VALIDITY OF CAPITAL ASSET PRICING MODEL IN

RELATION TO INDIAN STOCK MARKET

A dissertation submitted in partial fulfilment of the

requirements for the award of the degree of

MASTER OF BUSINESS ADMINISTRATION

By

DIBYA NANDAN MISHRA

Register No 1220214

Under the Guidance of

PROF KRISHNA M C

Institute of Management

Christ University, Bangalore

March 2014

ii

DECLARATION

I, Dibya Nandan Mishra, a bona fide student of Christ University Institute of

Management (CUIM), hereby declare that the dissertation entitled Validity of Capital

Asset Pricing Model In Relation To Indian Stock Market has been undertaken for the

award of the degree of Master of Business Administration. I have completed this study

under the guidance of Mr Krishna M C, Associate Professor (Finance), Department

of Finance, Institute of Management, Christ University, Bangalore.

I also declare that this dissertation has not been submitted for award of any

degree, diploma, associateship or fellowship or any other title in this University or any

other University.

Place: Bangalore

Date: Dibya Nandan Mishra

Register No 1220214

iii

CERTIFICATE

This is to certify that the dissertation submitted by Mr. Dibya Nandan Mishra

on the title Validity of Capital Asset Pricing Model In Relation To Indian Stock

Market is a record of research work done by him during the academic year 2013-14

under my guidance and supervision in partial fulfillment of Master of Business

Administration. This dissertation work has not been submitted for award of any degree,

diploma, associateship or fellowship or any other title in this University or any other

University.

Place: Bangalore

Date: Prof Krishna M C

iv

ACKNOWLEDGEMENTS

I am indebted to many people who helped me accomplish this dissertation

successfully.

First, I thank the vice chancellor Dr Fr Thomas C Matthew of Christ University

for giving me the opportunity to do my research.

I thank Prof Ghadially Zoher, Associate Dean, Fr Thomas T V, Director, and Prof

T S Ramachandran, Head Finance of Christ University Institute of Management for

their kind support.

I thank Prof Krishna M C for his support and guidance during the course of my

research. I remember him with much gratitude for his patience and motivation, but for

which I could not have submitted this work.

I thank my parents for their blessings and constant support, without which this

dissertation would not have seen the light day.

Dibya Nandan Mishra

Register No 1220214

v

ABSTRACT

Capital Asset Pricing Model has always been in debate for its validity. Thus a lot

of research work has been done over it to prove the validity of the same. Arbitrage

theories and many multi-factor models have come to picture in contrast to CAPM model,

but this model is still used for its simplicity and proved valid in many scenarios.

The objective is to see if CAPM model is valid in Indian stock market. As of now

very few researches are done in the Indian market to prove its validity, of which they are

for very short period of around 5 years or there is no proved model taken to prove the

validity. Fama and MacBeths Unconditional Traditional Approach is used in this

research to prove the validity of CAPM model over a period of 15 years from 1st

January,1999 to 31st December,2013 by taking the daily risk premiums of CNX NIFTY

50 stocks and creating an portfolios from that. The research checks the linearity and the

beta-return relationship to prove the CAPM model over the years.

The findings from the research work done are that the CAPM model proved to be

valid from the period after 2010 and not before the previous year of data/calculations.

This research would have given a better validation to the model if the whole of

NSE listed stocks were taken into consideration and not the Nifty listed stocks. A multi-

variable approach would have given a more powerful dimension to the result.

This dissertation can help to create portfolios and to know the volatility of stocks

in Indian stock market.

This dissertation can help the investors to choose a better model for capital asset

pricing.

Keywords: CAPM model, CNX NIFTY 50, Fama and MacBeths, Unconditional

approach, risk-return, beta

vi

TABLE OF CONTENTS

Declaration ii

Certificate iii

Acknowledgement iv

Executive Summary v

Table of Contents vi

List of Tables ix

CHAPTER I

INTRODUCTION

1.1 BACKGROUND OF THE STUDY 1

1.2 NEED AND RATIONALE OF THE STUDY 2

1.3 PURPOSE OF THE STUDY 2

1.4 SIGNIFICANCE OF THE STUDY 3

1.5 RESUME OF SUCCEEDING CHAPTERS 3

CHAPTER II

REVIEW OF LITERATURE

2.1 INTRODUCTION 4

2.2 HOW REVIEW HAS BEEN CONDUCTED 4

2.3 STUDIES CONDUCTED ABROAD 4

2.4 STUDIES CONDUCTED IN INDIA 9

2.5 CONCLUSION 9

vii

CHAPTER III

RESEARCH DESIGN AND METHODOLOGY

3.1 INTRODUCTION 10

3.2 STATEMENT OF THE PROBLEM 10

3.3 VARIABLES UNDER INVESTIGATION AND EXPLANATION 10

3.4 OBJECTIVES OF THE STUDY 11

3.5 HYPOTHESES 11

3.6 POPULATION AND SAMPLE OF THE STUDY 11

3.7 SAMPLING TECHNIQUE 11

3.8 TOOLS ADOPTED FOR THE STUDY 12

3.9 LIMITATIONS 12

3.10 CONCLUSION 12

CHAPTER IV

INDUSTRY OVERVIEW

4.1 INTRODUCTION 13

4.2 METHOD OF COMPUTATION AND SELECTION

4.2.1 BASE DATE AND VALUE 15

4.2.2 CRITERIA FOR SELECTION OF CONSTITUENT

STOCKS 15

4.2.3 INDEX MAINTENANCE 17

4.2.4 HEDGING EFFECTIVENESS 17

4.2.5 TRADING IN NIFTY 17

4.2.6 TOTAL RETURN INDEX 17

viii

CHAPTER V

DATA ANALYSIS AND INTERPRETATIONS

5.1 INTRODUCTION 19

5.2 QUANTITATIVE ANALYSIS 19

5.3 TESTING OF HYPOTHESES 22

CHAPTER VI

FINDINGS, CONCLUSION AND SUGGESTIONS

6.1 FINDINGS 24

6.2 CONCLUSION 24

6.3 SUGGESTIONS 24

6.4 SUGGESTIONS FOR FURTHER RESEARCH 25

BIBLIOGRAPHY

APPENDICES

ix

LIST OF TABLES

Sl. No. Title Page No.

