Mutual funds [www.writekraft.com]

Evaluationof mutual fund performance in the
present marketcondition

TABLE OF CONTENTS
1. INTRODUCTION...................................................................................................................3
1.1. BACKGROUND OF THE STUDY...............................................................................3
1.2. SIGNIFICANCE OF THE STUDY...............................................................................7
1.3. OBJECTIVES OF THE STUDY.................................................................................10
2. LITERATURE REVIEW......................................................................................................11
3. RESEARCH METHODOLOGY ........................................................................................44
3.1. SAMPLE SIZE DETERMINATION ...........................................................................45
3.2. DATA COLLECTION INSTRUMENTS.....................................................................45
4. DATA ANALYSIS ................................................................................................................46
4.1. PRESENTATION OF DATA ......................................................................................47
5. RECOMMENDATIONS......................................................................................................63
6. CONCLUSION.....................................................................................................................65
7. BIBLIOGRAPHY..................................................................................................................68
APPENDIX I................................................................................................................................70

1. INTRODUCTION
1.1. Background of the Study
Even in a relatively developing economy like India the importance of marketing as a
profit making activity aimed at facilitating the flow of the required products from the
place of production to the consuming public or users is recognized. To achieve
effectiveness, such activity requires a lot of planning and marketing strategies.
Aware of the fact that, there is a good number of cement producing companies in the
country and the fact that profit, which is one of the objectives of every business
enterprise, can only be realized by selling products rather than merely producing them.
Therefore, business as an act can be seen from a couple of ways. As many as these
ways are not withstanding, business can be summarized as the act of marketing goods
and services geared towards satisfying customers’ or users’ need and wants with the
primary aim of making profit. For this aim to succeed, every business therefore has
several ways and styles of having enough money to operate or stay out of debt. This
can be subsumed to simply mean, business strategy. However, part of any business is
to be competitive. That is, competing against other business set-ups or being competed
against.
Competition can be very interesting, especially when it is healthy and practice within the
rules of the game. Because through healthy competition, business bodies can do self-
assessment, readjust and seek avenues for innovation and development.
Consumer behaviour from the marketing world and financial economics have come
together to bring to surface an exciting area for study and research in the form of

Behavioral Finance and it has been gaining importance over the recent years. With
reforms in financial sector and the developments in the Indian financial markets, Mutual
Funds (MFs) have emerged to be an important investment avenue for retail (small)
investors. The investment habit of the small investors particularly has undergone a sea
change. Increasing number of players from public as well as private sectors has entered
in to the market with innovative schemes to cater to the requirements of the investors in
India and abroad. For all investors, particularly the small investors, mutual funds have
provided a better alternative to obtain benefits of expertise- based equity investments to
all types of investors. So in this scenario where many schemes are flooded in to market,
it is important to analyze needs of consumers and to find out which factors affects
consumers' needs the most.
Mutual funds are that collect money from several sources - individuals or institutions by
issuing 'units', invest them on their behalf with predetermined investment objectives and
manage the same all for a fee. They invest the money across a range of financial
instruments falling into two broad categories -and debt. Individual people and no doubt
can and do invest in equity and debt instruments by themselves but this requires time
and skill on both of which there are constraints. Mutual funds emerged as professional
financial intermediaries bridging the time and skill constraint. They have a team of
skilled people who identify the right stocks and debt instruments and construct a
portfolio that promises to deliver the best possible 'constrained' returns at the minimum
possible cost. In effect, it involves outsourcing the management of money.
More the benefits of investing in and debt instruments are supposedly much better if
done through mutual funds. This is because of the following reasons: Firstly, fund

managers are more skilled. They are trained to identify the best investment options and
to assess the portfolio on a continual basis; secondly, they are able to invest in a
diversified portfolio consisting of 15-20 different stocks or bonds or a combination of
them. For an individual such diversification reduces the risk but can demand a lot of
effort and cost. Each purchase or sale a cost in terms of brokerage or transactional
charges such a demat account fees in India. The need to possibly sell 'poor' stocks
bonds and
I buy 'good' stocks and bonds demands constant tracking of news and performance of
each company they have invested in. Mutual funds are able to maintain and track a
diversified portfolio on a constant basis with lesser costs. This is because of the
pecuniary economies that they enjoy when it comes to trading and other transaction
costs; thirdly, funds also provide good liquidity. An investor can sell her/his mutual fund
investments and receive payment on the same day with minimal transaction costs as
compared to dealing with individual securities, this totals to superior portfolio returns
with minimal cost and better liquidity. This can be represented with the following flow
chart:

Chart 1:
Source: Association of Mutual Funds in India (AMFI)

1.2. Significance of the study
This thesis makes several meaningful contributions to the literature and the practical
perspective. First, it is conducted in a different setting from most previous studies. Thus,
it provides an out-of-sample test for the theories and empirical models so far
established.
Second, this study fills one of the gaps in mutual fund studies by asking whether the
findings in Indian market carry over to India. This is important because, even though
India displays several characteristics which are not found in developed markets, the
literature on mutual funds in India is relatively thin and incomplete.
Third, this study uses an extensive dataset. The high data frequency not only helps to
validate our results, but also allows us to advance some analysis.
Furthermore, this is the first empirical study of an India which includes flexible funds in
the sample. In theory, a flexible fund is in some ways similar to equity funds since its
main assets are also stocks. However, a proportion of its holdings can be more varied
over time, subject to the fund manager’s decision. Thus, this study includes flexible
funds in the sample and puts them into a separate category and it is hoped to provide a
more comprehensive account of portfolio behaviour.
Fourth, this study applies new methodologies which have never been applied to India.
For instance, explores the determinants of risk-adjusted mutual fund performance using
multidimensional regression in addition to the common approach, which is to use a
zero-cost trading strategy. This alternative methodology can explore several factors
simultaneously while controlling the effect between one and another. Using the two

methods allows us to examine determinants of fund performance statistically and
economically and it provides more meaningful results. Moreover, in we apply a model in
the hedge fund literature in measuring the illiquid assets contained in a portfolio in our
mutual fund data. This is the first empirical study to use such a model outside the hedge
fund literature.
Fifth, this study explores new issues which have not hitherto been observed in previous
studies. This is the first study in India which explores the stock selection strategies and
style of fund managers.
We consider a broader range of characteristics than previous studies in India have done
in determining mutual fund performance and also include more new factors, namely
fund longevity and family size, in the analysis. We look at the effect of liquidity on the
mutual fund performance because liquidity is one of the major concerns in India.
Leaving aside India, the liquidity effect is negligible in all mutual fund literature, even
though this issue has been widely documented by writers of asset pricing. The study
also puts forward an auxiliary model based on the liquidity effect in measuring mutual
fund performance.
Sixth, this study can claim several new findings. This is the first mutual fund study to
expose the evidence of a liquidity premium and emphasize the inclusion of including a
liquidity factor in the fund performance measure. This study also provides new findings
about India. The study reveals the style of fund managers in these markets and shows
that they rely on medium capitalization strategy. This chapter also relates the sensitivity

of data frequency to the fund performance. In addition, it gives the first evidence from
the India of short-term persistence in performance among poorly performing funds.
Seventh, the study is the only one which gives important policy implications, reporting
them in turn in each empirical chapter. This is the first study on India which discusses
the effect of the Indian government’s encouragement of individual savings by adopting
special fund styles which give favorable tax treatment. We reveal the policy implications
of this action by assessing these specific funds in a separate group from general funds,
before comparing and discussing the results from the two groups.
Finally, in its practical aspects, this study will, it is hoped, be useful for individuals and
institutional investors in selecting mutual funds. It also helps fund managers to identify
their positions and gives ideas on the strategies which they should follow in order to
maximize returns for their investors.

1.3. Objectives of the Study
• To know the preference of investors and their needs regarding mutual funds
investment.
• To analyze factors that influences most while buying mutual funds.
• To evaluate performance of mutual fund schemes preferred by investors on the basis
of return parameters.

2. LITERATURE REVIEW
This chapter has two main purposes. The first is to review the theories associated with
the research questions in order to provide readers with an understanding of the
theoretical domain. The second purpose is to relate the theories to the research
questions and develop a theoretical framework for analysis. The reason for discussing
the theories is not to produce a comprehensive survey of their richness but rather to
provide a framework within which to facilitate the collection of empirical evidence,
conduct the analysis and, finally, achieve solutions to the research questions.
The growth of investments in mutual funds around the world has widely increased
during the past few decades, leading to fierce competition in the industry. Investors now
have a wide range of products to choose from, which makes their investment decision
more complicated than before. Although there are many factors in their decisions,
performance still seems to be a determining factor (see Ippolito, 1992; Capon et al.,
1996; Sirri and Tufano, 1998). As a result, from the investors’ point of view, it is
important not only to know how the portfolio managers perform, but also to understand
their investment policies. Similarly, at the macro level, it is worth examining the
performance of fund managers as a whole to see whether they provide value added to
portfolios or they are just sweeping benefits from investors.
However, superior performance in the past does not necessarily mean that it will
continue into the future. This is because superior performance may be due to either a
manager’s skill or good luck. Therefore, it is interesting to understand the characteristics
of funds and to know what caused the performance; this helps investors to understand
how to select their fund manager.

