research proposal idp final

8/12/2019 Research Proposal IDP Final

1/26

Research Proposal

On

Validity of Capital Asset Pricing Model & Stability of Systematic

Risk (Beta). An Empirical Study on Indian Stock Market

PAYAL B. BHATT

127700592008

YESHA B. MANKAD

127700592067

MBA Sem III

SUBMITTED TO

JAYSUKHLAL VADHAR INSTITUTE OFMANAGEMENT STUDIES

JAMNAGAR

AFFILITED TO:

GUJARAT TECHNOLOGICAL UNIVERSITY


2/26

Introduction

To

FMCG (Fast Moving Consumer Goods)

The term FMCG (fast moving consumer goods), although popular and frequently

used does not have a standard definition and is generally used in India to refer to

products of everyday use. Conceptually, however, the term refers to relatively fast

moving items that are used directly by the consumer. Thus, a significant gap exists

between the general use and the conceptual meaning of the term FMCG.

Further, difficulties crop up when attempts to devise a definition for FMCG. The

problem arises because the concept has a retail orientation and distinguishes

between consumer products on the basis of how quickly they move at the retailers

shelves. The moot question therefore, is what industry turnaround threshold should

be for the item to qualify as an FMCG.

Products which have a quick turnover, and relatively low cost are known as Fast

Moving Consumer Goods (FMCG). FMCG products are those that get replaced

within a year. Examples of FMCG generally include a wide range of frequently

purchased consumer products such as toiletries, soap, cosmetics, tooth cleaning

products, shaving products and detergents, as well as other non-durables such as

glassware, bulbs, batteries, paper products, and plastic goods. FMCG may also

include pharmaceuticals, consumer electronics, packaged food products, soft

drinks, tissue paper, and chocolate bars.


3/26

The FMCG Industry

The Indian FMCG sector is the fourth largest sector in the economy with a total

market size in excess of US$ 13.1 billion. It has a strong MNC presence and is

characterized by a well-established distribution network, intense competition

between the organized and unorganized segments and low operational cost.

Availability of key raw materials, cheaper labor costs and presence across the

entire value chain gives India a competitive advantage.

The FMCG market is set to treble from US$ 11.6 billion in 2003 to US$ 33.4

billion in 2015. Penetration level as well as per capita consumption in most product

categories like jams, toothpaste, skin care, hair wash etc in India is low indicating

the untapped market potential. Burgeoning Indian population, particularly the

middle class and the rural segments, presents an opportunity to makers of branded

products to convert consumers to branded products.

Industry Classification

The FMCG industry is volume driven and is characterized by low

margins. The products are branded and backed by marketing, heavy advertising,

slick packagingand strong distribution networks. The FMCG segment can be

classified under the premium segment and popular segment. The premium segment

caters mostly to thehigher/upper middle class which is not as price sensitiveapart from being brandconscious. The price sensit ive popular or

mas s se gme nt con si st s of co nsu mer s belonging mainly to the semi-

urban or rural areas who are not particularly brandconscious.


4/26

FMCG Industry Economy

FMCG industry provides a wide range of consumables and accordingly the

amount of money circulated against FMCG products is also very high. The

competition among FMCG manufacturers is also growing and as a result of this,

investment in FMCG industry is also increasing, specifically in India, where

FMCG industry is regarded as the fourth largest sector with total market size of

US$13.1 billion. FMCG Sector in India is estimated to grow 60% by 2010. FMCG

industry is regarded as the largest sector in New Zealand which accounts for 5% of

Gross Domestic Product (GDP).


5/26

History of FMCG

Fast moving consumer goods (FMCG), also known as consumer packaged goods

(CPG) are the products that have a quick turnover and relatively low cost.

Consumers generally put less thought into the purchase of FMCG than they do for

any other products.

The Indian FMCG industry witnessed significant changes through through 1990's.

Many players had been facing severe problems on account of increased

competition from small and regional players and from slow growth across its

various product categories. As a result, most of the companies were forced to

revamp their product, marketing, distribution and customer service strategies to

strengthen their position in the market.

