PERCEPTUAL MAPPING FOR MUTUAL FUND

INVESTMENT

by

MEGALAA.J(Reg. No.31708631054)

A PROJECT REPORT

Submitted to the

FACULTY OF MANAGEMENT STUDIES

In partial fulfillment of the requirements For the award of the degree

Of

MASTER OF BUSINESS ADMINISTRATION

IN

FINANCE AND HUMAN RESOURCE

St.JOSEPH’S COLLEGE OF ENGINEERING, CHENNAIANNA UNIVERSITY

CHENNAI 600 025.

SEPTEMBER 2009

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ST. JOSEPH’S COLLEGE OF ENGINEERING (Affiliated to Anna University)

JEPPIAR EDUCATIONAL TRUST JEPPIAR NAGAR, OLD MAMALLAPURAM ROAD, CHENNAI – 119.

BONAFIDE CERTFICATE

Certificated that the project report titled “PERCEPTUAL MAPPING FOR MUTUAL

FUND INVESTMENT” is the bonafide work of “MEGALAA.J” Reg.no. 31708631054

who carried out the research under my supervision. Certificated further, that to the

best of my knowledge the reported herein does not from part of any other project

report or dissertation on the basis of which a degree or award was conferred on an

earlier occasion on this or any other candidate.

Dr .D.RADJAMANOGARI, Dr. JAYASREE KRISHNAN, M.Com., M.A., BGL.,M.B.A., M.Phil., B.Sc., M.B.A., PhD Asst., Lecturer., HEAD OF THE DEPARTMENT GUIDE Department of Management Studies, Department of Management Studies, St. Joseph’s College of Engineering, St. Joseph’s College of Engineering, Jeppiar Nagar, Jeppiar Nagar, Old Mahabalipuram Road Old Mahabalipuram Road, Chennai – 600 119. Chennai - 600 119.

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ABSTRACT

To find out the perceptual mapping for mutual fund schemes used by the customer.

Mutual funds provide various schemes to customers, where each scheme is targeted to

different segments, this study helps us in identifying the actual targeted segments of each

scheme of mutual funds from customer perceptive. Opinion will be collected from customers.

Position of different schemes will be done by using Multidimensional Scaling technique for

the selected variables. The selected variables are risk, safety, return, liquidity, availability

aspects and usage experience. From this the customers can understand where there is a gap

and where there is a cluster; accordingly they can use a new scheme for investment or

restructure the existing scheme.

The thesis consists of five chapters. The first chapter contains the introduction and

details about the perceptual mapping process. It also includes the profiles of different mutual

fund schemes for investment. It also elaborates on the objectives of the study. The second

chapter focuses on the review of literature. The third one discusses the type of analysis and

the method of data collection. The fourth chapter forms the core with in-depth study of the

various criteria of the respondents and various inferences drawn from the analysis. The last

chapter houses the findings, suggestions, and conclusion.

The type of research carried for the study is descriptive research and sampling taken is

non-probability convenience sampling. The data source used is primary data. The sample size

chosen is 50. The mode of data collection is done through questionnaire. In this method

questionnaire is given to the respondent consent with request to answer the questionnaire.

The respondent has to answer the questionnaire on their own. Most of the questions are

multiple choices and dichotomous. The statistical tools applied are MULTIDIMENSIONAL

SCALING, CHI-SQUARE, and MEAN PLOT.

ACKNOWLEDGEMENT

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I would like to express my gratitude to take this opportunity to express my profound

sense of gratitude and to extend my best wishes to all people who have guided, inspired and

motivated me during this project, which gives me immense pleasure to acknowledge their co-

operation.

I would have to render my deep sense of gratitude to our beloved

chairman Dr. Jeppiar, M.A., B.L., Ph.D., and our Director Dr. B. Babu manoharan, M.A.,

M.B.A., Ph.D., for all their effort and administration in educating us in their premier

institution.

My sincere thanks to our Principal Dr. JOLLY ABRAHAM, M.E., Ph.D., and our

Head of Department and my internal guide Dr. JAYASREE KRISHNAN, B.Sc., M.B.A,

Ph.D., for their kindness and guidance. Without their guidance this project would not have

been completed.

I specially thank Dr .D.RAJAMANOGARI, M. Com., M.A., BGL.,M.B.A., M. Phil., PhD., for his special guidance and motivation, without his invaluable help & support; this project work would have never been possible.

I express my sincere thanks to all other staff members of who has directly or

indirectly helped me in carrying out this project.

I wish my heart full gratitude to my family members who has been the primary source

of inspiration for my success; last but not least, I wish to thank my friends who really gave

me some boost to complete my project.