Table 5.1 Distribution of Analysis Period and Number of

Qualifying Stocks. 15

Table 5.2 Number of Stocks in Portfolios 16

Table 5.3 Summary of the Result 18

CHAPTER i

Introduction

1.1 BACKGROUND OF THE STUDY

Harry Markowitz (1952) developed an approach to help investors

achieve an optimal portfolio, thus making a historical contribution to financial

mathematics with his classic article Portfolio Selection. He incorporated the

quantification of risk in the portfolio choice problem. He developed a

framework where investors who like wealth and dislike risk would hold mean-

variance efficient portfolios.

William Sharpe (1964), Lintner (1965), Mossin (1966) and Fisher

(1972) soon followed up developing a model to price capital assets. Sharpe

agreed on Lintners and others findings, this equation they derived has later

been named the Capital Asset Pricing Model (CAPM). This model relates

expected return to a measure of risk for an efficient portfolio or an individual

security. This measure, now known as beta, used the theoretical result that

diversification allows investors to escape the company specific risk. This

relationship was useful in two ways, as a benchmark and as an approximate

guess to the return that is expected in future. Though CAPMs empirical

record is poor and many multifactor models have been formed as its

alternative, it is still widely used in both academics and in real-world

applications. This is because the major attraction of the CAPM is its economic

intuition and ease of use.

CAPM model was first to interpret the risk of investment in a project

and to estimates its cost of capital. It says about the rate of return of the

project. CAPM has still been prominent for over 30 years and the basis of

modern portfolio theory till it accumulated increase in researches against its

validity.

Though many researches like that of Black, Jensen and Scholes (1972),

Fama McBeth (1973), Ball et al. (1976), Johnson (1990), Fama and French

(1989) showed the linear relationship as stated by the CAPM model, but after

further researches Roll (1977), Fama and French (1992, 1994) themselves

found out it was not valid under a certain period length in the stock returns and

its demerits due to its restriction to historical data only. CAPM model has been

used in other forms to test and develop capital markets in U.S.A., Europe,

2

Australia and capital markets of developing nations. In addition to find

the relation between risk and return, it is also used to calculate the cost of

equity of a firm and thus helping to find the cost of capital and capital

structure of the company.

1.2 NEED AND RATIONALE OF THE STUDY

The rationale of the validity of CAPM model is to know if this model

is valid in the Indian Stock Market over a period of years taking into

consideration both the condition of uptrend and downtrend in the market

returns.

This will explain and support the various research done to check the

validity of the model in different stock markets of different countries, and to

check its validity in Indian context.

This study will tell how relevant it is to use the CAPM model in

current Indian market or do we need a better multifactor models for a better

risk return relation in order to help investors to create a better portfolio which

is risk adverse.

1.3 PURPOSE OF THE STUDY

CAPM model is the most popular as compared to Arbitrage Pricing

Theory (APT) or any other multivariate models formed seeing the demerits of

the model. Past few years have shown that financial experts and economists

have tried to bring out a number of models and tools in order to create the best

investment management/portfolio to outperform the market. The study is to

verify if the model justifies the wide use in the current market scenario.

This study will check if CAPM model is valid in Indian Stock Market

taking into consideration the stocks listed in CNX NIFTY 50 and Fama and

MacBeth (1973) model will be used to check the validity.

3

1.4 LIMITATIONS OF THE STUDY

The Limitations of the studies are:

1. A better work could have been done if the time availability for this

research would have been more.

2. Availability of the data for all the companies was another limitation to this

research.

3. A more researches done in the Indian context would have given a more

deep idea and on the horizon of the study.

1.5 RESUME OF SUCCEEDING CHAPTERS

The dissertation will follow up with Chapter II covering the review of

literature of the relevant research papers done on the similar topic which will

act as a support to my research study. Papers are taken from both abroad and

Indian based.

Chapter III will give the structure of the research methodology and all

the details about the sample data, variables used and the statistical tools used.

It gives the objective and hypothesis to be proved.

Chapter IV will give the overall industry overview of the Indian stock

market and the history of NSE and how stocks enter into the CNX NIFTY 50

Index

Chapter V will give the analysis and interpretation of the research done

and thus concludes the findings of the result.

Chapter VI will speak about the recommendations and suggestions and

gives the conclusion to the study and research done.

CHAPTER II

Review of literature

4

2.1 INTRODUCTION

This chapter tells about the researches done on validating the CAPM

model, which will act as support for my dissertation topic and will also tell

about the different aspects, outcomes, results, findings and conclusion made

over past few years in different geographical regions including India. We will

get to know the various methods used, the way the research made and their

relevance and importance in current world. This will help to make us know the

historical evidence and drawbacks of the studies previously conducted. The

main sub-sections which will speak about the studies conducted abroad

(section 2.3), studies conducted in India (section 2.4).

2.2 HOW REVIEW HAS BEEN CONDUCTED

Journals, Research Articles, Master Theses have been reviewed both of

Indian and Abroad in order to find clearer evidence to support the dissertation

and to make a better approach by limiting the drawbacks of previously

conducted research on the topic of validity of CAPM model in different

capital/stock markets.