By the turn of 20th century, the face of Indian FMCG industry had changed

significantly. With the liberalization and growth of economy, the Indian customer

witnessed an increasing exposure to new domestic and foreign products throughdifferent media, such as television and the Internet. Apart from this, social changes

such as an increase in the number of nuclear families and the growing number of

working couples resulting in increased spending power also contributed to the

increase in the Indian consumer's Personal consumption. The realization of the

customer's growing awareness and the need to meet changing requirements and

preferences on account of changing lifestyles required the FMCG producing

companies to formulate customer-centric strategies. These changes have a positive

impact, leading to the rapid growth in the FMCG industry. Increased availability of

retail space, rapid urbanization and qualified manpower also boosted the growth of

the organized retailing sector.


6/26

HUL led the way in revolutionizing the product, market, distribution and service

formats of the FMCG industry by focusing on rural markets, direct distribution,

creating new product, distribution and service formats. The FMCG sector also

received a boost by the government led initiatives in the 2003 budget such as

setting up of excise free zones in various parts of the country that witnessed firms

moving away from outsourcing to manufacturing by investing in the zones.

Though the absolute profit made on FMCG products is relatively small, they

generally sell in large numbers and so the cumulative profit on such products can

be large. Unlike some industries, such as automobiles, computers and airlines

FMCG doesn't suffer from mass layoffs ever time the economy starts to dip. A

person may put off buying a car but he Willnot put off having his dinner.

Unlike other economy sectors, FMCG share float in a steady manner irrespective

of global market dip, because they generally satisfy rather fundamental, as opposed

to luxurious needs. The FMCG sector which is growing at a rate of 9% is the

fourth largest sector in the Indian economy and is a worth of Rs. 93000 crores. The

main contributor, making up 32% of the sector, is the south Indian region. It is

predicted that in the year 2010, the FMCG sector will be worth Rs.143000 crores.

The sector being one of the biggest sectors of the Indian economy provides upto 4

million jobs.


7/26

The FMCG sector consists of the following categories:

Personal care- Oral care, Hair care, Wash (soaps), Cosmetics and Toiletries,

Deodorants and perfumes, Paper products (Tissues, Diapers, Sanitary products)

and Shoe care; the major players being Hindustan Uni-liver Limited, Godrej Soaps,

Colgate, Marico, Dabur and Procter & Gamble.

Household Care - Fabric wash (laundry soaps and detergents), Household

cleaners (Dish/utensil/floor/toilet cleaners), Air fresheners, Inseticides and

Mosquito repallants, Metal polish and Furniture polish; the major players being

HinduatnUni-liver Limited, Nirma and Ricket Colman.

Branded and Packaged Foods and Beverages -Health beverages, Soft drinks,

Staples/Cereals, Bakery products (Biscuits, Breads, cakes), Snack foods,

Chocolates, Ice-creams, Tea, Coffee, Processed fruits, Processed vegetables,

Processed Meat, Branded flour, Bottled water, Branded rice, Branded sugar,

Juices; the major players being Hindustan Uni-liver Limited, Nestle, Coca-Cola,

Cadbury, Pepsi and Dabur.

Spirits and Tobacco -The major players being ITC, Godfrey, Philips and UB.


8/26

INTRODUCTION

TO

CAPM (CAPITAL ASSET PRICING MODEL)

The Capital Asset Pricing Model (CAPM) is used to determine a theoretically

appropriate required rate of return of an asset, if that asset is to be added to an

already well-diversified portfolio, given that asset's non-diversifiable risk. The

model takes into account the asset's sensitivity to non-diversifiable risk (alsoknown assystematic risk ormarket risk), often represented by the quantitybeta ()

in the financial industry, as well as the expected return of the market and the

expected return of a theoretical risk-free asset. CAPM suggests that an investors

cost of equity capital is determined bybeta.An extension to the CAPM is thedual-

beta model, which differentiatesdownside beta fromupside beta.[2]

The CAPM was introduced byJack Treynor (1961, 1962),William Sharpe (1964),

John Lintner (1965a,b) and Jan Mossin (1966) independently, building on the

earlier work of Harry Markowitz ondiversification and modern portfolio theory.

Sharpe, Markowitz and Merton Millerjointly received theNobel Memorial Prize

in Economics for this contribution to the field offinancial economics.