This literature survey chapter is organized as follows. Section 2.2 surveys the writings
related to performance measures and empirical evidence to do with them in the
developed markets. Section 2.3 surveys the literature on persistence in mutual fund
performance.
Section 2.4 surveys the literature on flows and their relation to performance. Section 2.5
surveys the literature on style analysis. Section 2.6 gives empirical evidence on India
and, finally, section 2.6 draws some conclusions and makes suggestions for further
research. At the end of this chapter, Tables 2.1 and 2.2 summaries the main theoretical
and empirical studies related to mutual fund performance in developed and India, in
turn.
Performance measures
It is typical that when one has made a decision, one wonders what its consequences
will be. Therefore, once an investor has given money to a fund manager to invest on
his/her behalf, he/she should have the right to know what sort of performance they have
obtained. Does the fund manager offer superior or inferior performance? How does the
fund manager perform compared to peers? And what sort of strategy is used?
Performance evaluation measures the skill of an asset manager and its principal idea is
to compare the returns with an alternative appropriate portfolio to that which was
obtained in a particular case. The emergence of modern portfolio theory (MPT) by
Markowitz (1952), who quantifies how rational investors make decisions based on
expected return and risk, has brought much development to portfolio performance
measurement. It moves performance measurement from crude measures toward more

precise, risk-adjusted measures. Up to now, many researchers have proposed various
methods for evaluating portfolio performance in order to find a model which could give a
precise and reliable measure (e.g. Jensen, 1968; Grinblatt and Titman, 1993; Ferson
and Schadt, 1996; Cahart, 1997; Daniel et al., 1997). Although these researchers use
different methods to evaluate portfolio performance, they all aim to provide an
appropriate method by which to distinguish superior managers from others. However, it
is difficult for a user to decide which model is the best suited for the performance
evaluation is a given case. Therefore, while many researchers have proposed different
methods for performance evaluation, some researchers also enquire which model gives
the best evaluation technique. (e.g. Grinblatt and Titmann, 1994; Kothari and Warner,
2001; Fletcher and Forbes, 2002; Otten and Bams, 2004). An appropriate model
depends not only on the method used for measurement, but also depends on the
appropriateness of the measure to the data and the market being evaluated. This
section will first introduce various methods of portfolio performance measurement which
have been discussed in the literature, partially following Grinblatt and Titman (Jarrow
etal., 1995). We divide performance measures into three classes: first, performance
measures in the early stage (Section 2.2.1), second, measures which require
benchmark returns (Section 2.2.2 - 2.2.4) and, third, measures which evaluate portfolios
based on their composition and do not necessarily require a benchmark portfolio
(Section 2.2.5). Following this, we highlight empirical evidence of fund performance in
developed markets in Section 2.2.6.

The early stage of performance measurement
In the early stage, the past few decades, performance evaluation was made by focusing
fund performance on the returns of the portfolio. The two methods which can measure
the return on a portfolio are the ‘money-weighted return method’ and the ‘time-weighted
return method’. The money-weighted return (otherwise called the internal rate of return)
is the discount rate which makes the final value of portfolio equal the sum of initial value
and cash flows occurring during the period. Alternatively, the time-weighted return
method is the geometric mean return of the portfolio’s sub periods. This measure
assumes that all distributed cash flows, such as dividend, are reinvested. As return is
the key aspect of performance measurement, some criticisms can be made of the
choice of method when measuring return. For example, Sharpe and Alexander(1990)
suggest that the time-weighted return method is preferable because this method is not
strongly influenced by the size and timing of cash flows, which managers are unable to
control. Spaulding (2003) reveals that when a portfolio is measured in a short period
and has few cash flows, the choice of return method is not different. Campisi (2004)
argues that the money-weighted return method is more appropriate for measuring active
investments. Nevertheless, the time-weighted return method is still widely used in
practice in the investment fund industry and it is believed that increasing the
measurement interval improves the precision of the calculation.
In term of risk measurement, there are two possible choices for measuring risk, namely,
‘total risk’ and ‘systematic risk’. Total risk is the overall risk of a portfolio including both
systematic and unsystematic risk and is measured by the portfolio’s standard deviation
of portfolio. In contrast, systematic risk (or market risk) is measured by the portfolio’s

beta coefficient, which is the sensitivity of the portfolio’s return to changes in the return
on the market portfolio. The choice of risk measures depends on the way in which the
portfolio is diversified. If the portfolio is well diversified, then using systematic risk is
preferable. Thus, it is advisable in the early stages of mutual fund performance
evaluation to use the basic approach, directly comparing the return on portfolios to other
portfolios with the same risk (benchmark portfolio). This evaluation technique is
straightforward and still widely used among investors and practitioners. However, it
could potentially be misleading and biased, because to be truly comparable it requires
the benchmark portfolio to have same risks and constraints.
In India one can gain additional benefit by investing through mutual funds tax savings.
Investment in certain types of funds such as Equity Linked Tax Savings Schemes
(ELSS) allows for certain amount of income tax benefits.
Mutual Funds are one form of Collective Investment Vehicles (CIV's) in India. The other
forms being Collective Investment Schemes (CIS's) and Venture Capital Funds
(VCF's).The organization of mutual funds in India (excepting for Unit Trust of India)2 is
dictated by the Securities and Exchange Board of India - SEBI (Mutual Funds)
Regulations, 1996, (henceforth termed as 'regulations'). Bank-owned mutual funds are
also supervised by the Reserve Bank of India (RBI). This does not overlap with SEBl's
supervision. Besides, the Indian Companies Act of 1956 and Indian Trust Act of 1882
also govern funds.

The SEBI regulations stipulate a three tier structure. The constituents of a mutual fund
include the Sponsors, the Mutual Fund, the Trustees and the Asset Management
Company (AMC).
The Sponsor as an individual or along with another corporate body initiates the process
by approaching the SEBI for registration of a mutual fund. There are certain eligibility
criteria which the sponsor has to fulfill [as laid out in Chapter II, clause 7 of the
regulations). Broadly speaking it requires a sound financial track record over the past
five years, a sound reputation with respect to integrity and a minimum of 40 percent
stake in the AMC by the sponsor. For instance, Tata Mutual
1. Section 80 C of the Indian Income Tax Act allows for Income Tax exemptions upto a
maximum of Rs. 100000
2. Unit Trust of India (UTI) is governed by the Government of India UTI Act of 1963
Fund set up in 1995 is sponsored by Tata Sons Limited and Tata Investment
Corporation Limited
The Mutual fund is itself set up in the form of a trust under the Indian Trust Act of 1882.
The instrument of the trust is executed by the sponsor in favour of trustees and is
registered under the Indian Registration Act, 1908. The investor subscribes to the 'units'
of the fund and, the collected funds/assets are held by the trustee for the benefit of the
investor.
The Sponsor then appoints the Trustees, AMC and Custodian [Chapter II, clause 7 (e),
(I), (g) of the regulations]. A Trustee holds the fiduciary responsibility of protecting the
interest of the investor. The trustees themselves are to be of impeccable personal

credentials [Chapter II, clause 16 (2)]. Two thirds of them have to be independent
persons and should not be associated with the sponsors in any manner'. No employee
of the AMC is to be a part of the Trustee. The Trustee has the duty of ensuring that the
AMC carries out its activities in accordance with the regulations and prevent conflict of
interest between the investors and the AMC. The trustee could be either a group of
individuals or a Trust Company. Most funds prefer a board of trustees. The Trustee for
Tata Mutual Fund is Tata Trustee Company Pvt. Ltd.
The AMC consists of the fund managers who manage the investments
Regulations are laid down [Chapter IV] with regard to their eligibility and obligations.
The AMC takes decisions with respect to investment/sales, computing asset values,
declaring dividend and providing investor information, regularity. An AMC cannot
www.tatamutualfund.comlrisk-factors.asp
Earlier only 50 percent were required to be independent members. This was amended
in 2006 by the SEBI (mutual funds) (Fifth Amendment) regulations. Act for any other
fund. The AMC for Tata mutual fund is Tata Asset Management Ltd. In addition to the
above three principal constituents there is the custodian (Chapter IV, clause 26)
predominant duties includes stock keeping of securities and settlement between funds.
A custodian can service more than one fund but not a fund promoted by a sponsor who
has 50 percent stake or more in the custodian.
For Tata Mutual Fund, ABN AMRO Bank N.U and Deutche Bank are the custodians.
Apart from these there are the depositories, transfer agents and distributors who
complete the organizational chain for mutual funds in India. The study firstly reviews the