2.3 STUDIES CONDUCTED ABROAD

Dzaja and Aljinovic (2013), in their research paper titled Testing

CAPM model on the emerging markets of the central and South-eastern

Europe, examines is the CAPM model is adequate for capital asset valuation

on the central and South-eastern European market. Monthly stock returns of

nine countries in period of January 2006 to December 2010 was taken, cross

sectional analysis was done between the risk and return of each countries

which shows that there are no adequate reason to make CAPM a good model

to use it for capital valuation in the Europe Market.

Bilgin and Basti (2011), in their research paper titled A Test of the

validity of Capital Asset Pricng Model in Istanbul Stock Exchange, tests

the validity of CAPM model in Istanbul Stock Exchange taking the

unconditional approach of Fama and MacBeth (1973). A period of five years

5

were taken which were further divided into three twenty-month sub-periods

and unconditional testing Fama and MacBeth approach was applied to it. The

result supported the Fama and MacBeth research and other previous test on the

same market thus no strong relationship between risk and returns were found.

Wakyiku (2010), in his paper titled Testing the Capital Asset

Pricing Model on the Uganda Stock Exchange, examines the validity of

CAPM model on the Uganda Stock Market, data taken from USE stock

exchange which contains 11 companies for period 1st March 2007 to 10th

November 2009. This research uses the Black, Jensen and Scholes (1972)

CAPM model to examine its validity. The research uses monthly stock returns

rather than a portfolio as there are only 10 stocks used out of 11 listed. This is

one of the disadvantage of this research. The final result shows that the beta

co-efficient does not offer any relevant explanation to the relationship between

the risk and return.

Jarlee (2007), in his bachelor thesis titled A test of the Capital Asset

Pricing Model: Studying Stocks on the Stockholm Stock Exchange, test if

CAPM model holds true in Stockholm Stock Exchange, in brief he wanted to

prove if higher beta yields high, if the intercept of slope of Security Market

Line (SML) equals average risk premium and if there is linearity between risk

and return. Data from January 2001 to December 2006 was taken and Black,

Jensen and Scholes (1972) time-series and Fama and MacBeth (1973) cross-

sectional approaches were used. The result showed that CAPM is not

completely valid in the market. There were no evidence if higher beta has

higher returns and the SML slope was negative. Though a linear relationship

between risk and return was established.

Paavola (2007), in her masters thesis titled Empirical Tests of Asset

Pricing Models in Finnish Stock Market, in this study she investigates the

relationship between different risk and return portfolios from year 1987 to

2004. Not only CAPM but APT and CCAPM model is used in this research.

Gursoy and Rejepova (2007), in their paper Test of Capital Asset

Pricing Model in Turkey, attempts to test the validity of CAPM model in

Turkey by regressing the weekly risk premium against the systematic risk

6

(beta) of the 20 portfolios formed each having 10 stocks each over the period

of 1995-2004. The data consisted of ISE 100 index and they used both Fama

and MacBeth (1973) and Pettengil et. al. (1995) approaches for their research.

They created overlapping year in each two consecutive sub-periods to reduce

volatility variance. Their research supported that the systematic risk (beta) is

an important variable to determine the portfolio return in Turkey. It also

supported the traditional view of higher beta gave better returns in up-trends

and vice versa.

Rahaman and Baten (2006), in their research journal titled An

Emperical Testing of Capital Asset Pricing Model in Bangladesh, aims to

explore if CAPM is a good asset pricing indicator in Bangladesh capital

market. They used Fama-French (1992) method to validate their research by

taking five variables stock market return, book to market value, market

capitalization and sales. They took data over a period of 1999 2003. They

conducted a five yearly average cross-section and polled multiple regression

analysis. The result strongly supported the relationship among all the variables

also proving that beta is not the lone factor to determine the return of a

portfolio.

Theriou, Aggelidis and Spiridis (2002), in their research titled

Empirical testing of Capital Asset Pricing Model, studies the validity of

CAPM model in the Athens Stock Exchange (ASE) using Black, Jensen and

Scholes, i.e. the BJS approach. The data was taken over a period of 14 years

from July 1987 to June 2001. It was divided into two sections one of

investigation period and other as estimation period, former had a five year

period and later a one year period. Cross sectional and time series test was

done with the conclusion formed that CAPM was not valid in Athens Stock

Market.

Pettengill, Sundaram and Mathur (1995), this study is the one of

which attempted to overcome one important problem encountered in testing

CAPM. This problem is the negative market and portfolio risk premiums

observed in many observation periods such as weeks or months. Although this

does not create any problem in estimating beta coefficients, it does so by

7

weakening the ex-post relationship between betas and risk premiums. If

negative data points are plotted on the same scatter diagram with positive data

points, and if neither group is only a negligible fraction of total number of

observations, the slope of the regression line will most likely be very close to

zero implying that there is no meaningful relationship between betas and risk

premiums as predicted by security market line. On the other hand, when

positive and negative data points are plotted on two different scatter diagrams,

the two regression lines, with positive and negative slopes will both be

consistent with the prediction of security market line. This is why Pettengil et.

al. (1995), after observing 280 negative market risk premiums out of 660 data

points, divided the data set into positive and negative risk premium subsets,

called up-market and down market respectively, They used a modified

version of Fama and Macbeths three-step method, but analysed positive and

negative market risk premiums separately. The 15-year sample period was

divided into three 5-year sub periods: portfolio formation period, portfolio

beta estimation period, and testing peroid. Securities were equally divided into

20 portfolios according to the ranked beta coefficients calculated for the first

sub period. Beta coefficients of these portfolios were recalculated using

second period data. Actual returns of portfolios calculated in the third period

were regressed against the portfolio betas calculated in the second period. But

the third step was modified taking into consideration up-market and down-

market phenomena. The empirical results of cross sectional regression tests

provided strong support for a systematic but conditional relationship between

beta and realized risk premiums. The results of traditional test showed a

significant relationship between beta and returns for the whole sample period,

but not for the sub periods. The results of conditional test, on the other hand,

showed significant positive relationship between beta and risk premiums for

periods with positive market risk premiums, and an inverse relationship for

periods with negative market risk premiums.