Because of its simplicity and despite more modern approaches to asset pricing and

portfolio selection (like Arbitrage pricing theory and Merton's portfolio problem,

respectively), CAPM still remains popular.
http://en.wikipedia.org/wiki/Rate_of_returnhttp://en.wikipedia.org/wiki/Assethttp://en.wikipedia.org/wiki/Portfolio_%28finance%29http://en.wikipedia.org/wiki/Diversification_%28finance%29http://en.wikipedia.org/wiki/Riskhttp://en.wikipedia.org/wiki/Systematic_riskhttp://en.wikipedia.org/wiki/Market_riskhttp://en.wikipedia.org/wiki/Beta_%28finance%29http://en.wikipedia.org/wiki/Expected_returnhttp://en.wikipedia.org/wiki/Risk-free_interest_ratehttp://en.wikipedia.org/wiki/Betahttp://en.wikipedia.org/wiki/Dual-betahttp://en.wikipedia.org/wiki/Dual-betahttp://en.wikipedia.org/wiki/Downside_betahttp://en.wikipedia.org/wiki/Upside_betahttp://en.wikipedia.org/wiki/Capital_asset_pricing_model#cite_note-Misleading_Betas:_An_Educational_Example-2http://en.wikipedia.org/wiki/Capital_asset_pricing_model#cite_note-Misleading_Betas:_An_Educational_Example-2http://en.wikipedia.org/wiki/Capital_asset_pricing_model#cite_note-Misleading_Betas:_An_Educational_Example-2http://en.wikipedia.org/wiki/Jack_L._Treynorhttp://en.wikipedia.org/wiki/William_Forsyth_Sharpehttp://en.wikipedia.org/wiki/John_Lintnerhttp://en.wikipedia.org/wiki/Jan_Mossinhttp://en.wikipedia.org/wiki/Harry_Markowitzhttp://en.wikipedia.org/wiki/Diversification_%28finance%29http://en.wikipedia.org/wiki/Modern_portfolio_theoryhttp://en.wikipedia.org/wiki/Merton_Millerhttp://en.wikipedia.org/wiki/Nobel_Memorial_Prize_in_Economic_Scienceshttp://en.wikipedia.org/wiki/Nobel_Memorial_Prize_in_Economic_Scienceshttp://en.wikipedia.org/wiki/Financial_economicshttp://en.wikipedia.org/wiki/Arbitrage_pricing_theoryhttp://en.wikipedia.org/wiki/Merton%27s_portfolio_problemhttp://en.wikipedia.org/wiki/Merton%27s_portfolio_problemhttp://en.wikipedia.org/wiki/Arbitrage_pricing_theoryhttp://en.wikipedia.org/wiki/Financial_economicshttp://en.wikipedia.org/wiki/Nobel_Memorial_Prize_in_Economic_Scienceshttp://en.wikipedia.org/wiki/Nobel_Memorial_Prize_in_Economic_Scienceshttp://en.wikipedia.org/wiki/Merton_Millerhttp://en.wikipedia.org/wiki/Modern_portfolio_theoryhttp://en.wikipedia.org/wiki/Diversification_%28finance%29http://en.wikipedia.org/wiki/Harry_Markowitzhttp://en.wikipedia.org/wiki/Jan_Mossinhttp://en.wikipedia.org/wiki/John_Lintnerhttp://en.wikipedia.org/wiki/William_Forsyth_Sharpehttp://en.wikipedia.org/wiki/Jack_L._Treynorhttp://en.wikipedia.org/wiki/Capital_asset_pricing_model#cite_note-Misleading_Betas:_An_Educational_Example-2http://en.wikipedia.org/wiki/Upside_betahttp://en.wikipedia.org/wiki/Downside_betahttp://en.wikipedia.org/wiki/Dual-betahttp://en.wikipedia.org/wiki/Dual-betahttp://en.wikipedia.org/wiki/Betahttp://en.wikipedia.org/wiki/Risk-free_interest_ratehttp://en.wikipedia.org/wiki/Expected_returnhttp://en.wikipedia.org/wiki/Beta_%28finance%29http://en.wikipedia.org/wiki/Market_riskhttp://en.wikipedia.org/wiki/Systematic_riskhttp://en.wikipedia.org/wiki/Riskhttp://en.wikipedia.org/wiki/Diversification_%28finance%29http://en.wikipedia.org/wiki/Portfolio_%28finance%29http://en.wikipedia.org/wiki/Assethttp://en.wikipedia.org/wiki/Rate_of_return