Ories of regulation. The works of Stigler (1971) and Posner (1969) discuss the general
theoretical approaches to regulation. The justification of mutual fund regulations stems
from asymmetric information leading to possible investor - manager conflict of interest.
To control for such behaviour in 'public interest' the regulator might seek to use different
approaches including direct price control and or disclosure norms.
The study reviews literature relating to measure of risk in the case of equity returns. It
looks at both the Mean-Variance (M-V) approach and the lower partial movement
(LPM), while the M-V approach assumes that preferences are based only on the mean
returns and the variance of the fund portfolio. It is appropriate only if the returns are
normally distributed. During the 70s a semi variance measure of risk known as LPM
was developed. It gave a better approach towards measuring the risk-return
combination.
Writings on the single factor capital asset pricing model (CAPM) which uses the M-V
approach to risk and a Hemative multi-factor models used to measure portfolio
performance are also reviewed. In the process it looks at the efficient market hypothesis
and the theoretical impossibility of earning more returns than an informational efficient
market.
The study then moves on to theories of regulations and the necessity for the same to
tackle Principal-Agent problems that arise due to information asymmetries.
Regulation ought to be dynamic changing according to market conditions as the fund
industry gets competitive the necessity of regulations might wane. In fact it might be a
bane as regulations have an impact on performance and increase costs.

Posner speaks of the costs of regulations generally. To sum up, the basis of regulating
mutual funds appears to be from a public interest perspective to control hazards to
investors arising from market imperfections. Further the need to have appropriate risk-
reward measures emerges clearly.
Empirical studies pertaining to mutual fund performance can be grouped into single
factor CAPM which uses a single benchmar1< and multiple factor CAPM. Some of the
predominant single factor CAPM studies were those of Sharpe (1966), Treynor and
Mazuy (1966), Jensen.M (1968). But, Ross (1976) argued that systematic risk need not
be explained by a single factor and that there could be 'K' factors. Hence the basis for
multi factor models for assessing performance.
Several factors such as return of small cap stocks, large cap stocks, midcap stocks,
growth stocks, value stocks and momentum are included in various studies. For
instance, Fama and French (1993) used multifactor model with the market return, the
return of small less big stocks (SMB) and the return of high market, less low market
stocks (HML) as three important factors. Using multiple factors eliminates the error that
arises out of the assumption of homogeneity of assets held by different portfolios or
funds. The multiple factor models recalculate the Jansen alpha which measured
superior performance. Apart from these two broad approaches to performance,
empirical work on other special factors influencing performance analysis is reviewed.
Studies on the influence of size on performance such as Grinblatt and Titman (1989),
Indro et al (1999) and Chen et al (2003) are some who examine the role of size and
diseconomies of scale/all in the U.S context). The results are however mixed with no
clear consensus on diseconomies of scale. With respect to India there has been no

attempt to study the possibilities of size affecting returns. Another factor which has been
found important is the style of a fund. Sharpe (1992), Grinblatt et al (1995), and Bogle. J
(1998) discusses the role of style. Style describes the asset class of the portfolio of a
fund. This explains a large part of the funds return variability. Studies evolved from the
holdings based style analysis (HBSA) method (categorization of funds on the basis of
average market capitalization and average price-to-earnings of the fund portfolio) to the
returns based style analysis (BSA) classification (compares fund returns to returns of a
number of selected indexes)
While taking samples of funds for assessing their performance the survivor bias has to
be considered. Funds tend to close or merge with others, at times this covers up for
poor performance. So choosing funds which survive might tend to bias performance
analysis. Several funds in India had been terminated or merged and hence this factor
has to be considered while assessing performance.
Since the overwhelming emphasis of regulations in India is on direct controls on fees
and expenses that are charged to fund, investors' empirical studies relating to this issue
have been reviewed. In the relationship between fund expenses and performance
Sharpe (1966) and Ippolito (1989) throw up different conclusions.
On the relationship between fund size and expenses or economies of scale and scope
Baumol et al (1989), Rea (1999), Latke (1998) establish economics of scale and
Baumol also finds economics of scope. The Indian context regulatory caps on fund
manager fees and expenses and impact on constraining fund expenses has not been
dealt with so far.

Studies on Indian mutual fund performance by Sahadevan and Thiropol Raju (1997)
and Sadhak (1997) focus on general trends in the mutual fund performance, regulation
and expenses from 1990-91 to 1996. Their focus was not on the evolved risk return
analysis. Madhu S Panigrahi (1996) and Bijan Roy et al (2003) have attempted risk-
return analysis and using traditional CAPM and conditional performance evaluation
techniques respectively.
The review of empirical literature points out to the role of benchmarks and style of funds
in deciding fund performance. Studies also cover fund behaviour in terms of
management fee and expenses. These help point to the general issues of focus
concerning mutual funds. The Indian studies, it is found, tend to focus on using evolving
techniques to study of fund performance. But there is no attempt to study the impact of
regulations on fund behaviour in terms of expenses, fees and performance. This gap in
Indian studies needs to be seriously considered. It gives us the motivation for our study.
We need to study the past implications of fund regulations before we go ahead with
further changes in the same. Have the costs of regulations exceeded the benefits? Can
we improve regulations to ensure better governance? Do we notice tendencies of price
competition between funds? Do they deliver more than what regulations demand in
terms of cost charged to investors?

The organization conceived as above has is emphasis on eliminating moral hazards
that could arise out of post contractual opportunistic behaviour on the part of fund
managers. It aims at ensuring arms length transactions between the sponsor and the
AMC.
Types of Mutual Funds
A mutual fund, say, Tata Mutual Fund, can have several 'funds' [called 'schemes' in
India) under its management. These different funds can be categorized by structure,
investment objective and others. It would be well illustrated by the following flow chart:

Chart 3:
Source: Association of Mutual Funds in India (AMFI)
Is match of stocks in the equity and derivative (Mures and options) segments of the
stock market (Value Research Inc). They invest predominantly in equities 'Money
Marker. Funds invest only in short term debt such as call money, treasury bills and
commercial paper. In the case of these funds the Net Asset Value is simply the interest
accrued on these investments on a daily basis. Their NAV does not fall below the initial
investment value, unlike bond funds which are marked to market.

Tax saving funds give an investor tax benefits under section 80 C of the Income Tax
Act. Such funds also termed as Equity Linked Saving Schemes (ELSS), have a lock in
period of three years. By investing in such funds a person can avail of a maximum of
rupees one hundred thousand in tax deductions. ELSSs are normally diversified equity
funds. Index funds invest in securities of a particular index such as the Bombay Stock
Exchange (BSE) sensex in the same proposition. They provide returns which are close
to that of the benchmark index with similar risks as well. It is a passive investment
approach with lower costs.
Sector specific funds focus their investments on specific sectors which the fund
manager feels would do well. For instance, Franklin FMCG fund invests only in shares
of companies that produce fast moving consumer goods. Exchange Traded Fund's
(ETF) are relatively a new concept in India. Such funds are essentially index funds that
are listed and traded on the stock markets.
There are also commodities ETFs such as Reliance hold ETF.
The Mutual Funds Industry in India
The beginning of mutual funds in India was laid by the enactment of the Unit Trust of
India (UTI) Act in 1963. The objective was to provide investors from the middle and
lower income groups with a route to invest in the equity market. It was also meant to
encourage savings. UTI brought out its first fund, Unit Scheme (US) 64 in 1964. It called
an amount of Rs.246.7 millions. UTI remained a monopoly in the mutual fund industry
till 1987. By then US 64 had grown to Rs.32.69 billion and the overall asset base of UTI
was RS.67.38 billion with 25 different schemes·. In 1987 other public sector banks were