Famas contribution is crowned by his work with his colleague French

with whom he devised the three-factor model that extends the single market

premium factor of traditional asset pricing theories. In their work, they show

8

that sensitivity to size and value provides an adequate model for share price

movements. The first factor is denoted as SMB (small minus big) which is the

difference between the returns on diversified portfolios of small capitalisation

stocks and a portfolio of large stocks constructed to be neutral with respect to

book equity to market equity (BE/ME). The second factor is HML (high

minus low) is the difference between the returns on diversified portfolios of

high and low book equity to market equity shares constructed irrespective to

size. The betas are evidently slopes in the regression.

Modigliani, Pogue and Solnik (1973), in their research titled A Test

of the Capital Asset Pricing Model on European Stock Markets, uses daily

price and dividend data for 234 stocks of eight major European countries. The

period covered was from March 1966 to March 1971. The research supported

to the hypothesis taken, i.e. systematic risk is an important factor in the pricing

of European capital market.

Fama and MacBeth (1973), they included all common stocks traded

in NYSE from 1926 to 1968 in their analysis. They used a method called

three-step approach. They divided total period (1926-1968) into 9 overlapping

analysis periods. Each analysis period, in turn, was divided into three sub-

periods: a four-year portfolio formation period, a five year beta estimation

period and a 5-year testing period. 20 portfolios were formed on the basis of

ranked betas of individual securities during the first sub-period. Then the betas

of the portfolios formed were re-estimated using the subsequent periods data.

Portfolio returns during the testing period were regressed against the betas

calculated in estimation period. The test results showed a positive relationship

between period t-1 betas and period t returns on average. Black, F., M. Jensen,

and M. Scholes (1972) and Fama, E. F. and J.D.MacBeth

(1973) studies were later called traditional studies.

Black., Jensen, and Scholes (1972), their study covered the period of

1931-65 and used all NYSE stocks. They estimated beta coefficients for the

five-year periods based on monthly data, and ranked them from highest to

lowest in order to form 10 portfolios. They used 1 month T-Bill rate as risk-

free return. Although they found time-series analysis more powerful, they used

9

cross-sectional analysis as well to regress average returns against betas of

portfolios formed. The results they found were consistent with the predictions

of CAPM.

2.4 STUDIES CONDUCTED IN INDIA

Kant (2011), in his research journal Testing of Capital Asset Pricing

Model during an upward trend in the Indian Stock Market. It takes stocks

from BSE Sensex companies from 1st July 2007 to 31 December 2007,

consisting of 30 companies. Here the result shows that CAPM model is valid

in that period but the high risk high return and vice versa was not valid though.

Choudhary and Choudhary (2010), in their paper titled Testing

Capital Asset Pricing Model: Empirical Evidences from Indian Equity

Market, examines the CAPM for Indian Stock Market using monthly returns

from 278 companies of BSE 500 index from a period of January 1996 to

December 2009. The test is to check if there is any nonlinearity of relation of

beta and return. The result and findings did not support the basic hypothesis

that higher risk gives higher return nor did it gave intercept as zero or the

excess return equal to slope. Thus the period taken into consideration clearly

rejected the CAPM model.

2.5 CONCLUSION

We can clearly see that there has been many researches done in abroad

than in India. Seeing the result of validity testing of CAPM there has been

both positive and negative support to CAPM which is due to the time period

and geographical stock markets. So testing the validity in Indian Stock Market

and taking the recent period will provide us the reason if CAPM is valid in the

current market trends which has seen lots of regulations and deregulations in

the recent few years.

CHAPTER III

Research design and methodology

10

3.1 INTRODUCTION

This chapter will explain how the research is started by telling about

the secondary data taken, research methodology used, variables taken,

hypothesis, the design and the tools used to process these variables. Section

3.2 will speak about the problem statement, 3.3 will talk about the different

variables used, 3.4 will describe the objective, 3.5 will talk about the

hypothesis, 3.6 will talk about the range of data taken and its size, 3.7 will tell

about the sampling technique used, 3.8 tells about the tools to be used and will

then end with the limitations and conclusion in section 3.9 and 3.10

respectively.

3.2 STATEMENT OF THE PROBLEM

Capital Asset Pricing Model has always been used due to its simplicity

and ease of use. Though many multivariate models and techniques like

Arbitrage Pricing Technique (APT) has come out to picture in contradiction to

CAPM, CAPM is still the most preferred of all. CAPM has been proved valid

by many researches done over years, though there are equal number of

researches who proves CAPM wrong and not fit in many cases in different

time-periods and geographical capital markets. This study will check the

validity of CAPM model in the Indian Stock Exchange by taking data from

CNX Nifty 50 over a period of 15 years from 1st January, 1999 to 31st

December, 2013. Fama and MacBeth (1973) will be used as the approach to

prove the validity of CAPM model in Indian Stock Market.

3.3 VARIABLES UNDER INVESTIGATION AND

EXPLANATION

The dependent variables taken in the study:

1. Expected Return : This measures the return of each portfolio created

The independent Variables taken in the study:

1. Beta/Systematic Risk : This is the risk of each of the portfolio created

2. Risk-free rate: The RBI 91 T-bill rate is taken as proxy.

11

3.4 OBJECTIVES OF THE STUDY

The objective of the study are:

1. To study and understand the Capital Asset Pricing Model.

2. To study the validity of CAPM model in the Indian stock market.

3. To study the applicability of CAPM model and to describe risk return

relationship in Indian Stock Market.