9/26

Formula:

where:

is the expected return on the capital asset is the risk-free rate of interest such as interest arising from government

bonds

is the sensitivity of the expected excess asset returns to the expected

excess market returns, or also ,

is the expected return of the market is sometimes known as the market premium (the difference

between the expected market rate of return and the risk-free rate of return).

is also known as the risk premium

Restated, in terms of risk premium, we find that:

Security Market Line:

The SML essentially graphs the results from the capital asset pricing model

(CAPM) formula. The x-axis represents the risk (beta), and the y-axis represents

the expected return. The market risk premium is determined from the slope of the

SML.
http://en.wikipedia.org/wiki/Sensitivity_and_specificityhttp://en.wikipedia.org/wiki/Security_market_linehttp://en.wikipedia.org/wiki/Security_market_linehttp://en.wikipedia.org/wiki/Sensitivity_and_specificity


10/26

The relationship between and required return is plotted on the securities market

line(SML), which shows expected return as a function of . The intercept is the

nominal risk-free rate available for the market, while the slope is the market

premium, E(Rm)Rf.

The securities market line can be regarded as representing a single-factor model of

the asset price, where Beta is exposure to changes in value of the Market. The

equation of the SML is thus:

It is a useful tool in determining if an asset being considered for a portfolio offers a

reasonable expected return for risk. Individual securities are plotted on the SML

graph. If the security's expected return versus risk is plotted above the SML, it is

undervalued since the investor can expect a greater return for the inherent risk.

And a security plotted below the SML is overvalued since the investor would be

accepting less return for the amount of risk assumed.

Asset Pricing:

Once the expected/required rate of return is calculated using CAPM, we can

compare this required rate of return to the asset's estimated rate of return over a

specific investment horizon to determine whether it would be an appropriate

investment. To make this comparison, you need an independent estimate of the

return outlook for the security based on either fundamental or technical analysis

techniques, including P/E, M/B etc.


11/26

Assuming that the CAPM is correct, an asset is correctly priced when its estimated

price is the same as the present value of future cash flows of the asset, discounted

at the rate suggested by CAPM. If the estimated price is higher than the CAPM

valuation, then the asset is undervalued (and overvalued when the estimated price

is below the CAPM valuation). When the asset does not lie on the SML, this could

also suggest mis-pricing. Since the expected return of the asset at time is

, a higher expected return than what CAPM suggests

indicates that is too low (the asset is currently undervalued), assuming that at

time the asset returns to the CAPM suggested price.

The asset price using CAPM, sometimes called thecertainty equivalent pricing

formula,is a linear relationship given by

Where,

Is the payoff of the asset or portfolio.
http://en.wikipedia.org/w/index.php?title=Certainty_equivalent_pricing_formula&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Certainty_equivalent_pricing_formula&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Certainty_equivalent_pricing_formula&action=edit&redlink=1http://en.wikipedia.org/w/index.php?title=Certainty_equivalent_pricing_formula&action=edit&redlink=1


12/26

ISSUES / PROBLEMS OF THE SECTOR

Increasing rate of inflation, which is likely to lead to higher cost of rawmaterials.

The standardization of packaging norms that is likely to be implemented bythe Government by Jan 2013 is expected to increase cost of beverages,

cereals, edible oil, detergent, flour, salt, aerated drinks and mineral water.

Steadily rising fuel costs, leading to increased distribution costs. The present slow-down in the economy may lower demand of FMCG

products, particularly in the premium sector, leading to reduced volumes.

The declining value of rupee against other currencies may reduce margins ofmany companies, as Marico, Godrej Consumer Products, Colgate, Dabur,

etc who import raw materials.

RESEARCH PROBLEM

The model assumes that the variance of returns is an adequate measurementof risk. This would be implied by the assumption that returns are normally

distributed, or indeed are distributed in any two-parameter way, but for

general return distributions other risk measures (likecoherent risk measures)

will reflect the active and potential shareholders' preferences more

adequately.