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INDEX

INDEX…………………………………. ……………………………………………………. iLIST OF TABLES iiLIST OF CHARTS iiiCHAPTER I 1INTRODUCTION 41.2 COMPANY PROFILE1.3 PRODUCT PROFILE1.4 INDUSTRY PROFILE1.5 NEED OF THE STUDY1.6 OBJECTIVES OF THE STUDYCHAPTER 2 12REVIEW OF LITERATURECHAPTER 3 173.1 TYPE OF RESEARCH3.2 DATA SOURCE3.3 RESEARCH INSTRUMENTS3.4 PILOT SURVEY3.5 SAMPLE UNIT3.6 SAMPLING TECHNIQUE3.7 SAMPLE SIZE3.8 PLACE OF STUDY3.9 PERIOD OF THE STUDY3.10 DATA ANALYSIS3.11 STATISTICAL TOOLSCHAPTER 4………………………………………………………………………………….224.1 ANALYSIS AND INTERPRETATION CHAPTER 5 365.1 FINDINGS 365.2 SUGGESTIONS 385.3 CONCLUSION 39ANNEXUREBIBILOGRAPHY 40QUESTIONNAIRE 41

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LIST OF TABLES

4.1.1 Gender of the respondents 224.1.2 Age group of the respondents 234.1.3 Education level of the respondents 244.1.4 Profession of the respondents 254.1.5 Family income per annum 264.1.6 No. of person in the Family 274.2.1 Preferred schemes of mutual funds 274.2.2 Mutual fund schemes preferred by the respondents and

Demographic variables

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LIST OF CHARTS

Chart No Title Page No

4.1.1 Gender of the respondents 224.1.2 Age group of the respondents 234.1.3 Education level of the respondents 244.1.4 Profession of the respondents 254.1.5 Annual family income of the respondents 264.1.6 No. of person in the Family 27

4.2.2 Mutual scheme preferred 294.2.3 Return of the schemes 304.2.4 Risk of the schemes 314.2.5 Liquidity of the schemes 324.2.6 Safety of the schemes 334.2.7 New fund offering of the schemes 344.2.8 Expectation met by the schemes 35

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CHAPTER I

INTRODUCTION

1.1 Introduction to the Project

Perceptual mapping is used to describe a set of techniques designed to represent

perceptions about various mutual fund schemes and their similarities in a visual "space".

It is useful for providing highly intuitive representations in order to position mutual

fund schemes on dimensions critical to consumer perceptions in that visual space, a variety of

simple to complex statistical methodologies can be used to create them. Some of the latter

include multi-dimensional scaling, factor or cluster analytical methods, and conjoint analysis.

Usually these techniques result in schemes being mapped on 2 to 3 dimensions. Two-

dimensional maps are the most popular as they are most easily understood and interpreted by

clients. There is also substantive agreement that consumers use only a limited number of

separate (though sometimes complex and integrative) concepts to assess mutual fund

schemes.

Every scheme has value locked deep within it. Perceptual mapping process it provide

insight into consumers’ motivations, prejudices, and desires to unlock that value. By charting

your schemes current position and its expected future, it empowers customers to evaluate

misalignments, potential opportunities, and hidden value—revealing whether they should

maintain position, or take action to reposition.

It outlines the facts and opinions that affect your market and audience to identify the

keys to unlocking your hidden scheme value.

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1.2 SCHEME PROFILE

Mutual fund schemes:

A mutual fund scheme can be classified into open-ended scheme or closed-ended

scheme depending on its maturity period.

1.2.1 Open-ended Fund

An open-ended mutual fund is one that is available for subscription and repurchase on

a continuous basis. These funds do not have a fixed maturity period. Investors can

conveniently buy and sell units at Net Asset Value(NAV) related prices which are

declare on a daily basis. The key feature of open-end schemes is liquidity.

1.2.2 Close-ended Fund

A close-ended mutual fund has a stipulated maturity period e.g. 5-7 year. The fund is

open for subscription only during a specified period at the time of the initial public

issue and thereafter they can buy or sell the units of scheme on the stock exchanges

where the units are listed. In order to provide an exit routed to the investors, some

close-ended funds give an option of selling back the units to the mutual fund through

periodic repurchase at NAV related prices. SEBI regulations stipulate that at least one

of the two exit routes is provided to the investors i.e. either repurchase facility or

through listing on stock exchanges. These mutual funds schemes disclose NAV

generally on weekly basis.

1.2.3 Growth

The aim of growth funds is to provide capital appreciation over the medium to long-

term. Such schemes normally invest a major part of their corpus in equities. Such

funds have comparatively high risk. These schemes provide different options to the

investors like dividend option, capital appreciation, etc. and the investors may choose

an option depending on their preferences. The investors much investors must indicate

the option in the application form. The mutual fund also allows the investors to

change the options at a later date. Growth schemes are good for investors having a

long-term outlook seeking appreciation over a period of time.

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1.2.3.1 Income oriented scheme

The aim of income funds is to provide regular and steady income to investors. Such

schemes generally invest in fixed income securities such as bonds, corporate

debentures, government securities and money market instruments. Such funds are less

risky compared to equity schemes. These funds are not affected because of

fluctuations in equity market. However, opportunities of capital appreciation are also

limited in such funds. The NAVs of such funds are affected because of change in

interest rates in the country. If the interest rates fall, NAVs of such funds are likely

to increase in the short run and vice versa. However, long term investors may not

bother about these fluctuations.

1.2.4 Liquid Fund

These funds are also income funds and their aim is to provide easy liquidity,

preservation of capital and moderate income. These schemes invest exclusively in

safer short-term instruments such as treasury bills, certificates of deposit, commercial

papers and inter-bank call money, government securities, etc. Returns on these

schemes fluctuate much less compared to other funds. These funds are appropriate for

corporate and individual investors as a means to park their surplus funds for short

periods.

1.2.5 Balanced Funds

The aim of balanced funds is to provide both growth and regular income as such

schemes invest both in equities and fixed income securities in the proportion indicated

in their offer documents. These are appropriate for investors looking for moderate

growth. They generally invest 40%-60% in equity and debt instruments. These funds

are also affected because of fluctuations in share prices in the stock markets.