allowed to offer mutual funds. The State Bank of India (SBI) set up the SBI Mutual Fund
and Canara Bank Mutual Fund. Other public sector banks such as Bank of India,
Punjab National Bank, Indian Bank entered the fray by 1990. Two public sector
insurance companies -Life Insurance Corporation of India (LlC) and General Insurance
Corporation of India (GIC) also started their own mutual fund companies. But during this
period only public sector companies were permitted to enter the mutual fund market.
The collective assets under management continued to grow and by the end of 1993 it
was Rs.470 billion with UTI alone accounting for RS.390 billion>' There were 44.7
million investors in mutual funds".
1992-93 saw the beginning of economic reforms in India. The reforms aimed at
reducing government control over the economy and allowing for greater play for the
private sector besides others. In keeping with this direction the private sector was
allowed to enter the mutual fund industry in 1993. In keeping with this direction the
private sector was allowed to enter the mutual fund industry in 1993. In the same year
the first mutual fund regulations 1993 SEBI (mutual fund) Regulations came into being.
This was later substituted by a more comprehensive set of regulations - SEBI (mutual
fund) Regulations 1996. However, UTI did not come under these regulations and
continued to be governed under the UTI Act of 1963. By 2003 the total assets under
management (AUM) had increased to Rs.1, 218 billion mutual fund families and 401
funds. UTI alone accounted for Rs.445 billion of the total AUM
In 2003 the public sector UTI, which had faced serious problems in the late 90's and
again during 2002, was into two entities. One was the specified undertaking of UTI
which managed US 64, assured return schemes and others which totaled to Rs.298.4

billion and the other was UTI Mutual Fund Ltd. The latter came under the regulations of
SEBI. Since 2003 the mutual fund industry has also seen a spate of mergers. Hence
this period was marked by consolidation. By March 2007 the total AUM excluding UTI
touched Rs.3, 591 billion showing a phenomenal growth of 47 percent year-on-year
since 2003". During this period only Russia and China did better than India AUM growth
rates of 97 percent and 67 percent, respectively.
The financial savings of the households in India and the savings of the private corporate
sector form the main source of funds for the mutual fund industry. The gross financial
assets of Indian households increased from Rs.l09.6 billion (10.4 percent of the GOP at
CMP) in 1993-94 to Rs.4, 176.8 billion (14.85 percent of GOP at CMP) in 2003-0413.
The gross financial assets include currency held, bank and non-bank deposits, life
insurance, provident and pension funds, claims on the government, shares and
debentures, investments in Unit Trust of India and the net trade debt. Bank deposits
comprised of 42.83 percent of the total financial assets and shares and debentures
(which include mutual fund investments) forming a small 1.81 percent (EPW). The total
AUM at the end of March 2004, Rs.1, 396.16 billion was 4.96 percent of the GOP
(CMP). A comparison of India with other countries is given below:

Data from Investment Company Institute 2004, fact book
•• GDP data from IMF world economic outlook databases
The above table shows the vast potential for growth in the mutual funds industry. A
minuscule 5 percent of the GOP (CMP) was invested in mutual funds as "Economic and
political weekly, Oct. 09, 2004, pp 4487 compared to 67.5 percent in the U.S. The
comparison is to show what the growth potentials are.
In many ways the mutual fund industry can be termed to be still in its infancy. A SEBI
survey of Indian Investors 14 for the period April 01, 1999 to March 31, 2001 revealed
the low household penetration rate for mutual funds. The survey found that 7.4 percent
of Indian households (13.7 percent of urban and 3.8 percent of rural households) had
invested in mutual funds. Even among the urban households most investors were from
the largest cities with a population of 5 million or more. The facts point to a low
household penetration rate by mutual funds and also a very narrow urban bias. For

individual investors direct investment in equity was a risky proposition and an important
deterring factor as per the survey. Mutual funds have potential to offer a safer route to
the vast untapped households that still seem to prefer bank savings. But to use the
mutual fund route there are other concerns which need to be addressed.
Firstly funds have to deliver in terms of performance. Comparisons are bound to arise
particularly between fund return and benchmark indices are to be expected.
Outperforming benchmarks with lower costs is an important factor to attract more
savings into mutual funds. Apart from performance there is the issue of moral hazards.
Once a contract has been entered into with the fund house there are risks of conflicting
interests. These risks could be broadly classified into portfolio selection risks and
management process risks. The former involves 'adverse portfolio selection' which
contradicts the objective of the fund as mentioned in the prospectus. This could mean
higher risk of the fund portfolio on Risk Containment. Opinion, Business Line, 2~
October 2000 or lower risk-weighted returns. There could also be excessive churning of
the portfolio leading to more expenses that would be deducted from the AUM.
Management process risks involve risks arising due to errors in execution of
transactions losses due to counter-party default. It is to protect investors against such
risks that SEBl's (mutual fund) Regulations of 1993 were framed. The same was
substantially amended in 1996.
Given the growth of the mutual fund industry, it's present and potential importance as a
vehicle of financial saving for Indian households, and the development of regulations to
govern fund behaviour we feel it is important to assess the role of regulation in adding

value for the investor. Have the regulations ensured due diligence, transparency and
sound portfolio selection? Have the dynamics of the fund industry led to the necessity
for change in regulations? Is the present form of fund performance information
dissemination adequate? These are some of the questions that the present study
attempts to answer. This is sought to be done by examining the ability of regulations to:
ensure proper performance disclosure; better returns from funds; control costs of
operation; prevent excessive management fees and be proactive in tackling new issues.
The term ‘India’ was first introduced by the World Bank in the 1980s and defined as
countries which are in the transition from developing to developed economies.
More recently, the study of India has become more controversial and a number of
studies reveal several differences between them and developed markets. Harvey (1995)
claims that India exhibit high volatility and low correlation with developed markets.
However, the standard asset pricing model fails to explain cross-section returns in this
market, since India are not integrated with the world economy and there is a time
variation in risk exposure. Bekaert and Harvey(2002, 2003) also argue that India are
inefficient. India usually suffers from infrequent trading; high transaction cost; and
abnormal distribution of returns.
In addition, some researchers investigate the stock selection strategies in India and
reveal that stock returns in India are predictable owing to certain fundamental
characteristics. Claessens et al. (1995) investigate cross-section returns in 19
developing markets over the period 1986-1993 using several variables including, market
returns, earning-to-price, price-to-book value, size, dividend, turnover, and exchange

rate. They reveal that, in addition to market risk, firm size and turnover have explanatory
power in stock returns in many countries, although the signs are reversed in the
evidence from the US.
Conversely, Fama and French (1998) argue that the results in Claessens et al. are due
to the sensitivity to outliers. They examine the value and growth premium in 16 India for
1987-1995. They reveal that the evidence from developed markets is inconsistent with
the value and size premium in India. Nonetheless, they point to the unreliability of their
results, since the sample period is short and the returns are highly volatile. Using a
longer sample period, Rouwenhorst (1999) examines the return factors in 20 India over
the period 1982-1997. In comparison to Fama and French, he concludes that return
factors in India are similar to those in the US and in developed markets in that they
exhibit momentum and small and value premium. Similarly, van der Hart et al. (2003)
survey 32 India. They argue that stock returns can be
Explained by value, momentum and earning revisions but not for size, liquidity and
mean reversion. Nonetheless, Griffin et al. (2003), examining momentum strategy in 39
markets, show evidence of momentum strategy among Asian markets. In addition,
some studies investigate the return factors in some specific India. For instance, Drew
and Veeraraghanvan (2002) find a size and value premium in Malaysia; and Brown et
al. (2008) reveal a momentum and a value premium in Hong Kong and Singapore,
respectively.

In the mutual fund literature, in contrast to the extensive evidence from developed
markets, studies in India are scarce. Details of the empirical evidence in India are
chronologically presented in Table 2.2 and its main details are described below.
For his PhD thesis Elsiefy (2001) investigates the risk and return characteristics of 7
equity funds in Egyptian markets over the period 1996-1999. He employs several
performance measures, including the CAPM-based models; market timing models; and
Fama’s decomposition of returns (Fama, 1972). He reveals that over the period of his
study Egyptian funds do not outperform the market. However, the number of
underperforming funds is different for different measures used in the evaluation. Funds
do not diversify and therefore he suggests that using total risk is more appropriate in the
Egyptian context. In addition, he shows that performance does not change with the
market conditions. Roy and Deb (2003) take 89 Indian mutual funds over4 years, 1999-
2003 and examine the importance of using a conditional performance model which
allows time varying according to the economic conditions. They evaluate mutual fund
performance and market timing models, using both unconditional and conditional single-
factor models. Their conditional model includes 5 lagged information variables, namely,
t-bill, dividend yield, the term structure of interest rates, a dummy variable for the month
of April and a dummy variable for the tech rally. Inconsistently with the evidence from
the US, their results suggest that, as a whole, Indian mutual funds are unable to beat
the market. The conditional version makes funds look better and evidence of negative
market timing is not present. Soo-Wah (2007) explores 40 Malaysian funds over the
period 1996-2000 using single-factor and market timing models. He also tests for
benchmark sensitivity by employing two choices of benchmark: KLCI and the EMAS

