Portfolio Managent_saurabh Chhabra

PORTFOLIO MANAGEMENT March 25, 2011

PORTFOLIO MANAGENT:

Study of Top 30 Companies of Bombay Stock Exchange through

Capital Asset Pricing Model Project Report submitted in partial fulfillment of the requirements for the Degree

of Masters of International Business

Under the guidance of

Ms. Sunanina Kanojia

Submitted by

Saurabh Chhabra

MIB

Batch of 2011

Department of Commerce

Delhi School of Economics

University of Delhi

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DeclarationThis is to certify that the dissertation titled “Portfolio Management: Study of Capital Asset Pricing Model on the Stocks of BSE Sensex” submitted in partial fulfillment of the requirements of the award of the degree of Masters of International Business program is based on original research work carried out by Saurabh Chhabra, conducted under the guidance of Ms Sunaina Kanojia, for submission to the Department of Commerce, Delhi University.

It is further certified that the project report, or any part thereof, has not been submitted elsewhere for any other purpose, and no part of this work has been copied from any source. All references, wherever used, have been duly acknowledged.

( ) ( )Saurabh Chhabra Ms. Sunaina Kanojia

Master of International Business Department of Commerce Roll No:44, IVth Semester University of Delhi

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Acknowledgement

“No man is an island entire of itself” (John Donne, 1572-1631).The completion of this study would not have been possible without the help, encouragement and support of many individuals to whom I would like to express my deepest gratitude.

I would take this opportunity to express my sincere gratitude to Ms. Sunaina Kanojia for her invaluable inspiration, guidance and support through out this project. I truly appreciate her inputs and count it a privilege to have worked under the supervision. This dissertation report has given me immense knowledge about the institution of Capital Asset Pricing Model in a broader sense, its problems and its road ahead.

Thanks also to all the professors and teaching faculty for providing necessary guidance and valuable inputs. I would also like to extend my thanks to my friends in the Commerce Department (from Delhi School of Economics) who have helped me in the better understanding of the subject. Their insightful feedback about the project work helped a long way in shaping this final report.

Saurabh Chhabra

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TABLE OF CONTENTS

Abstract………………………………..………………………………………………………………………………,………………………………6

Chapter 1: Introduction……….………………………………………………………………………………………………………………………………….7

1.1 Scope of the dissertation….………………….…………………………………….….…………………………………………….....8

1.2 Objectives of the Study………………….……………………………………………….……………………………………………….9

1.3 Methodology…………………………………………………………………………………………………………………………………..10

1.4 Organization of the dissertation………………..…….…………………………………………………………………………….11

1.5 Limitations……………………………………………...….….………………………………………………………………………………12

Chapter 2: Conceptual Framework of Capital Asset Pricing Model

Review of Literature..……..……………………………………………….……………………………………………………………………13

2.1 Introduction of Portfolio Management…………..……………………………………………………………………………….14

2.2 Selection of Portfolios…………………………..………………………………………….……………………………………………..15

2.3 Evolution of Portfolio Management……………………………………………..…………………………………….……………16

2.4 Literature in Capital Asset Pricing Model…………………………………….….……………………………………………....18

2.5 Background….……………………………………………………………………………….…………………………………………………21

2.6 Security Market Line…………..………………………………………………………….………………………………………………..23

2.7 Risk & Diversification………….…………………………………………………………………………………………………………...24

2.8 Market Portfolio……………………………………………….……………………………………………………………………………..25

2.9 Assumptions of CAPM……………………………………….…………………………………………………………………………….26

2.10 Limitations of CAPM………...……………………………………………………………………………………………………………27

2.11 Summary………………………....……………………………………………………………………………………………………………28

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Chapter 3: CAPM: Conceptual Research