However, NAVs of such funds are likely to be less volatile compared to pure equity

funds.

1.2.6 Gilt Fund

These funds invest exclusively in government securities. Government securities have

no default risk. NAVs of these schemes also fluctuate due to change in interest rates

and other economic factors as is the case with income or debt oriented schemes.

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1.2.7 Index Fund

Index Funds replicate the portfolio of a particular index such as the BSE sensitive

index, S&P NSE 50 index (Nifty), etc. These schemes invest in the securities in the

same weightage comprising of an index. NAVs of such schemes would rise or fall in

accordance with the rise or fall in the index, though not exactly by the same

percentage due to some factors known as “tracking error” in technical terms.

Necessary disclosure in this regard are made in the offer document of the mutual fund

scheme. There are also exchange traded index funds launched by the mutual funds

which are traded on the stock exchanges.

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1.3 INDUSTRY PROFILE

First Phase (1964-87): Unit Trust of India (UTI) was established on 1963 by an

Act of Parliament. It was set up by the Reserve Bank of India and functioned under the

Regulatory and administrative control of the RBI. In 1978 UTI was de-linked from the

RBI and the Industrial Development Bank of India (IDBI) tool over the regulatory and

administrative control in place of RBI. The first scheme launched by UTI was Unit

Scheme 1964 . At the end of 1988 UTI had Rs.6, 700Crores of assets under

management.

Second phase (1987-1993) (Entry or Public Sector Funds): The year 1987 marked

the entry of non-UTI ,public sector mutual funds set up by public sector mutual funds set up

public sector banks and Life Insurance Corporation of India(LIC) and General Insurance

Corporation of India (GIC) . SBI Mutual Fund was the non-UTI Mutual Fund established in

June 1987 followed by Can bank Mutual Fund (Dec 87) , Punjab National Bank Mutual

Fund (89) , Indian Bank Mutual Fund (Nov 89).Bank of India(Jun 90),Bank of Baroda

Mutual LIC establish its mutual fund in June 1989 while GIC had set up its mutual fund in

December 1990.

Third Phase (1993-2003) (Entry of Private Sector Funds) :With the entry of

private sector in 1993, a new era started in the Indian mutual fund industry , giving the

Indian investors a wider choice of fund families.Also,1993 was the year in which the first

Mutual Fund Regulations came into being, under which all mutual funds, except UTI were to

be registered and governed. The erstwhile Kothari Pioneer (now merged with Franklin

Templeton) was the first private sector mutual fund houses went on increasing, with many

foreign mutual funds setting up funds in India and also the has witnessed several mergers and

acquisitions.

Fourth Phase- since February 2003: In February 2003, following the repeal of the

Unit Trust of India Act 1963 UTI was bifurcated into separate entities. One is the specified

undertaking of the UTI with assets management of Rs.29,835Crores as at the end of

January 2003,representing broadly , the asset of US 64 scheme ,assured return and certain

other schemes .The specified Undertaking of Unit Trust of India ,functioning under an

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administrator and under the rules framed by Government of India and does not purview of

the Mutual Fund Regulations.

The second is the UTI Mutual Fund Ltd, sponsored by SBI, PNB, BOB and LIC.

It is registered with SEBI and functions under the Mutual Fund Regulations. With the

bifurcation of the erstwhile UTI which had in March 2000 more than Rs. 76,000Crores of

assets under management and with the setting up of a UTI Mutual Fund, conforming to the

SEBI Mutual Fund Regulations, and with recent mergers taking place among different

sector funds, the mutual fund industry has entered its current phase of consolidation and

growth .

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1.4 OBJECTIVES OF THE STUDY

To map various schemes of mutual funds with respect to different attributes

like returns, risk, safety, liquidity, availability, and usage experience.

To find out segments served by each mutual fund scheme.

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CHAPTER 2

REVIEW OF LITERATURE

Overview of Perceptual MappingWilliam D. Neal The Sawtooth Software Conference on:

Conjoint Analysis, Perceptual Mapping, and Computer Interviewing

INTRODUCTION

Perceptual mapping is one of the few marketing research techniques that provides

direct input into the strategic marketing planning process. It allows senior marketing planners

to take a broad view of the strengths and weaknesses of their product or service offerings

relative to the strengths and weaknesses of their competition. It allows the marketing planner

to view the customer and the competitor simultaneously in the same realm.

Perceptual mapping and preference mapping techniques have been basic tools of the

applied marketing research profession for over twenty years now. It is one of the few

advanced multivariate techniques that have not suffered very much from alternating waves of

popularity and disfavor. Although I personally observed a minor waning of the use of the

techniques in the early 1980's, it is now as popular as ever.

And although these techniques have been used extensively over a large number of

applied research studies, and for a very wide variety of product and service categories, and

have been subjected to extensive validations, there still remain some very basic issues as to

the procedure's applicability and usefulness.

In addition, there remain many outstanding issues concerning the proper procedures

and algorithms that should be used for perceptual mapping.

So, I see that my main task at this conference is to raise the issues, as I see them. I am taking

a rather naive approach. That is, I will approach these issues from the research manager's

point of view, and not the statistician's. These issues represent the kinds of questions that my

clients ask me and my staff. Obviously, I have some answers, and some biases, but I will try

to minimize those, and concentrate on the issues.

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I know that many of these issues will be addressed at this conference, both in formal

presentations and in informal discussions. I am taking this route in the hope that this

introduction will encourage greater investigation, increase validation activities, and provide

fuel for additional conferences of this type.

