462 -0.01644 -0.10913 -0.11705Jul-10 33.43 4.01369 2.69699 7.273756 0.20462 0.111933 0.301882

113

Aug-10 33.92 1.465749 0.149049 0.022216 0.04885 -0.04384 -0.00653Sep-10 37.09 9.345519 8.028819 64.46193 0.0316 -0.06109 -0.49046Oct-10 37.87 2.102993 0.786293 0.618256 0.5275 0.434813 0.34189Nov-10 39.12 3.300766 1.984066 3.936517 -0.004 -0.09669 -0.19183Dec-10 36.47 -6.77403 -8.09073 65.45989 -0.1163 -0.20899 1.690857Jan-11 34.76 -4.68879 -6.00549 36.06585 0.21031 0.117623 -0.70638Feb-11 33.71 -3.02071 -4.33741 18.81316 -0.5325 -0.62519 2.711695Mar-11 33.41 -0.88994 -2.20664 4.869276 -0.075 -0.16769 0.370025Apr-11 36.04 7.871895 6.555195 42.97058 0.41605 0.323363 2.119707

May-11 34.26 -4.93896 -6.25566 39.13324 -0.0756 -0.16829 1.052746Jun-11 34.31 0.145943 -1.17076 1.370672 -0.0146 -0.10729 0.125607Jul-11 35.18 2.535704 1.219004 1.48597 0.07534 -0.01735 -0.02115

Aug-11 32.85 -6.62308 -7.93978 63.04013 -0.1369 -0.22959 1.822871Sep-11 32.65 -0.60883 -1.92553 3.707658 -0.4249 -0.51759 0.996628Oct-11 32.49 -0.49005 -1.80675 3.264331 -0.0429 -0.13559 0.244971Nov-11 32.68 0.584795 -0.7319 0.535684 0.46348 0.370793 -0.27139Dec-11 31.02 -5.07956 -6.39626 40.91213 -0.4782 -0.57089 3.651541Jan-12 31.5 1.547389 0.230689 0.053217 -0.198 -0.29069 -0.06706Feb-12 34.98 11.04762 9.730919 94.69079 0.54018 0.447493 4.354518Mar-12 34.8 -0.51458 -1.83128 3.353586 0.18203 0.089343 -0.16361Apr-12 34.74 -0.17241 -1.48911 2.21746 -0.0679 -0.16059 0.239132

Mean 1.316741 ∑dx^2 803.0854 ∑dx*dy 34.94107variance 22.9453 Covariance 0.998316SD 4.738 Beta 0.043509

BNP Paribas Equity Fund month NAV dx dx^2 Return (Y) dy dx*dyMay-09 22.64 Jun-09 27.42 21.11307 19.68207 387.384 1.127349 1.034662 20.3643Jul-09 24.63 -10.1751 -11.6061 134.7005 -0.14652 -0.2392 2.776222

Aug-09 27.21 10.47503 9.04403 81.79449 0.360529 0.267842 2.422369Sep-09 30.36 11.57663 10.14563 102.9337 0.041412 -0.05128 -0.52022Oct-09 31.26 2.964427 1.533427 2.351398 0.4381 0.345413 0.529666Nov-09 30.46 -2.55918 -3.99018 15.92154 0.3739 0.281213 -1.12209Dec-09 30.85 1.280368 -0.15063 0.02269 0.3089 0.216213 -0.03257Jan-10 31.62 2.495948 1.064948 1.134115 0.01627 -0.07642 -0.08138Feb-10 27.63 -12.6186 -14.0496 197.3911 -0.1654 -0.25809 3.626018Mar-10 30.82 11.54542 10.11442 102.3015 0.0476 -0.04509 -0.45603Apr-10 31.24 1.362751 -0.06825 0.004658 0.3089 0.216213 -0.01476

May-10 30.41 -2.65685 -4.08785 16.71052 0.01627 -0.07642 0.312381Jun-10 31.6 3.913186 2.482186 6.16125 -0.01644 -0.10913 -0.27087Jul-10 32.15 1.740506 0.309506 0.095794 0.20462 0.111933 0.034644

Aug-10 32.5 1.088647 -0.34235 0.117206 0.04885 -0.04384 0.015008

114

Sep-10 35.16 8.184615 6.753615 45.61132 0.0316 -0.06109 -0.41256Oct-10 36.84 4.778157 3.347157 11.20346 0.5275 0.434813 1.455387Nov-10 37.61 2.090119 0.659119 0.434438 -0.004 -0.09669 -0.06373Dec-10 35.55 -5.47727 -6.90827 47.72415 -0.1163 -0.20899 1.443738Jan-11 34.03 -4.27567 -5.70667 32.56606 0.21031 0.117623 -0.67124Feb-11 33.3 -2.14517 -3.57617 12.78896 -0.5325 -0.62519 2.235773Mar-11 32.77 -1.59159 -3.02259 9.13606 -0.075 -0.16769 0.506849Apr-11 38.74 18.21788 16.78688 281.7994 0.41605 0.323363 5.428257

May-11 33.17 -14.3779 -15.8089 249.9214 -0.0756 -0.16829 2.660433Jun-11 33.61 1.3265 -0.1045 0.01092 -0.0146 -0.10729 0.011212Jul-11 34.03 1.249628 -0.18137 0.032896 0.07534 -0.01735 0.003146

Aug-11 32.91 -3.29121 -4.72221 22.2993 -0.1369 -0.22959 1.084159Sep-11 32.52 -1.18505 -2.61605 6.843718 -0.4249 -0.51759 1.354034Oct-11 32.81 0.891759 -0.53924 0.290781 -0.0429 -0.13559 0.073114Nov-11 30.72 -6.37001 -7.80101 60.85574 0.46348 0.370793 -2.89256Dec-11 30.49 -0.7487 -2.1797 4.751083 -0.4782 -0.57089 1.244361Jan-12 31.15 2.164644 0.733644 0.538234 -0.198 -0.29069 -0.21326Feb-12 34.16 9.662921 8.231921 67.76453 0.54018 0.447493 3.683727Mar-12 34.61 1.31733 -0.11367 0.012921 0.18203 0.089343 -0.01016Apr-12 33.96 -1.87807 -3.30907 10.94994 -0.0679 -0.16059 0.531394

1.431121 ∑dx^2 1914.56 ∑dx*dy 45.03477Variance 54.70171 Cov 1.286708SD 7.396 Beta 0.023522

Bibliography

Books

Punithavathy Pandian -“Security Analysis and Portfolio Management”-

Vikas Publishing House Pvt Ltd, New Delhi (Reprint 2005)

S. Kevin-“Portfolio Management”-Prentice – Hall of India Pvt Ltd, New Delhi (Reprint 2006)

Preethi singh-“Investment Management-Security Analysis and Portfolio Management”-Himalaya Publishing House, Mumbai(Reprint 2001)

Kothari. C.R – Research Methodology Methods and Techniques Investment management and security analysis : Dhanesh Kumar Khathri Mutual funds in India : Nalini Prava Tripathi

115

Websites

www.nseindia.com

www.bseindia.com

www.investopedia.com

www.amfinindia.com

www.mutualfundsindia.com

www.moneycontrol.com

www.hedgeequities.com

116