3.1 Introduction & Background of Research…………………………………………………………………………………………..30

3.2 Portfolio Theory, Riskless Lending and Borrowing and Fund Separation………………………………………….32

3.3 Capital Asset Pricing Model……………………………………………………………………………………………………………..33

3.4 Is CAPM Useful……………………………………………………………………………………………………………………………….35

Chapter 4: Use of CAPM in BSE Sensex: An Empirical Study

4.1 Empirical Study of Applicabilty of CAPM in BSE Sensex…………………………………………………………………….39

4.2 Inferences of Empirical Study…………………………………………………………………………………………………………..59

4.3 Application of CAPM in Strategic Planning…………………………………..………………………………………………….63

4.4 Building A Portfolio……………………………………………………………………………………………………………………..…..64

4.5 Summary………………………………………………………………………………………………………………………………….….….65

Chapter 5

5.1 Conclusion…………………...………………………………………………………………………………………………….………………67

References………………………………………………………………………………………………………………………………………….…69

Annexures…………………………..…………………………………………………………………………………………………………………71

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AbstractThe proposition of this dissertation is that an optimal portfolio can be built by making an extensive analysis of various stock in correlation with market index as a whole using Capital Asset Pricing Model as the basis whereby we can not only diversify the risk but maximize the overall return of the portfolio.

The dissertation starts with historical background and concepts involved in need for diversification, the systematic and unsystematic risks involved, the technical and fundamental analysis. Finally, shifting the focus on the historical background of CAPM, evolution of CAPM model and the basic concepts on which it is based upon.

The dissertation extends into analysis of CAPM in BSE Sensex and to interpret whether CAPM can be used as a true reflector of the returns as provided by the stocks over a period of time.The dissertation concludes with Strategic implication of CAPM and with the conclusions drawn from the analysis for building the optimum portfolio.

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Chapter 1

IntroductionMany modern financial applications such as portfolio construction and risk management, require estimates of the asset returns. The finance literature in the past paid less attention to the estimation. This lack of attention is due to two factors. First, there was limited computing technology to practically handle large amount of cross-sectional information for covariance estimation. Second, it was generally believed that in a mean-variance optimization process, compared to expected returns, covariance is more stable and causes fewer problems; hence it is less important to have good estimations for it. Recently, with development in both optimization and computational technologies and renewed interests in portfolio risk management, therehas been increasing attention on CAPM.

This dissertation studies the applicability of CAPM in Indian Stock market. The need for diversification arises from the concept of having higher returns with lower risk involved and for that return on equity has to be considered. The cost of capital DCF model was used. Since it had certain loopholes many models have been developed to calculate return on portfolio and stocks with CAPM being the earliest model. Since then models like Efficient Market hypothesis, three factor model have been developed but CAPM has still its stronghold for such estimation. Thus, it becomes imperative to analyze it as an estimator. In this study, we focus on that very aspect and try to evaluate its sustainability in Indian Stock market by undertaking an empirical study.

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1.1 Scope of the study

The dissertation consists of five essays. The first essay is an empirical study on the need of diversification, history of Capital asset pricing model. We contribute to the literature by providing an up-to-date analysis of both old and new estimation methods. We compare these methods using the conventional comparison criteria.

We need to find a more powerful measure to compare the performance of alternative models. For portfolio risk management purposes, we want a more robust assessment criterion where the risks of any portfolios can be measured. This leads to the second part of our thesis, where we propose to use the applicability of Capital Asset Pricing model in order to determine if this model can be used as a true reflector of the actual returns provided by the stocks considered.

Understanding the various dimensions of Portfolio Management

Need for building Optimal Portfolios

Use of CAPM as a means to determine the optimal Portfolio

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1.2 Objectives of the Study

The core idea behind undertaking the dissertation is to attain following objectives:-

Various Models have been developed over a period of time for the very purpose of calculating the “Return on Equity”. The earliest model was based on the concept of Cost of Capital. Since there were certain loopholes in this model, the first model for calculating return on Equity is considered to be developed by Markowitz. However, since model like Du Pont, Arbitrage Pricing theory, Three factor model have become more prominent this study has been undertaken to authenticate that CAPM is still one of the most important model for the analysis on return on equity and no analysis would be complete without it.

i. Study the concept of Portfolio Management with the focus on Capital Asset Pricing Model.

ii. To sketch the conceptual framework used for the analysis of Capital Asset Pricing Model.

iii. To highlight the relation and sustainability of Capital Asset pricing Model in Indian Stock Market by doing the analysis of top 30 companies of Bombay Stock Exchange during a period of 10 years

iv. To draw the conclusions and give recommendations about the applicability.