CURRENT ISSUES IN PERCEPTUAL MAPPING

A. Defining and limiting the relevant space

How is the relevant space limited? There are three types of limitations that must be

placed on the relevant multivariate space that will be analyzed and mapped. They are:

1. Limits on the population that is to be surveyed. This seldom poses a serious

problem because it tends to be self-defining in terms of users, or purchasers of the

products, services, or firms in question. However, there are questions as to how

familiar a respondent is with a product, or brand. This will be discussed in a later

section.

2. Limits on the relevant set of variables that will be used to define the perceptual

space. In my opinion, this is the most critical area for setting limitations, except

for those using the scaling methods based on overall product similarities. The

major question to the applied researcher is what variables are to be used to orient

the perceptual positioning of the various competitors. There is a nearly unlimited

set of variables available.

3. Limits on the relevant set of products, services, or firms that will be mapped into

the multivariate space is also a major issue. Although I don't believe that this is as

critical an issue as the selection of the relevant variable set, it is still a serious one.

A balance is required.

B. Are there particular product categories or merchandise lines or firm types where

discriminant analysis-based mapping works better? If so, then what are the characteristics of

those product categories or industries?

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C. Is "high involvement" in the respondent rating process a necessary prerequisite for

multivariate mapping? What level of familiarity is necessary and sufficient to include a set of

ratings into the definition of the relevant multivariate space?

D. Extracting the dimensions.

1. What are some good rules of thumb for determining how many dimensions to

use? How much variance needs to be explained to be comfortable? How should

we handle dimensions with low variance explained, but test as significant?

2. How do you display more than two dimensions? What procedures and graphics

algorithms are available? What graphics procedures best convey the information

in the multivariate space to managers and creative professionals?

3. If you are forced to use a two-dimensional map, but have three or more significant

dimensions, how do you adequately show those attributes that are heavily loaded

on the third dimension? Or, do you eliminate those from the display. If you do

eliminate them, what criteria should you use?

4. What actions should you take when the first extracted dimension explains much

more variance then the second dimension? Is it appropriate to display those two

dimensions as equal axes in the map?

E. Plotting the variables in the derived space raises some interesting questions.

1. Should variable coordinate weighting be used to show differences in the amount

of variance explained by each axis?

2. If so, what should be used as the appropriate weights percent of variance

explained by each axis, eigen values, or something else?

F. Plotting the firms/products in the perceptual space

1. How should we show which products or firms are significantly different from

others on the map?

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2. Does anyone attempt to draw confidence limits around the mapped points

anymore?

G. Is longitudinal mapping a valid concept? What are the critical issues in overlaying maps?

What are the best methods for doing this?

1. Line up "index" points from successive time periods so as to minimize the

variance between them? Should the index points be the vector of importance

ratings, or some other measure?

2. Select a very stable vector that consistently discriminates between at least two of

the products or firms, and minimize the variance between their positions over

successive time periods?

3. Use both of these methods in combination?

4. Re-generate the dimensions with each attribute from each time period representing

a separate attribute, and each product from each time period representing a

separate product?

5. Always use the original space, and simply plug in the standardized means for each

product from successive time periods into the linear dimensional equations and

calculate the new coordinates?

6. What other procedures are being used?

H. How can you incorporate volumetric data into multivariate mapping? In other words, how

can you show the marketing manager where the greatest demand exists on the map or where

the opportunities are?

a. Are scatter plots of grouped respondent locations the only thing available?

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b. Or, can we develop a surface plot over the mapped space that will depict

such things as dollars spent, or number of items bought, or even number of

times visited? What methods are being used now? What could be done with

the new graphics packages combined with multivariate "smoothing"

routines to superimpose surface plots over the derived space?

CONCLUSIONS

Needless to say, there are still many outstanding issues and further development

opportunities with multivariate mapping procedures. I'm sure that there are others besides

these. I would like to challenge the readers to address these issues, share them with your

peers, publicize solutions to them, freely subject them to validations, and give us more

specificity in executing this most powerful and useful marketing research procedure.

De bond and Thaler (1985) while investigating the possible psychological basis for

investor behavior ,argue that mean reversion in stock prices is an evidence of investor over

reaction where investor over emphasize recent firm performance in forming future

expectations.

Shanmugham (2000) conduct a survey of 201 individual investors to study the

information sourcing by investors,their perception of various investment strategy dimention

and the factors, psychological and sociological factors dominated the economic factors

dominated the economic factors in share investment decisions.

Incidentally ,an investment in mutual funds would be entitled to indexation benefits in

the computation of capital gains, which would ortherwise be denied to a direct investment in

debt securities .It is a common observation that large companies deploy their investible

surplus in the fixed income schemes, which involves negligible downward risk, and seek to

leverage the tax arbitrage.

From press reports that mutual funds offer special plans, titled as serial plans, which

allow an investors to be the sole member of a scheme and the deployment of the money is

effected in avenues choosen by the said investor.

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CHAPTER 3

RESEARCH METHODOLOGY

3.1 TYPE OF RESEARCH

Descriptive research has been used in this study. Descriptive research includes

surveys and fact finding enquiries of different kind. The major purpose of descriptive

research is description of the state of affairs as it exists at present. The main feature of this

method is that, the researcher has no control over the variables; the researcher can only report

what has happened or what is happening. The descriptive research discovers the causes, even

when they cannot control the variables. Descriptive research provides data about the

population or universe being studied. But it can only describe the “who, what, when, where

and how “of a stimulate .not what caused it. Therefore, descriptive research is used when the

objective is to provide a systematic description that is as factual and accurate as possible. It

provides the number of times something occurs, or frequency, lends itself to statistical

calculations such as determining the average number of occurrences or central tendencies.