index. He finds inferior performance and poor market timing in these Malaysian funds.
However, the choice of benchmark does not impact on performance evaluation, which
contradicts the findings in developed markets (e.g. Grinblatt and Titman, 1994).
Similarly, Fauziah and Mansor (2007) study mutual fund performance in Malaysia, using
a longer sample period (1991-2001) than Soo-Wah used in his study; they employ the
measures of Sharpe, Jensen and Treynor. Unlike Soo-Wah, they reveal that funds
perform below the market and find no evidence of persistence in performance.
Another study in Malaysia was conducted by Fikriyahet al. (2007). These writers
observe the difference in performance between conventional and Islamic funds over the
period 1992-2001. Their sample is 65 funds, including 14 Islamic funds. Like the studies
above, they employ standard measures, including the Sharpe, Jensen and Market
timing models. Subsequently, they reveal that Islamic funds are less risky than
conventional funds and perform better in bearish market conditions. Conversely, in
bullish market conditions, conventional funds seem to perform better.
In the Indian market, as far as is known, only a few studies in fund performance have
been published, some being in the form of scholars’ dissertations. Results from these
studies are, for example, those of Plabplatern (1997), who uses the portfolio holdings
method to investigate the performance of Indian mutual funds from 1993 to 1997. He
uses the quarterly data of 63 closed end funds. All funds have superior performance
and half of them bear evidence of market timing. In contrast, Sakranan (1998), who
uses a similar approach and time period, 1995-1997, to examine mutual fund
performance, draws a different conclusion: that only 2 out of 98 funds show selectivity
skills. Pornchaiya (2000) uses Jensen’s single-factor measure to explore 77 funds over

the period 1996-1999. He reveals that only two funds have superior performance, which
is inconsistent with the two Indian studies listed above.
Vongniphon (2002) studies return and risk in 18 equity funds, using a longer and more
up-to-date sample, from 1994 to 2000. He employs Sharpe and Treynor measures and
also confirms the inferior performance of these funds. Likewise, Jenwikai (2005) uses
Sharpe and Treynor measures to compare the performance of 62 equity funds to his
self-constructed buy-and-hold portfolios. He reveals that equity funds perform worse
than portfolios with buy-and-hold strategy.
The most recent and extensive research in mutual fund performance in India is
Nitibhon’s (2004) dissertation. He considers 114 equity funds in India from 2000 to 2004
and investigates performance using various methods including: Jensen’s alpha (1968),
Cahart’s 4-factor model (1996), Ferson and Schadt’s conditional model (1996) and
Daniel’s characteristic-based performance measures (1997). He reveals that Indian
mutual funds perform better than the market but not enough to generate statistically
abnormal returns. However, he reveals that using a conditional approach creates fairly
similar results to those obtained from using unconditional models, which is inconsistent
with the conclusions of Roy and Deb (2003), who examine funds in India,
Furthermore, there are some researchers who concentrate their studies solely on
market timing performance, for example Srisuchart (2001) and Chunhachinda and
Tangprasert (2004), who explore timing ability in the Indian mutual funds. Srisuchart
explores equity and bond funds in the 1990s and Chunhachinda and Tangprasert
examine 65 equity funds over 2001-2003. Both of these studies yield the same

conclusion: that Indian equity fund managers have market timing ability. These results
are also comparable to those of Khanthavit (2001), who employs an alternative
technique in examining market timing ability in Indian closed end funds in the 1990s. He
uses a Markov-switching technique and reveals that fund managers exhibit both
selectivity and market timing abilities, although overall performance is not significant.
However, these find managers tend to use their market timing ability when the market is
up and their selectivity ability when the market is down.
Nonetheless, issues outside mutual fund performance evaluation have received less
attention. Fauziah Md and Mansor (2007) look at the issue of persistence in
performance in the Malaysian context as part of their study of mutual fund performance.
They estimate performance annually over the period 1991-2001 and examine the
correlation between past and current performance. They do not find persistence in
performance for mutual funds in Malaysia. However, this contrasts with the evidence in
India. Watcharanaka (2003) reveals persistence in performance in Indian mutual funds
over the period 1992-2002, using a cross-section regression approach in examining 62
funds. Nitibhon (2004) also examines persistence in performance for the Indian mutual
funds. In his study, he constructs portfolios on the basis of past year returns and
estimates performance using unconditional and conditional single-factor models. He
reveals that only the top docile portfolios (high past returns) show significant positive
performance. Some studies explore mutual fund style in relation to performance. These
include: Ferruz and Ortiz (2005), who investigate whether Indian mutual funds
correspond to their classification. They employ factor analysis and cluster analysis and
conclude that funds are very close to one another. Similarly, Acharya and Sidana (2007)

employ cluster analysis to mutual funds in India over the period 2002-2006 and reveal
the inconsistency between investment style and the returns obtained by mutual funds.
In Malaysia, Lau (2007) applies
Sharpe factor analysis to 43 funds over the period 1996-2000. He reveals that funds
which contain large and high liquidity stocks perform better than others.
Regarding the factors related to fund performance in India, Prasomsak (2001)
investigates 77 mutual funds over the period 1998-2000, using fixed-effect regression of
fund raw returns on market returns size, turnover and fund style. He claims that fund
returns are positively correlated with market returns but negatively related to fund size
and turnover.
This finding is in contrast to the findings of Nitibhon (2004), who employs cross-section
analysis and regress fund performance on size, value and growth factors. He reveals
that fund returns are positively related to size and growth stocks.
In addition, the evidence from Taiwan suggests that large funds perform better than
small funds (Shu et al., 2002). Tng Cheong (2007) explores the effect of fund size and
expenses on mutual fund performance in Singapore over the period 1999-2004. He
reveals that large funds perform insignificantly better than small funds and there is no
difference in fund returns between high and low expenses funds.
A study in the flows of mutual funds was conducted by Shu et al. (2002). They
investigate the investment flows of mutual funds in Taiwan over the period 1996-1990
and reveal the difference of behaviour between small- and large-amount investors. Both

small- and large-amount investors tend to buy funds on the basis of short-term
performance.
However, large-amount investors are more rational and redeem funds on the basis of
performance. In India, Nitibhon (2004) estimates mutual fund flows of docile portfolios
rank on the basis of the past year’s returns. He claims that flows are not induced by the
prior year return and suggests no evidence of a smart money effect in Indian mutual
funds.
Reviewing the evidence from the India makes it clear that: first, mutual fund literature in
this region concentrates mainly on performance evaluation. With various techniques
and different samples, most of these studies claim no abnormal returns in mutual fund
performance. Nevertheless, because these studies tend to use a small number of funds
and survey a short sample period, their results are still questionable. This is also
because, as mentioned above, India is highly volatile and there is a certain amount of
evidence of structural breaks.
Second, the evidence suggests that India is inefficient and display several
characteristics which distinguish them from to developed markets. In addition, there are
other factors outside the market risk which have explanatory in stock returns, for
example, size, and value and momentum premium. Nevertheless, mutual fund studies
in India mostly employ standard CAPM-based measures, such as the Sharpe ratio and
Jensen’s alpha and none of these studies take these effects into consideration.
Third, we know very little about other issues related to mutual fund performance.

Evidence on persistence and flows, as well as other factors related to performance, is
relatively small and still mixed.
Consumer perception and satisfaction towards Mutual Funds
Mutual funds have already attracted the attention of global practitioners and
academicians but most of the existing research available is on either accelerating the
return on funds or comparing it with benchmark fund schemes. In marketing literature,
Service
Quality and Customer Satisfaction have been conceptualized as a distinct, but closely
related constructs. There is a positive relationship between the two constructs (Beerli et
al., 2004). The relationship between customer satisfaction and service quality is
debatable. Some researchers argued that service quality is the antecedent of customer
satisfaction, while others argued the opposite relationship. Parasuraman et al (1988)
defined service quality and customer satisfaction as “service quality is a global
judgment, or attitude, relating to the superiority of the service, whereas satisfaction is
related to a specific transaction”. Jamal and Naser (2003) stated that service quality is
the antecedent of customer satisfaction. However, they found that there is no important
relationship between customer satisfaction and tangible aspects of service environment.
This finding is contrasted with previous research by Blodgett and Wakefield (1999), but
supported by Parasuraman et al (1991). Most of the researchers found that service
quality is the antecedent of customer satisfaction (Bedi, 2010; Kassim and Abdullah,
2010; Kumar et al., 2010; Naeem and Saif 2009; Balaji, 2009; Lee and Hwan, 2005;
Athanassopoulos and Iliakopoulos, 2003; Parasuraman et al 1988). Yee et al (2010)