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1.3 Research Methodology

The cornerstones of my approach to study the Applicability of risk analysis in listed companies of NSE and recommending a sustainable roadmap for building a portfolio using Markowitz model.The study is related to obtaining a better estimation of the returns of a reasonably large number of stocks for portfolio risk management. To set the stage for our analysis, we examine the returns offered by companies . Next, as part of exploring the best way to examine the risk involved in different stocks, we calculated co-relation between these companies and finally studied the risk involved in all this exercise using Markowitz model.

Interactions:Extensive interactions were held with certain corporate, representatives from the banking and financial industry based in Delhi to have a better analysis of the subject.

Case study based approach:All through the text my endeavor has been to study Markowitz Model as case study and try and draw out how it has been applied to calculate Return and risk on Equity, which in turn has helped me analyze the sector in a better way.

Extensive Secondary Research:Applicability of Markowitz Model in Indian Stock Market is not extensively researched in India. Moreover empirical records of Markowitz Model are quite less. Models like discounted cash flow, Du Pont analysis, arbitrage pricing theory, three factor model are used. Hence, I have focused on CAPM and used it to determine as a means. I have relied to a large extent on the publications and reports published in the international domain. Along with that journals have been also considered. The data for empirical study is basically collected from the various software like Prowess etc. The additional information about individual stock performances likes returns have been collected from financial journals as well as by studying of the Annual reports of the companies. To ensure the relevance in the Indian markets, research based out of the emerging markets has been considered.

Conceptual Analysis:In order to lay out a roadmap for CAPM, it was necessary to analyze the conceptual framework. Hence, key concepts and bases with respect to CAPM have been analyzed.

1.4 The organization of the dissertation

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Following the introduction of the dissertation report in Chapter 1, the rest of the dissertation is organized in the following way.

Chapter 2 reviews the literature on the Capital Asset Pricing Model. It focuses on the portfolio management, evolution of portfolio management, history of CAPM Model, various risk involved, need for diversification and CAPM as model to diversify the portfolio, assumptions and limitations Along with this, the usefulness of CAPM is also factored in.

Chapter 3 conducts a comprehensive empirical analysis of estimating the return on equity of various stocks of BSE Sensex using the CAPM Model. We examine how much CAPM is applicable in real life and if CAPM is a true reflector of the market value as reflected in prices of Stocks. This chapter extends as a tool for finding if CAPM could be used as a strategic planning. These comparisons helps in finding the optimal portfolio management, where the returns are maximized and the risk diversified. In Chapter 4, we analyse the CAPM model as a whole robust optimal portfolio measurement means. This chapter draws the final implication of the objectives of the study and the concepts of CAPM and the inferences drawn from the empirical study. Finally, we conclude and describes potential future research of CAPM model in Portfolio Management.

1.5 Limitations of the Study

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The following dissertation has following limitations..

Using CAPM as the only model for determining the optimal portfolio.

Limiting the scope of Stock to blue chip companies or heavy weights only in which case the risk is already diversified and lesser risk factor involved thus a skewed result has high probability.

Time frame of data for analysis limited to a period of 10 years.

Chapter 212


Conceptual Framework of Capital Asset Pricing Model

Literature Review

Estimation of return on the asset returns plays an important role in both the theory and practice of modern portfolio analysis and financial risk management.

Markowitz's (1952) mean-variance portfolio optimization theory shows that we can construct optimal portfolios if accurate estimation of expected returns, variance and covariance of every asset could be obtained. Following the work of Markowitz, numerous studies have been searching for methods that can provide the best estimates. Therefore, there has been considerable progress in the design of optimal portfolios.

This chapter provides a brief review of the literature on estimating a return of an asset and portfolio as a whole with Capital Asset Pricing model as the basis.

2.1 Introduction to Portfolio Management

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Investing in securities such as shares, debentures, and bonds is profitable as well as exciting. It is indeed rewarding, but involves a great deal of risk and calls for scientific knowledge as well artistic skill. In such investments both rationale and emotional responses are involved. Investing in financial securities is now considered to be one of the best avenues for investing one savings while it is acknowledged to be one of the best avenues for investing one saving while it is acknowledged to be one of the most risky avenues of investment.