This type of research is also a grouping that includes many particular research

methodologies and procedures, such as observations, surveys, self-reports and tests. The four

parameters of research will help us understand how descriptive research in general is similar

to, and different from, other types of research. It may focus on individual subjects and go into

great depth and detail in describing them. Individual variation is not only allowed but also

studied.

DATA SOURCE:-

Data sources refer to the various means through which data is collected.

Data could be primarily classified as

Primary data

Secondary data

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PRIMARY DATA:

It is the data collected for the first time through field survey. It is collected

with a specific set of objectives to assess the current status of variable studied. In short

primary data is the original data collected by the researcher first hand. Primary data has been

collected for this study. As this is descriptive research, surveys were performed. The primary

data used for this study is questionnaire.

SECONDARY DATA:

It refers to the information or facts already collected either published or

unpublished. It is used for collecting historical data. The tools used to collect the required

secondary data are made through Journals, Magazines, and Internet and Text books.

3.2 RESEARCH INSTRUMENTS:

Research instrument means the instrument used for gathering the data information or

responses. The data collection tool used for this study was questionnaire, with the structured

and undisguised form, to get the necessary information from the respondents.

3.3 PILOT SURVEY:

Before the final questionnaire is ready it needs to be tested under field condition,

initially a pilot survey of 10 respondents was done and based on their responses suitable

changes were made in the questionnaire. The final questionnaire is shown in the appendices.

3.4 SAMPLE UNIT:

General public who have invested in mutual fund schemes are taken for this project.

People in different profession and of different educational qualification are taken for study.

3.5 SAMPLING TECHNIQUE:

In non-probability sampling, population elements are selected on the basis of their

availability (e.g., because they volunteered) or because of the researcher’s personal judgment

that they are representative. The consequence is that an unknown portion of the population is

excluded (e.g., those who did not volunteer). One of the most common types of non-

probability sample is called a convenience sample – not because such samples are necessarily

easy to recruit, but because the research uses whatever individuals are available rather than

selecting from the entire population. Because some members of the population have no

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chance of being sampled, the extent to which a convenience sample – regardless of its size –

actually represents the entire population cannot be known.

A convenience sample is a sample where the samples are selected, in part or in whole,

at the convenience of the researcher. The researcher makes no attempt, or only a limited

attempt, to insure that this sample in an accurate representation of some larger group or

population. A convenience sample chooses the individuals that are easiest to reach or

sampling that is done easy. Convenience sampling does not represent the entire population.

3.6 SAMPLE SIZE:

A total sample of 50 respondents where taken for the study titled “To find out the

perceptual mapping for mutual fund schemes by the investors”.

3.7 PLACE OF STUDY:

The sample area was restricted to Chennai city and semi urban area. People who are

willing to take part in the study Chennai circle and semi urban area was taken for study.

3.8 PERIOD OF THE STUDY:

The period of study was limited to 15 days.

3.9 DATA ANALYSIS:

The data after collection has to be processed and analyzed in accordance with the

outline laid down for the purpose at the time of developing the research plan. This is essential

for the scientific study and for ensuring that we have all the relevant data. Processing implies

editing, Coding, classification and tabulation of collected data so that they acquiescent to

analysis. The data collected was analyzed with respect to objective of study using SPSS,

Marketing Research Software.

The term analysis refers to the computation of certain measures along with search for

patterns of relationships that exits among data groups. Analysis of data in a general way

involves a number of closely related operations that are performed with the purpose of

summarizing the collected data and organizing them in such a manner that they answer the

research questions.

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3.10 STATISTICAL TOOLS:

The statistical tools used for the study are:

Multidimensional Scaling (MDS)

Chi-square Test

One way ANOVA

MULTIDIMENSIONAL SCALING 

Multidimensional scaling attempts to find the structure in a set of distance measures

between objects or cases. This task is accomplished by assigning observations to specific

locations in a conceptual space (usually two- or three-dimensional) such that the distances

between points in the space match the given dissimilarities as closely as possible. In many

cases, the dimensions of this conceptual space can be interpreted and used to further

understand your data.

CHI-SQUARE TEST

Chi-square test is a testing tool used for testing hypothesis. Chi-square test is a non-

parametric test in which no rigid assumptions are necessary about the population. In this

research chi-square test is used as a test of independence to explain whether two attributes are

associated or not without indicating strength or direction of relationship. When the SPSS

package is used for chi-square test, Pearson chi-square, likelihood-ratio chi-square, and

linear-by-linear association chi-square are displayed with degrees of freedom and

significance value. Fisher's exact test and Yates' corrected chi-square are computed for 2x2

tables. Here, significance value means level of significance of particular chi-square value for

those degrees of freedom. If the level of significance is less than 0.05 then the particular null

hypothesis will be rejected and the alternate hypothesis can be stated that there exists a

significant association between those two attributes.

Definition of chi-square:

Chi-square = (O-E) 2 / E

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Where O and E denotes the observed and expected frequencies, respectively. Inspection of

definition shows that Chi Square is a descriptive measure of the magnitude of the

discrepancies between the observed and expected frequencies. The larger these discrepancies

the larger Chi Square will tend to be. If no discrepancies exits and the observed and expected

frequencies are the same Chi Square will be zero.