found that service quality has a positive influence on customer satisfaction. On the other
hand, Bitner (1990) and Bolton and Drew
(1991) pointed out that customer satisfaction is the antecedent of service quality. In
2004, Beerli et al supported this finding. Beerli et al mentioned a possible explanation is
that the satisfaction construct supposes an evaluative judgement of the value received
by the customer. This finding is contrasted with most of the researchers.
Investor’s satisfaction in case of mutual funds depends upon amount of trust and
dependence that an investor places with AMC and in turn the benefits that are actually
delivered to them. Although fund managers uses their expertise skills and diligence
while investment but still dissatisfaction prevail among the investors and their
experiences show that majority of mutual funds have shown underperformance in
comparison to risk free return and reported that mutual funds were not able to
compensate them for additional risk they have taken by investing in mutual funds
(Anand, S. And Murugaiah, V.2004). Concept of investor satisfaction is gaining
importance for every MF organization because in addition to its contribution in a
dominating way to the overall success of these organizations, it also shows them
roadmap to retain and grow their business.
Zeithaml, V (1993) expressed satisfaction of individual investor comprise of a range of
varied parameters and is not easy to define but in general it means positive
assessment. Where the growing demand of investor’s expectation is following the way
most of researcher admit the fact that working of customer’s mind is a mystery which is
difficult to solve (Dash, 2006). Customer satisfaction is subjective and even difficult to

measure. To draft an accurate picture of customer satisfaction organizations should
diligently use information – collecting tools and market research that will finally enable
an organization to identify critical elements of customer satisfaction and further fine-
tune their operations to achieve incremental improvements. Significant gaps that exist
between service expectations and perceptions is right from the first step where AMCs
are not found capable enough to translate investor’s expectation, reason being financial
intermediaries having inadequate knowledge and training are not able to communicate
the message to each player effectively.
Consumer behavior
The consumer behavior literature has a long history of study of individual purchase
decisions. Anchored by Howard and Sheth's (1969) comprehensive model, consumer
behavior researchers have developed and tested many constructs believed to comprise
the purchase decision process. In this study, we focus on three of the more ubiquitous:
information sources, selection criteria, and purchase. We explore how these constructs
relate to one another in the mutual fund purchase decision.
Consumer behavior researchers have often modeled the purchase decision process in
the following manner. Initially, consumers gather information on the product class of
interest (i.e., mutual funds in this study) from both internal (e.g., memory of previous
experience) and external (e.g., advertising, brochures, newspaper articles) sources (the
two sources may be referred to as information sources). Armed with this information,
they develop a set of product and service attributes (e.g., price, performance, level of
service) that are important to them in assessing the various alternative product

offerings. Ultimately, consumers use this set of attributes (commonly referred to as
selection criteria) to determine which alternative from the set of available products to
purchase.
The two constructs of information source and selection criteria are quite distinct, yet
closely related. For example, three investors (consumers), whose major information
sources were, respectively. The Wall Street Journal, an investment advisor, and
personal experience with an asset management firm, might form very different selection
criteria. A factor complicating the distinction between information sources and selection
criteria in the mutual fund investment decision is that not only may some information
sources (e.g., published performance rankings) also function as selection criteria, a
single information item may serve a different function at each stage of the decision
process. For example, in the information gathering stage a consumer may use
performance rankings to identify the various possible performance measures (e.g., one-
year, five-year, or ten-year return), or to ascertain whether large fund families in general
outperform small fund families. In the selection criteria stage, the consumer may decide
that one-year return is the most important criterion, then use that criterion to
discriminate and choose among alternative mutual funds.
Consumer behavior researchers spend much effort to develop models of construct
interdependencies in order to predict purchase behavior. In a similar vein, we examine
both how information sources and selection criteria relate to each other, and how they
relate both to demographic profiles of investors and to mutual fund purchase. Through
an investigation of these interrelationships, we hope to develop a richer understanding
of the mutual fund investment decision.

Information sources
In the purchase decision process, consumers may receive twotypes of information—
namely, interpersonal and impersonal (mass) communication.
Interpersonal communication is received from both informal (e.g., family and friends)and
formal (e.g., organizations) sources.-^ Research on the relationship between
information sources and other purchase decision constructs is limited (Engel, Blackwell,
and Miniard, 1986, pp. 259-299). A notable exception is the Vinson and McVandon
(1978) study that identified a strong relationship between the subjects' information
sources and their product concept recall. In addition, Murray (1991) related information
source use to product category (goods versus services) and consumer experience;
internal memory was preferred as a source of information by those with greater
experience.
In related research, the degree of personalization of a service encounter has been
shown to impact the level of consumer satisfaction (Surprenant and Solomon, 1987).
Inthe financial services arena, Carroll (1990) argues that a bank's retail customer mix
maybe enhanced through selective information presentation; and Crosby and Stephens
(1987) demonstrate that insurance customers value personal over impersonal
information sources.
For the mutual fund purchase decision, impersonal sources include advertising, direct
mail, and published fund performance statistics; informal interpersonal sources include
family and friends; formal interpersonal sources include planners—fee-based advisors
(who charge a set fee for their services regardless of transaction volume), and

commission-based advisors (who implicitly charge on a per transaction basis).
Unfortunately, little hard data concerning the relative value that investors place on these
various information sources are available, despite their importance for mutual fund
managers who must allocate resources for communication and distribution.
Selection criteria
Selection criteria embrace the set of product or service attributes that consumers
consider when making purchase decisions among alternatives. Such attributes may be
clearly defined physical attributes, such as the scope of a mutual fund family (i.e. the
number of funds), or may be less precise constructs, such as responsiveness or
perceived confidentiality of a mutual fund sales agent. Fishbein and Azjen (1975) is
perhaps the most widely cited attempt by consumer researchers to model the choice
process. In their multi-attribute model, choice is determined by each alternative's sum of
perceived values on multiple (importance-weighted) attributes. The alternative with the
largest score on independently rated, weighted attributes is selected. Lancaster
(1966)presents a multi-attribute model of consumer choice that may be more familiar to
researchers in economics and finance. He suggests that consumer utility resides in the
characteristics that a good possesses, rather than in the good itself. Thus, preference
orderings for goods are rankings of sets of characteristics (i.e., attributes) and are only
indirectly rankings of goods. We attempt to identify those attributes or characteristics of
mutual funds that are important to investors when making investment decisions.

For a given purchase, three sets of variables—individual, brand or product
characterizes, and purchase context—jointly determine the particular selection criteria
employed.
Individual factors encompass a variety of demographic and psychographic
characteristics of decision makers (Maheswaran and Meyers-Levy, 1990). Brand or
product characteristics, including product features or attributes (e.g., price, quality, and
performance: return and risk for the mutual fund purchase) are widely believed to
impact significantly upon the weighting of selection criteria (Gupta, 1988). Finally,
purchase context (e.g., internal and external framing of the purchase decision) has a
significant impact on selection criteria (Kahneman and Tversky, 1974).
Some researchers have investigated the relationship between consumer selection
criteria and demographic variables. For example, Anderson, Cox, and Fulcher (1976)
find that consumer selection criteria for a bank (e.g., convenience versus service
orientation)is related to several demographic variables (e.g., service-oriented customers
were more likely to have a working spouse and higher income).
In examining the mutual fund investment decision, as noted above, previous research
has focused on the attributes of return and risk. Based on the research reviewed above,
we expect to find that investors employ other selection criteria, either in addition to, or
instead of, risk and return.

3. RESEARCH METHODOLOGY
Research methodology is a systematic and objective search for new knowledge of the
subject of study and or application to knowledge to the solution of a novel problem.
Patel (2004) defines research design as “the structuring of investigation aimed at
identifies variables and their relationship to one another”.
This is use for the purpose of obtaining data to enable the research questions. It is an
outline or a scheme that serves as a useful guide to the research in the efforts to
generate data for the study. The design for this research is descriptive in nature. The
research entails collection of data which is used in making a systematic description of
the existing situation.
The present Research will be divided into two different studies:
Primary Research

Primary Research to know the preference of mutual fund investors regarding their
investment
Secondary Research
Secondary Research to evaluate the performance of Mutual funds which are preferred
by most of the investors is based upon Descriptive Research Design. Three mutual fund
sectors viz. tax Volume 5 Issue 3 (September 2012) funds, diversified funds and sector
funds are selected and top 5 companies based on NAV is selected from each sector for
further analysis. The secondary Research is based upon Judgmental Sampling.
Judgmental sampling is a non-probability sampling technique where the researcher
selects units to be sampled based on their knowledge and professional judgment.
Sampling Method and Sampling Frame
The primary research will be based upon convenience sampling.
Convenience sampling
(Sometimes known as grab or opportunity sampling) is a type of non- probability
sampling which involves the sample being drawn from that part of the population which
is close to hand.
3.1. SAMPLE SIZE DETERMINATION
Primary research is conducted of 100 educated investors of Mumbai city.
3.2. DATA COLLECTION INSTRUMENTS
The data collection instrument used for primary research is questionnaire. The type of
questionnaire used is open and close ended structured.