4. To study the dependence of the systematic risk on the risk return.

3.5 HYPOTHESES

1. H01: There is a no positive relationship between expected return and

systematic risk, i.e. slope of CAPM equation is negative.

H11: There is a positive relationship between expected return and

systematic risk, i.e. slope of CAPM equation is positive.

2. H02: The relationship between expected return and risk is non-linear.

H12: The relationship between expected return and risk is linear.

3.6 POPULATION AND SAMPLE OF THE STUDY

The sample data is selected from CNX Nifty 50 companies on the

National Stock Exchange (NSE) of Indian Stock Market. This data is retrieved

from historical database from www.nseindia.com and www.rbi.org. CNX

Nifty 50 data is selected as it includes top corporates from which we can get

relevant resources. So the total sample size included 34 NSE 50 companies.

The period of data taken is for 15 years from 1st January, 1999 to 31st

December, 2013.

3.7 SAMPLING TECHNIQUE

The data were collected by looking at their data availability for

respective periods. As this data was collected in accordance to its availability

at hand, it is a convenience sampling technique.

12

3.8 TOOLS ADOPTED FOR THE STUDY

The statistical tools used in the study is Cross-sectional Linear

Regression analysis in unconditional approach taken for checking the validity.

3.9 LIMITATIONS OF THE STUDY

Only few companies were able to come to the sample because of the

limitations like:

1. Availability of daily closing prices.

2. Companies which were merged.

3. Companies which were listed in the late years of the study period.

3.10 CONCLUSION

So the data are secondary and statistical analysis will be done using

IBM SPSS program and basic excel functions for reporting and to conduct

different statistical test like regression and correlation to prove the hypothesis

of the study.

CHAPTER IV

Industry Overview

13

4.1 INTRODUCTION

The CNX nifty, conjointly known as the nifty 50 or just the nifty, is

National stock exchange of India's benchmark index for Indian equity market.

The CNX nifty is a well wide-ranging fifty index accounting for twenty two

sectors of the economy. Its used for a range of functions like benchmarking

fund portfolios, index based mostly derivatives and index funds. Nifty is

owned and managed by India Index Services and products Ltd. (IISL) that

could be a subsidiary of the NSE Strategic Investment Corporation limited. .

IISL is India's 1st specialised company targeted upon the index as a core

product. IISL encompasses a selling and contract with standard & Poor's

for co-branding equity indices. 'CNX' in its name stands for CRISIL NSE

Index.

CNX nifty has formed up as a largest single monetary product in India,

with a system comprising: exchange listed funds (onshore and offshore),

exchange-traded futures and options (at NSE in India and at SGX and CME

abroad), different index funds and over-the-counter derivatives (mostly

offshore).

The CNX nifty covers twenty two sectors of the Indian economy and

offers investment managers exposure to the Indian market in one portfolio.

throughout 2008-12, CNX nifty fifty Index share of NSE market capitalization

fell from sixty fifth to twenty ninth thanks to the rise of sectorial indices like

CNX Bank, CNX IT, CNX middle Cap, etc. The CNX nifty fifty Index

provides 29.70% weightage to monetary services, 0.73% weightage to

industrial producing and null weightage to agricultural sector.

The CNX nifty index is a free float market capitalization weighted

index. The index was at the start calculated on full market capitalization

methodology. From June 26, 2009, the computation was modified to free float

methodology. The bottom amount for the CNX nifty index is Gregorian

calendar month three, 1995 that marked the completion of one year of

operations of National Stock Exchital Market section. The bottom price of the

index has been set at a thousand, and a base capital of Rs 2.06 trillion. The

14

CNX nifty Index was developed by Ajay shah and Susan Thomas. The CNX

nifty presently consists of the subsequent fifty major Indian firms.

Post expiration of agreement between IISL and Standard and Poors

financial Service LLC on 31st January 2013, index is addressed as CNX nifty

Index. (Formerly, CNX nifty Index)

The CNX nifty Index represents regarding 68.99% of the free

float capitalisation of the stocks listed on NSE as on December 31,

2013.

The total listed price for the last six months ending December

2013 of all index constituents is close to 59.01% of the listed price of

all stocks on the NSE.

Impact price of the CNX Nifty for a portfolio size of Rs.50

lakhs is 0.06% for the month December 2013.

CNX Nifty is professionally maintained and is good for

derivatives mercantilism.

On the subsequent dates, the CNX Nifty index suffered major

single-day falls (of a hundred and fifty or additional points)

1. sixteen Aug. 2013 --- 234.45 Points (because of rupee

depreciation)

2. twenty seven Aug. 2013 --- 189.05 Points

3. 03 Sep Aug. 2013 --- 209.30 Points

4. In 1991, Indian capital kick-started the economic

reforms method owing in the main to the intense

balance of payments crisis it absolutely was facing.

5. 1997 Asian monetary Crisis - Investors deserted rising

Asian shares, together with an overheated Hong Kong

securities market. Crashes occur in Thailand, Indonesia,

South Korea, Philippines, et al, reaching a climax

within the Oct 27, 1997 mini-crash.

15

4.2 METHOD OF COMPUTATION AND SELECTION

CNX Nifty is computed exploitation free float capitalisation weighted

technique, whereby the extent of the index reflects the entire value of all the

stocks within the index relative to a selected base amount. The strategy

conjointly takes into consideration constituent changes within the index and

significantly company actions like stock splits, rights, etc. while not moving

the index price.