ONE WAY ANOVA

Analysis of variance is a test of homogeneity of mean. The analysis of variance is a

method, which separates the variation ascribable to one set of causes from the variation

ascribable to other set. It is a method of splitting the total variation of a data into constituent

parts, which measures different sources of variation.

The total variation is split into the following two components

1. Variation within the sub groups of samples.

2. Variation between the sub groups of samples.

F-statistic= Variation between the samples/Variation within the samples.

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CHAPTER 4

ANALYSIS AND INTERPRETATION

4.1 Profile of the Respondents

Demographic variables are factors which describe the characteristics of the

population. The demographic characteristics considered for the study are age, gender,

education, occupation, monthly income, number of persons in the family and place of

residence.

Table No. 4.1.1: Gender of the Respondents

Gender Frequency Percentage

Male 40 80.0

Female 10 20.0

Total 50 100.0

The above table shows that around 80.0 percent are male respondents and remaining

20.0 percent are female respondents.

Figure No. 4.1.1: Gender of the Respondents

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Hence it is inferred that the majority respondents are male.

Table no: 4.1.2 - Age of the respondents

Age of the respondents Frequency Percentage

less than 25 2 4.0

26 – 35 16 32.0

36 – 45 26 52.5

46 and above 6 12.0

Total 50 100.0

The above table shows that around 12.0% of the respondents are in the age category

of 46 and above, 52.5 % belonging to the age group of 36 – 45 years, 32.0% and 4.0%

respectively for the age groups between 26 – 35 years and less than 25 years.

Figure No. 4.1.2- Age of the respondents

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Hence it could be studied that the majority respondents fall under the upper middle-

age group.

Table no: 4.1.3 - Education level of the respondents

Education level of the respondents Frequency Percentage

High School 5 10.0

Bachelor’s Degree 16 32.0

Master’s Degree 18 36.0

Doctorate Degree 11 22.0

Total 50 100.0

The above table shows that around 32.0 percent of the respondents are graduates, 10.0

percent of High School, 36.0 percent of Master’s Degree, 22.0 percent of Doctorate Degree.

Figure No. 4.1.3 - Education level of the respondents

Hence it is realized that the educational level of the respondents is pretty much higher

on standards.

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Table no: 4.1.4 - Profession of the respondents

Profession of the respondents Frequency Percentage

Professional 8 16.0

Govt. Employee 12 24.0

Private Employee 14 28.0

Self Employee 15 30.0

Others 1 2.0

Total 50 100.0

From the above table it can be inferred that around 24.0 percent of the respondents are

Government employee, 28.0 percent of Private employee, 30.0 percent of Self employee 16.0

percent of Professional and 2.0 percent in others.

Figure No. 4.1.4 - Profession of the respondents

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Hence it is understood that respondents of different professions like private,

government employee, professional, self employed and others were considered.

Table no: 4.1.5 - Family income per annum

Family income per annum Frequency Percentage

<1,50,000 2 4.0

1,50,000 to 2,50,000 10 20.5

2,50,000 to 3,50,000 18 36.0

Above 3, 50,000 20 40.0

Total 50 100.0

From the above table it can be inferred that around 20.5 percent of the respondents are

in the income category of 1, 50,000 to 2, 50,000, 36.0 percent in 2,50,000 to 3,50,000

and40.0% in Above 3, 50,000 income category and 4.0 percent are less than 1,50,000 income

group.

Figure No. 4.1.5 - Family income per annum

Hence it is found that the majority of the respondents fall under the income level of

above3, 50,000 per annum.

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Table no: 4.1.6 - No. of person in the Family

No. of person in the Family Frequency Percentage

Single 2 4.0

Two 15 30.0

Three 23 46.0

More than three 10 20.0

Total 50 100.0

From the above table it can be inferred that around 46.0 percent of the respondents

have three persons in their family, 20.0 percent of the respondents have more than three

persons in their family, 30.0 percent of the respondent two persons in their family and only

4.0 percent of the respondents are single.

Table no: 4.2.1 - Preferred schemes of mutual funds

Schemes of mutual funds Frequency Percentage

Open-ended 14 28.0

Closed- ended 13 26.0

Growth fund 10 20.0

Regular income fund 6 12.0

Liquid fund 4 8.0

Mid-cap fund 1 2.0

Large-cap fund 1 2.0

Sectoral fund 1 2.0

Total 50 100.0

From the above table it can be inferred that around 28.0 percent of the respondents are

using Open-ended, 26.0 percent of the respondents are using Closed-ended, 12.0 percent of

the respondents are using Regular income fund, 8.0 percent of the respondents are using

Liquid fund, 20.0 percent of the respondents are using Growth fund, 2.0 percent of the

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respondents are using Mid-cap fund, 2.0 percent of the respondents are using Large-cap fund

and 2.0 percent of the respondents are using Sectoral fund.

Figure No. 4.2.1 - Preferred schemes of mutual funds

Hence it is found that the majority of the respondents are using Open-ended funds.

4.1.1.1 Association between mutual fund schemes and demographic variables

The influence of demographic variables on mutual fund schemes is analyzed using

chi-square test.

H0: There is no significant relationship between demographic variables and the mutual

fund schemes preferred by the respondents.

H1: There is a significant relationship between demographic variables and the mutual fund

schemes preferred by the respondents.