The model assumes that all active and potential shareholders have access tothe same information and agree about the risk and expected return of all

assets (homogeneous expectations assumption).
http://en.wikipedia.org/wiki/Coherent_risk_measurehttp://en.wikipedia.org/wiki/Coherent_risk_measure


13/26

The model assumes that the probability beliefs of active and potentialshareholders match the true distribution of returns. A different possibility is

that active and potential shareholders' expectations are biased, causing

market prices to be informationally inefficient. This possibility is studied in

the field of behavioral finance, which uses psychological assumptions to

provide alternatives to the CAPM such as the overconfidence-based asset

pricing model of Kent Daniel, David Hirshleifer, and Avanidhar

Subrahmanyam.
http://en.wikipedia.org/wiki/Behavioral_financehttp://en.wikipedia.org/wiki/David_Hirshleiferhttp://en.wikipedia.org/wiki/David_Hirshleiferhttp://en.wikipedia.org/wiki/Behavioral_finance


14/26

REVIEW OF LETERATURE

1) The capital asset pricing model (CAPM) is the standard risk-return modelused by most academicians and practitioners. The underlying concept ofCAPM is that investors are rewarded for only that portion of risk which is not

diversifiable. This non-diversifiable risk is termed as beta, to which expected

returns are linked. The objective of the study is to test the validity of this

theory in Indian capital market & the stability of this non diversifiable risk

(i.e. systematic risk or beta). The study has used the data of 10 stocks & 10

sectoral indices listed on the BSE, for a period of 4 years (January 2005 to

December 2008) for the analysis. The studies provide evidence against the

CAPM hypothesis. And finally, the studies also provide the evidence against

the stability of systematic risk.


15/26

2)H. Jamal Zubairi, ShaziaFarooq Department of Finance andAccounting College of Business Management, Karachi :

The Capital Asset Pricing Model (CAPM) and Arbitrage PortfolioTheory

(APT) have been commonly used techniques in the global investing community

for calculating the required return of a risky asset. This paper investigates

whether CAPM and APT are valid models for determining price/return of the

fertilizer and the oil & gas sector companies listed on the Karachi Stock

Exchange (KSE). The purpose of the research is also to identify plausible

reasons for deviations from the theories. The conclusions arrived at through

data analysis reveal weak correlation between realized excess returns (i.e.

actual returns over and above the risk free rate) and the expected return based

on CAPM. With respect to APT model, the study reflects that macroeconomic

factors including changes in GDP, inflation, exchange rate and market return do

not serve as valid determinants of returns on oil, gas and fertilizer stocks.


16/26

3)KapilChaoudhary , SakshiChaoudhary (2010):The present study examines the Capital Asset Pricing Model (CAPM) for the

Indian stock market using monthly stock returns from 278 companies of BSE 500

Index listed on the Bombay stock exchange for the period of January 1996 to

December 2009. The findings of this study are not substantiating the theorys basic

result that higher risk (beta) is associated with higher levels of return. The model

does explain, however, excess returns and thus lends support to the linear

structure of the CAPM equation. The theorys prediction for the intercept is that it

should equal zero and the slope should equal the excess returns on the marketportfolio. The results of the study lead to negate the above hypotheses and offer

evidence against the CAPM. The tests conducted to examine the nonlinearity of

the relationship between return and betas bolster the hypothesis that the expected

return-beta relationship is linear. Additionally, this study investigates whether the

CAPM adequately captures all-important determinants of returns including the

residual variance of stocks. The results exhibit that residual risk has no effect on

the expected returns of portfolios.


17/26

4)Abu Hassan Md Isa and Chin-Hong Puah and Ying-Kiu Yong(2008):

This paper examines the applicability of CAPM in explaining the risk-return

relation in the Malaysian stock market for the period of January 1995 to December

2006. The test, using linear regression method, was carried out on four models: the

standard CAPM model with constant beta .The standard CAPM model with time-

varying beta .The CAPM model conditional on segregating positive and negative

market risk premiums with constant beta .As well as the CAPM model conditional

on segregating positive and negative market risk premiums with time varying beta

. Empirical results indicate that both the standard CAPM models are statistically

insignificant. However, the CAPM models conditional on segregating positive and

negative market risk premiums (Model III and Model IV) are statistically

significant. In addition, this study also discovers that time varying beta provides

better explanatory power.