4.2.1 BASE DATE AND VALUE

The base amount elite for CNX Nifty index is that the shut of costs on

November three, 1995, that marks the completion of 1 year of operations of

NSE's Capital Market section. The base price of the index has been set at a

thousand and a base capital of Rs.2.06 trillion.

4.2.2 CRITERIA FOR SELECTION OF CONSTITUENT STOCKS

The constituents and therefore the criteria for the choice decide the

effectiveness of the index. Choice of the index set relies on the subsequent

criteria:

Liquidity (Impact Cost)

For inclusion within the index, the protection ought to have listed at a

median impact price of 0.50% or less throughout the last six months for

ninetieth of the observations for a basket size of Rs. 2 Crores.

Impact price is price of corporal punishment a dealing during a security in

proportion to the weightage of its free float market capitalization as against the

index free float market capitalization at any purpose of your time. This is often

the share mark-up suffered whereas shopping for / mercantilism the required

amount of a security compared to its ideal worth (best purchase + best sell) / a

pair.

16

Floating Stock

Companies eligible for inclusion in CNX Nifty ought to have a

minimum of 100 percent floating stock. For this purpose, floating stock shall

mean stocks that don't seem to be command by the promoters and associated

entities (where identifiable) of such firms.

Others

a) an organization that comes out with an IPO are going to be eligible for

inclusion within the index, if it fulfils the conventional eligibility criteria for

the index like impact price, market capitalization and floating stock, for a three

month amount rather than a half dozen month amount.

b) Replacement of Stock from the Index:

A stock is also replaced from an index for the subsequent reasons:

1. Mandatory changes like company actions, delisting etc. In such

a state of affairs, the stock having largest free float capitalisation and

satisfying different needs associated with liquidity, turnover and free float are

going to be thought of for inclusion.

2. once a far better candidate is on the market within the

replacement pool, which might replace the index stock i.e. the stock with the

very best free float capitalisation within the replacement pool has a minimum

of double the free float capitalisation of the index stock with very cheap free

float capitalisation.

With relevance (2) on top of, a most of 100 percent of the index size

(number of stocks within the index) is also modified during a civil year.

Changes meted out for (2) on top of area unit no matter changes, if any, meted

out for (1) on top of.

From June 26, 2009, CNX Nifty is computed exploitation Free Float

market capitalization weighted technique, whereby the extent of index reflects

the free float market capitalization of all stocks in Index.

17

4.2.3 INDEX MAINTENANCE

Index Maintenance plays an important role in making certain stability

of the Index yet as in meeting its objective of being a standardized benchmark

of the equity markets.

IISL has recognised an Index Policy Committee that is concerned in

policy and tips for managing the CNX Indices. The Index Maintenance Sub-

committee takes all choices on addition/ deletion of firms in any Index.

The index is reviewed each six months (on half-yearly basis) and a six

weeks notice is given to the market before creating changes to the index set.

4.2.4 HEDGING EFFECTIVENESS

Exhaustive calculations are meted out to see the hedging effectiveness

of the 50-security index CNX Nifty against varied every which way chosen

equally-weighted portfolios of various sizes varied from one to one hundred of

tiny cap, midcap and huge cap firms yet as several business indices/sub-

indices provided by CMIE. It absolutely was discovered that the correlation

(R2) for numerous portfolios and indices exploitation monthly returns

information on the CNX Nifty vis-a-vis different indices was considerably

higher indicating that the CNX Nifty had higher hedging effectiveness.

4.2.5 TRADING IN NIFTY

The National exchange of Asian nation restricted (NSE) commenced

mercantilism in derivatives with index futures on June twelve, 2000. The

futures contracts on NSE area unit supported CNX Nifty. The Exchange later

introduced mercantilism on index choices supported Nifty on June four, 2001.

The turnover within the derivatives section has shown sizable growth within

the last year, with NSE turnover accounting for the entire turnover within the

year 2000-2001.

4.2.6 TOTAL RETURN INDEX

CNX Nifty reflects the comeback one would get if investment is

created within the index portfolios. As Nifty is computed in period of time, it

18

takes into consideration solely the value movements. However, the value

indices don't contemplate the comeback from dividend payments of index

constituent stocks. Solely the capital gains thanks to worth movement is

measured by the value index. So as to induce a real image of returns, the

dividends received from the index constituent stocks conjointly must be

enclosed within the index movement. Such AN index, which has the dividends

received, is named the entire Returns Index.

The Total Returns Index is an index to mirror the returns on the index

from index gain/loss and dividend payments by constituent index stocks.

Methodology

Index info on the subsequent area unit the stipulations for calculation

of Total Returns (TR) Index:

Price Index shut.

Price Index returns.

Dividend pay-outs in Rupees.

Index Base capitalisation on ex-dividend date

Dividend pay-outs as they occur area unit indexed on ex-date.

Indexed dividend = Dividend payout(Rs.) x 1000

Base cap of index (Rs.)

Indexed dividends area unit then reinvested within the index to grant

TR Index.

TR Index = [Prev. TR Index + (Prev. TR Index * Index returns)] +

[Indexed dividends + (Indexed dividends * Index returns)]

Base for each the shut index and TR index shut are going to be a

similar.

CHAPTER V

DATA ANALYSIS AND INTERPRETATIONS

19

5.1 INTRODUCTION

In order to prove the validity of CAPM model in Indian Stock Market

Fama and MacBeths traditional approach was used as the model to prove the

hypothesis. The analysis period is taken from year starting 1st January, 1999 to

31st December 2013, a total time period of 15 years. This period was divided

into seven 9-year sub-periods with eight overlapping period. The periods are

been continuously overlapped to reduce the variability of the beta co-efficient

that were estimated.