4. DATA ANALYSIS
The aim of the discussion is providing the needed foundation for offering useful
recommendations in the next chapter which are thought to be essential for improving
the investors’ returns performance.
This chapter will also deals with the presentation and analysis of data collected, and
testing of the hypothesis formulated earlier in chapter one. It is important in a research
project for data to be analyzed and interpreted in the light of the analysis made. Osuala
(1987), states that “the analysis and interpretation of the raw data of an investigation are
the means by which the research problem is answered and the stated hypothesis
tested”. This means that data collected in its real being willed be meaningless and
useless if there are not analyzed and interpreted in a meaningful way. If this is done, the
data therefore becomes information on which basis, decisions are made and
conclusions are drawn from there.

4.1. Presentation of Data
Findings of Demographics
The above table is self-explanatory. However the following observations can be made
Gender Distribution: Total number of respondents is 100 out of which 93% are male
and 7% are female respondents. Hence we can say that the majority of our respondents
are male and due to this reason No further analysis of the impact of gender as a
dependant (demographic) factor on other independent factors is done.

Age Distribution: This shows that majority of the respondents are young and they have
just started their career. It might be possible that these respondents do not have
complete knowledge of mutual fund and they might be investing in various avenues
according to the advices given by their brokers and agents.
Qualification Distribution: A minor portion of 6% of the respondents are high school
pass out while maximum of them i.e. 46% are graduates while 29% and 19% of the
respondents hold Postgraduate and Professional qualification respectively.
Occupation Distribution: 51% of the respondents are salaried employees which forms
a majority. 33% are business persons 12% are practicing professionals (like Chartered
Accountants, Architects, Lawyers etc.) while a minor portion of 4% of them are retired
employees.
Income Distribution: Majority of the respondent’s i.e.59% lie in the slab of annual
income between Rs. 3-5lakhs. 34% of the respondents have an income ranging from
Rs. 5-15 lakh, while a minor portion of 6% and1% of the respondents have an annual
income of Rs.15-25 lakh and above Rs. 25 lakh respectively.

Preferred Investment Avenue by investors:
Ranking the Kind of investments preferred by the respondents
Factor preferred most while making investment and Age of investors:

The investors who are of the age of less than 30 are more attracted by the high returns
followed by low risk involved and then liquidity or company reputation. Investors in the
age group of 31-40 years of age also give high preference to high return. On the other
hand the investors between the age group of 41-50 are evenly distributed for factors like
liquidity, high return and low risk. Investors above 50years of age prefer low risk more
than any other factor.
Out of total sample of 100 investors, 75 investors are investing in to mutual funds. So
further Analysis is done with sample of 75 investors.
Annual income of the respondent and % investment of mutual fund in total
Investments
The respondents having an annual income of 3-5 lakhs usually prefer to invest less than
Rs. 20000 or between 20000-50000 in mutual fund while investors with anannual
income between 5-15 lakhs usually prefer toinvest between 20000-50000. On the other
handinvestment of more than 100000 in mutual fund is madeonly by the investors
having an annual income rangingbetween 5-15 lakhs. Annual income of the
individualinvestor and annual investment in mutual fund are Independent of each other.

Share of Mutual Funds in your total Investment:
The cross tabulation clearly states that no matter in which income slab the investor
might lie, he would mostly prefer to invest 0-33% of his total investments in mutual
funds. There are around 15 no of investors who would prefer 25-50% of their
investments in mutual fund, while only 5 investors prefer 50-75% investments in mutual
fund. This is the minimum. Moreover the above table also states that annual income
does not have any impact on % investment of mutual fund out of total investment and a
high income does not mean that his investment in mutual fund would also be high.
Share of mutual funds in the total investment and the income of the investors are
independent of each other.

Qualification of the respondent and knowledge about mutual fund
The above cross tabulation shows those investors who are just high school pass out are
mostly aware of the specific scheme in which they have invested. The graduates are
either mostly partially aware of mutual fund or fully aware of the specific scheme. It can
be clearly seen that whatever the qualification maybe the investors are on an average
aware of the scheme in which they have invested and their qualification plays a little role
to determine their knowledge about mutual funds.

Qualification and knowledge about mutual funds have moderate correlation with each
other.
Occupation of the respondent and the feature that allures him the most while
investing in mutual fund
Thus there is no significant relationship between two variables. Occupation of individual
investor and the feature that allures him the most are independent of each other

Preferred mode to receive the returns and frequency to receive the returns from a
mutual fund scheme
The table above shows that there is significant relationship between two variables.
Mode preferred to receive returns yearly and the type of Return expected by the
investors is dependent on each other.
Findings related to Schemes most preferred by the investors:

Investors mostly prefer equity schemes while making investment into mutual funds.
Amongst equity schemes also equity tax savings (ELSS), Equity diversified scheme and
Equity sectoral schemes are mostly preferred by the investors.
Based on this preference top 5 schemes are selected from each of this category and its
Performance is measured on the basis of secondary data analysis and schemes are
identified which have outperformed the market. The analysis is as follows.
Equity Tax Savings Scheme
Risk Analysis:

The Risk analysis of Equity Tax Planning top 5 schemes have a varying attributes such
as Standard deviation, Sharpe, Beta, Treynor and Correlation which measures the
schemes in terms of risk to the portfolio or the individual schemes. For the return
analysis of Equity Tax Planning top 5schemes it can be seen that all the returns of 1
month,3 months, 6 months and 1 year are having negative returns so here investor
have to invest minimum for 3years to get returns in positive value. The returns of such
schemes since inception have shown a growth but on a fluctuating basis as the scheme
Canara Robeco
Equity Tax saver - Growth and Franklin India Tax shield- Growth which is ranked fourth
and third respectively shows the highest return since inception of 32.82 and25.85 while
the schemes such as BNP Paribas Tax Advantage Plan - Growth and Axis Long Term

Equity Fund - Growth which are ranked second and first respectively have the lowest
growth amongst the top 5schemes. So the investors who have invested in the schemes
whose growth has been highest have benefited more than the investors who had
invested in the first two schemes.
Canara Robeco Equity TaxSaver - Growth is considered as a better scheme but with
standard deviation, beta and correlation to also be considered then Axis Long
Term Equity Fund - Growth is considered as a viable investment option.
Amongst the top 5 schemes of Equity Diversified funds, It can be said that UTI Wealth
Builder Fund - Series II
- Growth is said to be the most advisable one irrespective of the ranking giving on the
basis of NAV, so similarly Canara Robeco Large Cap+ Fund -Growth is said to be the
least advisable to the investors.
Hence these schemes are not having the same ranking as per the preference given on
the basis of the risk analysis so it can be said that Standard Deviation,
Sharpe, Beta, Treynor and Correlation are not the only measure of fund ranking
analysis.

Equity Diversified Schemes:
Risk Analysis:

Amongst the top 5 schemes of Equity Diversified funds, it can be said that UTI Wealth
Builder Fund - Series II
- Growth is said to be the most advisable one irrespective of the ranking giving on the
basis of NAV, so similarly Canara Robeco Large Cap+ Fund -Growth is said to be the
least advisable to the investors.
Hence these schemes are not having the same ranking as per the preference given on
the basis of the risk analysis so it can be said that Standard Deviation,
Sharpe, Beta, Treynor and Correlation are not the only measure of fund ranking
analysis.
Return Analysis

The top 5 schemes of Equity Diversified funds are having negative returns for short term
investments that include 1month, 3 months, 6 months and 1 year. But for the investors
who wants to invest for a long term period they will be benefited with the positive return.
The most beneficial scheme is the Edelweiss Absolute Return Fund - Growth but if the
return of the schemes are considered then UTI Wealth Builder Fund - Series II - Growth
and SBI Magnum Sector Funds Umbrella- Emerging Buss Fund - Growth are more
viable from the investment point of view again the investors who have invested in these
schemes since last 3 years have benefited more in comparison with the investors who
have invested in such schemes since inception. So the most profitable period for
investors to invest in the Equity Diversified schemes can be said is of last 3 years.
Again as per the ranking
Equity Sector Funds
Risk Analysis

In the top 5 schemes of Equity Sector funds for risk analysis all the measure have more
or less the same result so there is hardly any difference in the preference. High Sharpe
and Treynor. And SBI Magnum Sector Funds Umbrella - Pharma - Growth can be said
to be least preferred from amongst others in case of risk analysis of top 5 schemes of
equity sector funds.
Return Analysis

The investment in the top 5 schemes of Equity Sector
Funds advisable for a long term period as investment in short term period yields
negative returns to the investor. So only those investors who are planning to retain the
mutual fund investment as their asset for more than a year invest in such schemes. The
growth in 3 years investment in higher than the growth in the 5years investment and a
balance growth between the two is for the investors who had invested in the Equity
Sector Fund since inception. As per the ranking the SBI Magnum Sector Fund
Umbrella-Pharma-Growth is the first ranked scheme to invest in but the scheme that
has shown the highest growth in terms of return is the Reliance Pharma Fund - Growth
scheme. Irrespective of the long term period of investment that is 3 years, 5 years or
since inception the Reliance Pharma Fund - Growth have shown the highest growth in
terms of return analysis to the investor. But others schemes in the Equity Sector Fund
also have a good amount of return to the investor as all the schemes have more or less
the similar return to the investors.