18/26

5)Chandra ShekharBhatnagar,RiadRamlogan :The Sharpe (1964), Lintner (1965) and Black (1972) Capital Asset Pricing Model

(CAPM) is considered one of the foundational contributions to the practice of

finance. The model postulates that the equilibrium rates of return on all risky assets

are a linear function of their covariance with the market portfolio. Recent work by

Fama and French (1996, 2006) introduce a Three Factor Model that questions the

real world application of the CAPM Theorem and its ability to explain stock

returns as well as value premium effects in the United States market. This thesis

provides an out-of-sample perspective to the work of Fama and French (1996,2006). Multiple regression is used to compare the performance of the CAPM, a

split sample CAPM and the Three Factor Model in explaining observed stock

returns and value premium effects in the United Kingdom market. The

methodology of Fama and French (2006) was used as the framework for this study.

The findings show that the Three Factor Model holds for the United Kingdom

Market and is superior to the CAPM and the split sample CAPM in explaining

both stock returns and value premium effects. The real world application of the

CAPM is therefore not supported by the United Kingdom data.


19/26

6)Chien-Chung Nieh and Hsueh-Chu Yao (2013) :In this study, we used the PSTR (panel smooth transition regression) model to

investigate the nonlinear relationship between beta (systematic risk) and returns

(world market excess returns) for net oil export and net oil import groups. We set

the volatility of world market excess return as the threshold variable and the

percentage changes of crude oil price and exchange rate as the control variables.

Our results support the use of a nonlinear model to elucidate the behavior both

groups. We found that all beta values are positive and higher in the low regime

(i.e., volatility of world market excess return is low) and lower in the high regime(i.e., volatility of world market excess return is high). For the net oil export group,

the crude oil price change percentage is positive in the high regime, but the

exchange rate percentage change is positive in the low regime. For the net oil

import group, in both the low and high regimes, changes in crude oil price and

exchange rate have equally positive effects on the individual market excess return.


20/26

7)Mika VaihekoskiEeroPtri (2007) :This study investigates the relationship between different sorts of risk and return

on six Finnish value-weighted portfolios from the year 1987 to 2004. Furthermore,

we investigate if there is a large equity premium in Finnish markets. Our models

are the CAPM, APT and CCAPM. For the CCAPM we concentrate on the

parameters of the coefficient of the relative risk-aversion and the marginal rate of

intertemporal substitution of consumption, whereas for the CAPM we estimate the

market beta and for the APT we will select some macroeconomic factors a priori.

The main contribution of this study is the use of General Method of Moments(GMM). We implement it to all of our models. We conclude that the CAPM is still

a robust model, but we find also support for the APT. In contradiction to majority

of studies, we are able to get theoretically sound values for the CCAPMs

parameters. The risk-aversion parameters stay below two and the marginal rate of

intertemporal substitution of consumption is close to one. The market beta is still

the most dominant risk factor, but the CAPM and APT are as good in

terms of explanatory power.


21/26

8) Chandra ShekharBhatnagar, RiadRamlogan :

The Sharpe (1964), Lintner (1965) and Black (1972) Capital Asset Pricing Model

(CAPM) is considered one of the foundational contributions to the practice of

finance. The model postulates that the equilibrium rates of return on all risky assets

are a linear function of their covariance with the market portfolio. Recent work by

Fama and French (1996, 2006) introduce a Three Factor Model that questions the

real world application of the CAPM Theorem and its ability to explain stock

returns as well as value premium effects in the United States market. This thesis

provides an out-of-sample perspective to the work of Fama and French (1996,

2006). Multiple regression is used to compare the performance of the CAPM, a

split sample CAPM and the Three Factor Model in explaining observed stock

returns and value premium effects in the United Kingdom market. The

methodology of Fama and French (2006) was used as the framework for this study.

The findings show that the Three Factor Model holds for the United Kingdom

Market and is superior to the CAPM and the split sample CAPM in explaining

both stock returns and value premium effects. The real world application of the

CAPM is therefore not supported by the United Kingdom data.