5.2 QUANTITATIVE ANALYSIS

Each of the 9 year sub-period formed, it was further divided into three

3-year periods for portfolio formation, portfolio beta estimation and testing

period.

The Nifty 50 stocks as last traded on 31st December, 2013 are taken

into consideration for this research. All the qualifying stocks were included in

the analysis. Summary of the same is shown in the table 5.1.

Table 5.1: Distribution of Analysis Period and Number of Qualifying Stocks.

Three Portfolios each comprising of around 9 stocks at an average was

formed for each sub-periods.

First 3-year slice of each 9-year sub-period was used for portfolio

formation. Beta co-efficient of each stock was calculated by regressing the

daily risk premiums of the stock against daily risk premiums of the CNX

NIFTY 50 index. Any stock changes impacts due to dividend, splits are

excluded. 91 T-bill rates was taken as the risk free return rate for the

calculation.

1 2 3 4 5 6 7

1999 - 2007 2000 - 2008 2001 - 2009 2002 - 2010 2003 - 2011 2004-2012 2005 - 2013

Portfolio Formation Periods 1999 - 2001 2000 - 2002 2001 - 2003 2002 - 2004 2003 - 2005 2004 - 2006 2005 - 2007

Portfolio Beta Estimation Periods 2002 - 2004 2003 - 2005 2004 - 2006 2005 - 2007 2006 - 2008 2007 - 2009 2008 - 2010

Testing Periods 2005 - 2007 2006 - 2008 2007 - 2009 2008 - 2010 2009 - 2011 2010 - 2012 2011 - 2013

Number of Nifty 50 stocks 50 50 50 50 50 50 50

Qualifying Stocks 22 23 24 25 26 29 34

Sub - Periods

20

The following table 5.2 gives the summary of the portfolio formed and

stocks it consists.

Table 5.2: Number of Stocks in Portfolios

The following formula was used to calculate for each stock.

Sub - Periods Portfolio Number Number of Stocks in Portfolios

1 7

1 8

1 7

3 22

1 7

1 8

1 8

3 23

1 8

1 8

1 8

3 24

1 8

1 8

1 9

3 25

1 8

1 9

1 9

3 26

1 9

1 10

1 10

3 29

1 11

1 11

1 12

3 34

2004-2012

2005 - 2013

1999 - 2007

2000 - 2008

2001 - 2009

2002 - 2010

2003 - 2011

21

Where,

rs is the risk premium return on stocks

rb is the risk premium return on index

rs = ri rf

rb = rii - rf

Where,

rf is the risk free rate returns

ri is the stock return

rii is the index return

The portfolio was formed in order of decreasing beta of stocks, i.e.

Portfolio 1 will have the highest beta and portfolio 3 will have the least beta

stocks.

After the formation of the portfolios the next 3-year slice is taken to

recalculate the beta of each stock and the simple average of the beta of the

stock already included in the portfolio as the beta of the portfolio.

The last 3-year slice was used for the testing of the portfolios. Daily

risk premiums of assets were found and was simple averaged to arrive at the

risk premium return of each portfolios.

Thus at end we have 3 portfolio beta calculated from second 3-year

period and 3 portfolio risk premium from last 3-year period for each 9-year

sub-periods formed.

Cross sectional regression equation between beta and risk premiums

were estimated by using the Fama and MacBeths traditional approach.

The regression equation is given by:

Where:

Rip,t Rf,t is the risk premium on ith portfolio in testing period t,

y0t and y1t are the regression coefficients,

Rip,t Rf,t = y0t + y1t ip,t-1 + t

22

ip,t-1 is the beta of ith portfolio calculated in the previous 3-year time

period, and

t is the error term.

5.3 TESTING OF HYPOTHESES

We know that CAPM model is valid when y0 = 0 and y0 0.

Table 5.3: Summary of the Result

From the summary found in Table 5.3 we can say from the t-statistic of y0

and y1 (the table value of t-statistics is 4.303 at confidence level 5%) over the

periods that:

1. y0 ~ 0 in periods except for 2007-2009 and 2010 2012 which may be the

reason followed by the 2008 crisis.

2. y1 0 in all period except for 2010 2012.

3. The negative shown in few periods by y1 is mainly due to the negative risk

premium returns over the period.

4. Support to the above the R2 also proves that there is a strong correlation in the

periods 2010 2012 and 2007 2008.

Thus we can conclude that Fama and MacBeths Traditional approach

shows an ex-post relationship between beta and the risk premiums in the

period 2007 2008 and 2010 2012.

2005 - 2007 2006 - 2008 2007 - 2009 2008 - 2010 2009 - 2011 2010 - 2012 2011 - 2013

y0 -0.012417023 -0.050299357 0.015117246 -0.016088734 0.015145938 -0.014155145 -0.004571895

y1 0.003845075 0.052339500 -0.000723625 0.009708650 -0.033885000 -0.011178107 -0.004322300

se(y0) 0.010059514 0.025834029 0.001672924 0.020126016 0.027211423 0.000720818 0.033851925

se(y1) 0.009958614 0.025920140 0.001656144 0.020397756 0.027392817 0.000735350 0.033850797

se(ER) 0.000281672 0.000211637 0.000046843 0.000166547 0.000447323 0.000027514 0.000478723

R^2 0.360000000 0.803049214 0.160306736 0.184701195 0.604770696 0.995690998 0.016042366

ssreg 0.000000012 0.000000183 0.000000000 0.000000006 0.000000306 0.000000175 0.000000004

ssresid 0.000000079 0.000000045 0.000000002 0.000000028 0.000000200 0.000000001 0.000000229

t(y0) -1.234356103 -1.947019465 9.036422834 -0.799399851 0.556602196 -19.637599779 -0.135055677

t(y1) 0.386105445 2.019259901 -0.436933708 0.475966569 -1.237003138 -15.201061788 -0.127686802

TESTING PERIOD

23

So concluding the two hypotheses as defined previously in the chapter:

1. H01: There is a no positive relationship between expected return and

systematic risk, i.e. slope of CAPM equation is negative.