5. RECOMMENDATIONS
 One should diversify the investments between a few funds (the actual number
depends entirely on the amount of investment). This strategy ensures that the portfolio
is not dependent on the performance of one single fund. However, one needs to avoid
over-diversification as that would achieve nothing.
 Investor can also plan like one mutual fund of diversified equity plan, second
mutual fund of balanced type and third one you can plan of debt type etc. In this manner

the money will get diversified, risk is reduced and the investor will get excellent profit.
For Example: Rs 20,000 per month, it would be wise to opt for a maximum of three
funds. Consider well rated large-cap funds, mid-cap funds and a balanced fund. The
latter would provide the debt component and reduce the portfolio's downside risk.
 Don't just judge a fund by its NAV only.
 Never judge a fund on the basis of its NAV. Also have a look at the Standard
Deviation, Sharpe ratio, Treynor Ratio, Beta, Correlation, P/E Ratio, P/B
 Ratio and Expense Ratio & also its performance in the bear and the bull phase,
and then invest in it. Only judging a fund by its NAV, is irrelevant while selecting the
fund as it is the percentage gain or loss that matters.
 Also look for past returns, dividend etc. the mutual fund has declared. If the
investor has chosen equity or stock market related mutual fund, then he may go for SIP
(Systematic Investment Plan) method.
 A risk adverse investor should avoid investing in the Sectoral funds.
 AMC's use NFOs to create excitement and push their funds. These schemes are
launched because they are easy avenues to capture management fees and increase
the fund house's asset base. These schemes are usually just clones of existing
schemes, but with new peppy names flaunted to attract investors.
 It is important for investors to understand that NFOs are merely marketing
devices. There are a number of existing funds that have proved their mettle and
investors should opt for them because they have a track record

6. CONCLUSION
We reviewed existing performance measures and empirical results as well as other
relevant issues in mutual fund performance which have been widely discussed over a
decade. The mutual fund performance measures are largely influenced by the modern
portfolio theory.
The criticisms of the validity of the Capital Asset Pricing model and the evidence
suggesting that other variables outside the market risk can also explain stock returns
have amplified more recent models to become richer and more informative. These
models not only help to evaluate performance more efficiently but also allow us to

examine further the style and strategy which a fund manager follows. Empirical
evidence suggests that fund managers adjust portfolios dynamically on the basis of
economic information; invest heavily in small and value stocks; and make use of
momentum strategy. Nevertheless, in most cases, they are unable to outperform the
market, at least, once fees and expenses have been deducted. This indicates that fund
managers do not give value added to investors and this is partly due to the high fees
and expenses charged. The other two crucial concerns which are widely discussed in
the mutual fund literature are persistence in performance and the effect of fund flows on
fund performance. Nevertheless, the results in these studies are still mixed.
With regard to the extensive literature on mutual fund performance, we find that these
studies are concentrated in the US and other developed countries and research within
the emerging regions is still scant, even though they are in many respects unlike the
developed markets. For example, India suffers from infrequent trading, inefficiency and
high volatility and high trading cost. More importantly, the mutual fund industries in India
are distinctive from those in the developed markets in terms of growth, competitiveness,
and organizational structure and information availability. Moreover, it is still questionable
whether the findings in the developed markets carry over to the India. The gap between
the studies in developed and emerging countries is also owing to the sample size and
the models used in the studies. Most studies of the mutual funds in India employ a short
sample period, although these markets provide evidence of structural breaks.
Furthermore, these studies are still based on the prevailing approaches, such as the
Sharpe ratio, Treynor ratio and Jensen’s alpha, which involve many criticisms: for

instance, evidence from both the developed and the India suggests that there are other
factors which can explain stock returns and the risk factor is not constant over time.
In addition, the literature on mutual funds in India reveals that the main concern in this
region lies in performance evaluation. Very little has been written on other issues
related to mutual fund performance, such as style and performance determination.
Hence, these prevent a fuller understanding of the mutual fund business. Thus, this
study chooses to examine mutual funds in India, using India as a case study, and
comes up with three promising research ideas. First, we apply performance measures
in the existing literature to the mutual funds in India and investigate its performance
comprehensively. Second, we examine the factors related to mutual fund performance.
Third, we examine the effect of liquidity, as one of the main concerns in India in regard
to mutual fund performance, and elaborate an auxiliary performance measure.

7. BIBLIOGRAPHY
 Grinblatt, Mark and Sheridan Titman, 1989. "Mutual Fund Performance: An
Analysis of Quarterly Portfolio Holdings." Journal of Business, Vol. 62,No. 3, pp.
393-416
 Sadhak, H., 1991, "The alternate saving media", The Economic Times, April 30,
9.
 Madhusudan V. Jambodekar, 1996, Marketing Strategies of Mutual Funds –
Current Practices and Future Directions, Working Paper, UTI – IIMB Centre for
Capital Markets Education and Research, Bangalore.
 Atmaramani, 1996, "Restoring Investor Confidence", The Hindu Survey of Indian
Industry, 435-437.
 Shankar, V., 1996, "Retailing Mutual Funds : A consumer product model", The
Hindu, July 24, 26.
 Sharma C. Lall, 1991, "Mutual Funds - How to keep them on Right Track",
Yojana, Vol.35, No.23, Dec.18-19
 Anjan Chakrabarti and Harsh Rungta, 2000, "Mutual Funds Industry in India : An
indepth look into the problems of credibility, Risk and Brand", The ICFAI Journal
of Applied Finance, Vol.6, No.2, April,27-45
 Kavitha Ranganathan, Madurai Kamaraj University(2006), A Study of Fund
Selection Behaviour of
 Individual Investors Towards Mutual Funds – with Reference to Mumbai City ,
Indian Institute of Capital Markets 9th Capital Markets Conference Paper

 Dr S Narayan Rao, M Ravindran, Manager (2003),Performance Evaluation of
Indian Mutual Funds, SSRNsearch library.
 Sharad Panwar and R. Madhumathi ,(2006),Characteristics and Performance
Evaluation of Selected Mutual Funds in India , Indian Institute of Capital Markets
9th Capital Markets Conference
 Paper Rajeshwari T.R and Rama Moorthy V.E., (2002)
 Performance Evaluation Of selected Mutual Funds and Investor Behaviour, PhD
Thesis, Sri Sathya Sai Institute of Higher Learning, Prasanthinilayam
 Syama Sundar, P.V., 1998, "Growth Prospects of Mutual
 Funds and Investor perception with special reference to Kothari Pioneer Mutual
Fund" , Project Report, Sri Srinivas Vidya Parishad, And University,
Visakhapatnam
 Vidya Shankar, S., "Mutual Funds - Emerging Trends in India", Chartered
Secretary, Vol.20, No.8, 1990,639-640.

APPENDIX I
COVER LETTER
Dear Respondent,
I am a postgraduate student of the above named Institution involved in a research work
for the partial fulfillment of the requirements for the award of Management Degree. I am
undertaking a research work on the topic: “Evaluation of mutual fund performance in the
present market condition”.
Kindly respond to the following questions either by ticking the correct answer or by filling
the blank spaces. Your response will be treated confidentially.
Yours faithfully,
___________________

QUESTIONNAIRE
1. What is your Gender?
2. What is your Age?
3. What is your Qualification?
4. What is your Occupation?
5. What is your monthly Income?
6. What is your Preferred Investment Avenue?
7. How do you rank the various kinds of investments preferred by the you?
8. What factor is preferred by you most while making investment ?
9. What is the Share of Mutual Funds in your total Investment portfolio?
10.What feature that allures you the most while investing in mutual fund?
11.What is your preferred mode to receive the returns and frequency to receive the
returns from a mutual fund scheme?
12.List the Schemes most preferred by you?
13.List the top schemes preferred by you of Equity Sector?

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