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Table no: 4.2.2

Mutual fund schemes preferred by the respondents and

Demographic variables

S.No VariableChi-Square

value

Degree of

Freedom

Significance

level

1 Gender 8.040 7 0.329

2 Age group of respondents 25.301 21 0.234

3 Education level of respondents 23.460 21 0.320

4 Profession of respondents 70.193 28 0.000

5 Family income per month 21.133 21 0.451

6 No. of person in the Family 19.721 21 0.539

7 Place of residence 9.153 14 0.821

The Chi-square analysis shows a low significance value (typically below 0.05) and it

indicates that the Null Hypothesis is accepted which means demographic variables do not

have association with the mutual fund schemes preferred by the respondents.

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4.2 Perceptual mapping

Useful for providing highly intuitive representations in order to position schemes on

dimensions critical to consumer perceptions in that visual space, a variety of simple to

complex statistical methodologies can be used to create them. Some of the latter include

multi-dimensional scaling, factor or cluster analytical methods, and conjoint analysis. Usually

these techniques result in brands being mapped on 2 to 3 dimensions.

Figure no: 4.7.1 - Return of the scheme

From the above figure it is deducted that Open ended and Sectoral carry similarity in

their delivery of the product. Similarly Income fund and Mid-cap fund have resemblance in

their return of schemes.

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Figure no: 4.7.2 - Risk of the scheme

From the above figure it is understood that respondent’s perception towards the risk

level of Income fund and Mid-cap fund are the same. Similarly the risk level of Large-cap

and Sectoral fund are also perceived to be the same. It is also clear that Closed ended and

Growth fund does not share the same value in the minds of the respondents.

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Figure no: 4.7.3 - Liquidity of the scheme

From the above figure it is inferred that Mid-cap fund and Large-cap fund are similar

in liquidity, Open ended and Closed ended are similar in liquidity, Sectoral fund and Growth

fund are similar in liquidity of their schemes.

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Figure no: 4.7.4 - Safety of the scheme

From the above figure it is inferred that based on the features, Growth fund and

Income fund falls in the same category, Large-cap and Liquid fund falls in another category.

Closed ended fund, Open ended and Mid-cap fund are same in the features.

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Figure no: 4.7.5 – New fund offering of the scheme

From the above figure it is inferred that based on the New fund offering of the

scheme, Large-cap fund and Closed-ended fund fall in same category, Income fund, Sectoral

fund and Liquid fund fall in another category Mid-cap fund and Open ended fund fall in other

category.

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Figure no: 4.7.6 – Expectations met by the scheme

From the above figure it is inferred that Growth fund, Mid-cap fund and Liquid fund

carry similarity in meeting the expectations. Income fund, Open ended and Closed ended

fund are same in their meeting of expectations whereas Sectoral fund and Large-cap fund

carry same.

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CHAPTER 5

FINDINGS AND SUGGESTION

5.1 Findings

1. It was found that most of the respondents are upper middle-aged male who are mostly

graduates and their annual family income is in the range of Rs. 2, 50, 000 – 3, 50, 000.

2. It was found that majority of the respondents are government and private employees from

city and most of them have more than 3 persons in their family.

3. It was found that most of the respondent prefer Open-ended followed by Closed-ended,

Growth fund, Regular income fund, Liquid fund, Mid-cap fund, Large-cap fund, and

Sectoral fund.

4. It was found that demographic variables like gender, age, family income, educational

qualification, profession, number of persons in the family and place of residence have no

association with the scheme of mutual funds preferred by the respondents.

5. It is realized that the educational level of the respondents is pretty much higher on

standards.

6. It was found that majority of the respondents never switch their brand.

7. It was found that the bulk of the respondents use one scheme.

8. It was found that most of the respondent considered the return of the scheme before

making the decision and risk of the scheme of mutual fund preferred by the respondents

have association with reason to invest in mutual funds.

9. It was found that most of the respondents are influenced by Auditors and investment

advisors while making investment decisions and schemes of mutual funds preferred by

the respondents have association with source of influence.

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10. It was found that most of the respondents feels that open ended fund have good return and

they will recommend other to invest in open ended mutual funds.

11. It was found that return is given first priority by the respondent followed by risk, liquidity

and availability.

12. It was found that Open ended and Sectoral carry similarity in their delivery of the

product. Similarly Income fund and Mid-cap fund have resemblance in their return of

schemes.

13. It was found that respondent’s perception towards the risk level of Income fund and Mid-

cap fund are the same. Similarly the risk level of Large-cap and Sectoral fund are also

perceived to be the same. It is also clear that Closed ended and Growth fund does not

share the same value in the minds of the respondents.

14. It was found that that Mid-cap fund and Large-cap fund are similar in liquidity, Open

ended and Closed ended are similar in liquidity, Sectoral fund and Growth fund are

similar in liquidity of their schemes.

15. It was found that based on the features, Growth fund and Income fund falls in the same

category, Large-cap and Liquid fund falls in another category. Closed ended fund, Open

ended and Mid-cap fund are same in the features.

16. It is inferred that based on the New fund offering of the scheme, Large-cap fund and

Closed-ended fund fall in same category, Income fund, Sectoral fund and Liquid fund fall

in another category Mid-cap fund and Open ended fund fall in other category.

17. It is inferred that Growth fund, Mid-cap fund and Liquid fund carry similarity in meeting

the expectations. Income fund, Open ended and Closed ended fund are same in their

meeting of expectations whereas Sectoral fund and Large-cap fund carry same.