H11: There is a positive relationship between expected return and

systematic risk, i.e. slope of CAPM equation is positive.

Null Hypothesis is rejected for periods 2010 2012 and 2012

2013.

So there is a positive relation between beta and risk premiums

for the years 2010 2013. So for the current future CAPM model

is held valid.

2. H02: The relationship between expected return and risk is non-linear.

H12: The relationship between expected return and risk is linear.

Null Hypothesis is rejected for periods 2006 -2008 and 2010

2012.

So the market had an equivalent return to the risk the portfolios

had thus proved the CAPM model for the period 2006 2008 and

2010 2012.

CHAPTER VI

FINDINGS, CONCLUSION AND SUGGESTIONS

24

6.1 FINDINGS

The Findings from this research works were:

There was a positive relationship between expected return and systematic

risk for the period 2010 2013.

The expected return and systematic risk showed linearity for period 2006

2008 and 2010 2012.

Negative values were found which were basically due to the negative

return of the risk premium returns over years.

The systematic risk and the expected returns showed a direct relationship

between them for the period 2010 2013 only.

The correlation between the beta and risk returns were strong in period

2006 2008 and 2010 2012.

6.2 CONCLUSION

We can conclude from the findings that the CAPM model was not

valid in past years and starting from year 2010 it has proved valid as shown by

the linearity among the adjusted returns and the beta estimates of the

portfolios.

Beside this while calculating the beta for first two slices of 3-years it

was observed that the beta did not vary much from the market return except

few volatile stocks (example Indusind bank showed a great variation as

compared to others). Also the risk premium return for third 3-year gave a

negative return continuously for last few years of the periods taken.

6.3 SUGGESTIONS

It could be suggested from the findings and conclusion that seeing the

current Indian stock trend and mostly the NSE CNX NIFTY 50 stocks we can

depend on CAPM model and expect an equivalent and more linear

relationship between the risk taken and the return expected, i.e. the amount of

risk taken will also result into the equivalent return from the portfolio.

25

6.4 SUGGESTIONS FOR FURTHER RESEARCH

The following research was done taking the NIFTY 50 Index

companies of the National Stock Exchange traded stocks. For a more deep

research and a more accurate result the following suggestions and

recommendation can be used to make the research more accurate:

1. Monthly Risk free rates were taken in this case, daily risk free return could

have given more accurate answers.

2. Stocks trading in the particular years taken could have given a different

and better dimension to the research work.

3. Taking into consideration the dividends and stock split which were

excluded in this research may give a different view to the result.

4. Using a multi-factor analysis by taking the market-cap, book to size value

etc. will add more variance to the result.

5. Different methods like Fama French, BJS etc can be used to prove the

CAPM model.

6. Petengils conditional approach can be used to see how CAPM model

holds in up and down trend of market conditions over years.

7. All the 1635 currently listed NSE stocks (as on July, 2013) can be taken

into consideration to understand the real impact and the truthiness of

CAPM model in Indian Stock Market.

So coming to the final conclusion we saw that Fama and MacBeths

Traditional Unconditional Approach was held true from 2010 only thus

proving the validity of CAPM model in the current Indian market trend, but

was not true years ago.

bibliography

Fama, E.F. and MacBeth, J.D. (1973). Risk, Return, and Equilibrium: Empirical

`Tests. Journal of Political Economy.

Franco, M. and Gerald, A.P. (1973). A Test of the capital Asset Pricing Model on

Europe Stock Markets.

Theriou, N., Aggelidis, V. and Spiridis, T. Empirical testing of Capital Asset Pricing

Model.

Mostafizur, R. and Azizul, B. (2006). An empherical testing of capital asset pricing

model in Bangladesh. Journal of Research (Science).

Cudi,T.G. and Gulnara, R.(2007). Test of Capital Asset Pricing Model. Dou

niversitesi Dergisi, 8 (1) 47-58.

Mauri, P. (2007). Empirical Test of Asset Pricing Models in Finnish Stock Market.

Sylvester, J. (2007). A test of the capital asset pricing model: Studying stocks

on the Stockholm stock exchange.

David, W. (2010). Testing the capital asset pricing model on the Uganda Stock

Exchange.

Rumeysa, B. A test of the validity of capital asset pricing model in Istanbul Stock

Exchange. EuroEconomica 4(30), ISSN: 1582-88592011, 2011.

Josipa, D. and Zdravka, A.(2013). Testing CAPM model on the emerging markets of

the central and south-eastern Europe. Croatian Operational Research Review

(CRORR), Vol. 4.

Kapil, C. (2010). Testing Capital Asset Pricing Model: Emperical Evidences from

Indian Equity Market. Eurasian Journal of Business and Economics, 3 (6),

127-138.

Ravi, K. (2011). Testing of Capital Asset Pricing Model during an upward trend in the

Indian Stock Market. Indian Journal of Finance.

Chawla, D. and Sondhi, N. (2011). Research Methodology concepts and cases. New

Delhi, India: Vikash Publishing House Ltd.

S&P CNX Nifty. In Wikipedia. Retrieved February 22, 2014, from

http://en.wikipedia.org/wiki/S&P_CNX_Nifty.

http://en.wikipedia.org/wiki/S&P_CNX_Nifty

APPENDICES