22/26

9)Kushankur Dey & Debasish Maitra, Doctoral Participant :Investment theory in securities market pre-empts the study of the relationship

between risk and returns. A review of studies conducted for various markets in the

world that researchers have used a number of methodologies to test the validity of

CAPM. While some studies have supported and agreed with the validity of CAPM,

some others have reported that beta alone is not a suitable predictor of asset pricing

and that a number of other factors could explain the cross-section of returns. The

paper reiterates the importance of a multifactor model in the explanation ofinvestors required rate of return of the portfolio in the Indian capital market. The

results show that intercept is significantly different from zero and the combination

ofsizei, ln(ME/BE)i, (P/EiP/Em) do not explain the variation in security returns

under both percentage and log return series while (di-Rf) shows very dismal result.

The combination ofi, ln(ME/BE)i, (P/Ei P/Em), sizei, and (di-Rf) do not explain

the variation in security returns when log return series is used and the combination

of i, ln(ME/BE)i, sizeialso do not explain any variation in security returns when

percentage return series is used. However, beta alone, when considered

individually in two parameter regressions and also multi-factor model, does not

explain the variation in security/portfolio returns. This casts doubt on the validity

of extended and standard CAPM. The empirical findings of this paper would be

useful to financial analysts in the Indian capital market. From the researchers

prerogative multifactor analysis would be more indicative one to include some

macroeconomic factors, firm-specific factors and market factors to enlarge the

understanding of modern finance and to unfold the dilemma of using CAPM model

in asset-pricing.


23/26

10)MazenDiwani, HosseinAsgharian (2010) :This paper is designed to examine the validity of the CAPM model in the emerging

markets. Itook the Indian market to be the case in which we examine the

applicability of this model andtherefore I decided to perform the study on one of

the biggest Indian markets; Bombay StockExchange. The SENSEX30 was chosen

as the examined index and I performed the study on the28 listed companies in the

market (BSE30 or SENSEX30). I used weekly stocks returns for the period

Nov04 to OCT09. To eliminate the measurement bias which will be incurred

during the study, a window of 53 weeks was taken to regress the weekly returns ofthe listed stocks on the weekly returns of the SENSEX30 index at the same period,

this will result in 53 betas for each stock in the first period, and then we started to

move the window week by week. When testing the CAPM model for the whole

five-year period hasnt showed any strong evidence that support the validity of this

model and in order to get better estimates, we divided the whole sample into 5

subsamples of one year each. We have examined three tests for each year of the

whole 5 year sample and the results have shown some better estimates for some of

the years but still did not support the CAPM hypothesis When running the non-

linearity test, it was proven that the model explains the excess returns which-in

return-supports the linear structure of the CAPM equation.

This paper is solely based on the fact that in order for the model to be valid and

strong academically, the alpha (the intercept) should equal to zero and the beta (the

slope) should equalthe excess returns on the market portfolio. This was a pure

prediction of the CAPM, therefore wetested the above hypotheses but the results

failed to prove or provide any evidence that coincide with the null hypotheses!

The second part of this investigation was to examine the ability of the CAPM


24/26

model to provide a non-linearity relationship between the return and betas.

Conducting the test has shown that the expected return-beta relationship is linear.

In fact, this paper has gone too far by also including a brief investigation over

whats called the non-systematic test. The idea behind this was to investigate

whether the CAPM can include allthe components of the stocks returns including

the residual variance of the stocks. Our results based on the test for the non-

systematic risk-show that the residual risk has no effect on the expected returns of

the listed stocks!


25/26

OBJECTIVES OF THE STUDY

To identify the accuracy of beta on the basis of company return Validity of CAPM model for selected FMCG Company. To use the CAPM to establish benchmarks for measuring the performance of

investment portfolios.

To infer from the CAPM the correct risk-adjusted discount rate to use indiscounted-cash flow

Valuation models.


26/26

STATEMENT OF HYPOTHESIS

Ho:

H1:

SAMPLE DESIGN

TYPES OF RESEARCH Descriptive Research

DAT A COLLECTION METHOD Secondary data

STASTICAL TOOLSAppropriate statistical tools will be

applied

SAMPLE UNITS FMCG Industry (10 Companies)

LIMITATIONS OF THE STUDY

Limited sample size

Time constraint is limited Study is mainly dependent on assumptions.

research proposal idp final

Documents