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Suggestions

In the end of this study it was found some mismatching. The Large-cap fund is

targeted only at the elite and not at the low-income group. In contrast, the Income fund is

promoted on income grounds and the high income group doesn't favour it. The liquidity for

Large cap fund doesn't appeal to the common man. The mindset of the high class people is

about Large cap fund and that of income fund is only for the layman. That sort of image

must be taken out. Also the open ended fund is preferred more than other schemes, which

may be due to lack of awareness of the mutual fund investment schemes, which should be

created.

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5.2 Conclusion

The ultimate success of any project work rests on the realization of the fulfillment of

objectives for which it was stated. Based on the research survey conducted and from the

various articles entreated from text books, journals, internet, on the topic of study of

Perceptual Mapping, it is very clear that, it is a key area which require more focus and

attention. This study revealed the customers perception towards various schemes of mutual

funds. The study also offered some constructive suggestions for improving the investment

plans.

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BIBILOGRAPHY

Reference:

1. Donald R. Cooper and Pamela S. Schindler (2001), Business Research Methods, eighth Edition, Tata McGraw Hill Publishers.

2. C R kothari, Research Methodology - Methods and Techniques (2006), 23rd revised Edition, New Delhi.

Websites:

1. www.researchandmarkets.com

2. www.proquest.umi.com

3. www.wikipedia.org/wiki/multivariate

4. www.wikipedia.org/wiki/multidimensional_ scaling

5. www.managementparadise.com

6. www.Quickmba.com

7. www.asiamarketresearch.com/glossary/brand-mapping.htm

8. www.blackcoffee.com/brand-mapping.html

9. www.mcorpconsulting.com/services/tools/brandMapping.asp

10. www.mm4xl.com/software/tools/brand.php

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PERCEPTION MAPPING FOR MUTUAL FUND INVESTMENT

Name: Megalaa.J College: St.Joseph’s College Of Engineering.

Purpose: Project. Course: MBA

QUESTIONNAIRE

Personal particulars of the respondent (Questions 1 – 7)

(Please select the appropriate category)

1. Male / Female

Male Female

2. Current Age(Years)

Less than 25 26 – 35 36-45 46- Above

3. Educational Background

High School Bachelor’s Degree Master’s Degree

Doctorate Degree Any other (Please Specify) ________________

4. Occupation

Professional Govt. Employee Private Employee

Self Employee Any other (Please Specify) ________________

5. Family Income (Per Annum in Rupees)

<1,50,000 1,50,000 to 2,50,000 2,50,000 to 3,50,000

Above 3, 50,000

6. No. of persons in your family

Single Two Three More than three

7. Place of Residence

Semi-urban City Town Rural

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8. Which mutual fund scheme have you used?

Open-ended Close-ended Growth fund Regular Income fund

Liquid fund Mid- Cap Long-Cap Sectoral fund

9. How long have you been investing in mutual funds?

Less than 6 Months 6 months – 2 years 2 – 3 years

3 – 5 years More than 5 years

10. Have you ever changed your mutual fund scheme?

Frequently Occasionally Rarely Never

11. Why did you invest in mutual fund?

Return Safety Liquidity Regular Income Risk

12. Who influenced you to invest in mutual funds?

Friends & relatives Broker & agents Investment advisor

Media Auditors

13. How many mutual fund schemes do you use for investment?

One Two Three

14. Will you recommend others to invest in mutual fund schemes?

Yes No Don’t know

(Please Mark ( ) the appropriate category)15. For each factor please tell us whether the factors was strongly influential, some

what influential or not at all influential

FACTOR Strongly influential

Some what influential

Not at all influential

LiquidityRegular Income fundSafetyReturn

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16. What is your opinion about the return of the scheme?

Scheme Very Desirable Desirable Undecided Undesirable Very Undesirable

Open-endedClose-endedGrowth fund Income fundLiquidityMid-CapLarge-CapSectoral fund

17. What is your opinion when it comes to the risk of the scheme?

Scheme Very High High Neutral Low Very Low Open-endedClose-endedGrowth fundIncome fundLiquid fundMid-CapLarge-CapSectoral fund

18. What is your level of satisfaction when it comes to the liquidity of the schemes?

Scheme Very Good Good Undecided Bad Very BadOpen-endedClose-endedGrowth fund Income fundLiquid fundMid-CapLarge-CapSectoral fund

19. How likely have you recommend mutual fund to others?

Always Not at all

5- Always, 4 – Often, 0 – Can’t say, 2 – Never, 1 – Not at all

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5 4 0 2 1

20. When it comes to safety the scheme has, what is your level of satisfaction?

Schemes Best Good Undecided Bad Very BadOpen-endedClose-endedGrowth fund Income fundLiquid fundMid-CapLong-Cap

21. What is your level of satisfaction when it comes to the frequency NFO of the schemes?

Scheme Highly Satisfied

Satisfied Undecided DissatisfiedHighly Dissatisfied

Open-endedClose-endedGrowth fundIncome fundLiquid fundMid-CapLarge-CapSectoral fund

22. With regard to Meeting your needs and expectations fulfillment?

SchemeNo expectation are met

Met few expectation

Met most expectation

Met all expectation

Exceeded expectation

Open-endedClose-endedGrowth fundIncome fundLiquid fundMid-CapLarge-CapSectoral fund

THANK YOU

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