“It is rare to find investors investing their entire savings in a single security. Instead, they tend to invest in a group of securities. Such a group of securities is called portfolio” . Creation of a portfolio helps to reduce risk, without sacrificing returns. Portfolio management deals with the analysis of individual securities as well as with the theory and practice of optimally combining securities into portfolios. An investor who understands the fundamental principles and analytical aspects of portfolio management has a better chance of success.

Portfolio Management:

An investor considering investment in securities is faced with the problem of choosing from among a large number of securities and how to allocate his funds over this group of securities. Again he is faced with problem of deciding which securities to hold and how much to invest in each. The risk and return characteristics of portfolios. The investor tries to choose the optimal portfolio taking into consideration the risk return characteristics of all possible portfolios. As the risk return characteristics of individual securities as well as portfolios also change. This calls for periodic review and revision of investment portfolios of investors.

An investor invests his funds in a portfolio expecting to get good returns consistent with the risk that he has to bear. The return realized from the portfolio has to be measured and the performance of the portfolio has to be evaluated. It is evident that rational investment activity involves creation of an investment portfolio. Portfolio management comprises all the processes involved in the creation and maintenance of an investment portfolio. It deals specifically with the security analysis, portfolio analysis, portfolio selection, portfolio revision & portfolio evaluation. Portfolio management makes use of analytical techniques of analysis and conceptual theories regarding rational allocation of funds. Portfolio management is a complex process which tries to make investment activity more rewarding and less risky. The selection of portfolio depends upon the objectives of the investor.

2.2 SELECTION OF PORTFOLIO

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The selection of portfolio under different objectives are dealt subsequently Objectives and asset mix If the main objective is getting adequate amount of current income, sixty percent of the investment is made in debt instruments and remaining in equity. Proportion varies according to individual preference. Here the investor requires a certain percentage of growth as the income from the capital he has invested. The proportion of equity varies from 60 to 100 % and that of debt from 0 to 40 %. The debt may be included to minimize risk and to get tax exemption. It means that value of the investment made increases over the year. Investment in real estate can give faster capital appreciation but the problem is of liquidity. In the capital market, the value of the shares is much higher than the original issue price. Safety of principle and asset mix Usually, the risk adverse investors are very particular about the stability of principal. Generally old people are more sensitive towards safety.

Risk and return analysis

The traditional approach of portfolio building has some basic assumptions. An investor wants higher returns at the lower risk. But the rule of the game is that more risk, more return. So while making a portfolio the investor must judge the risk taking capability and the returns desired. Diversification Once the asset mix is determined and risk – return relationship is analyzed the next step is to diversify the portfolio. The main advantage of diversification is that the unsystematic risk is minimized.

2.3 Evolution of Portfolio Management

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Portfolio management is essentially a systematic method of maintaining one‘s investment efficiently. Many factors have contributed to the existence and development of the concept. In the early years of the century analyst used financial statements to find the value of the securities. The first to be analyzed using this was Railroad Securities of the USA. A booklet entitled ―The Anatomy of the Railroad was published by Thomas F. Woodlock in 1900. As the time progressed this method became very important in the investment field, although most of the writers adopted different ways to publish their data. They generally advocated the use of different ratios for this purpose. John Moody in his book ―The Art of wall Street Investing‖, strongly supported the use of financial ratios to know the worth of the investment. The proposed type of analysis later on became the ―common-size analysis.

The other major method adopted was the study of stock price movement with the help of price charts. This method later on was known as Technical Analysis. It evolved during 1900-1902 when Charles H. Dow, the founder of the Dow Jones and Co. presented his view in the series of editorials in the Wall Street Journal in USA. The advocates of technical analysis believed that stock prices movement is ordered and systematic and the definite pattern could be identified. There investment strategy was build around the identification of the trend and pattern in the stock price movement.

Another prominent author who supported the technical analysis was Ralph N. Elliot who published a book in the year 1938 titled ―The Wave Principle. After analyzing 75 years data of share price, he concluded that the market movement was quite orderly and followed a pattern of waves. His theory is known as Elliot Wave Theory. According to J.C. Francis the development of investment management can be traced chronologically through three different phases. First phase is known as Speculative Phase. Investment was not a wide spread activity, but a cake of few rich people. The process is speculative in nature. Investment management was an art and needed skills. Price manipulation was resorted to by the investors. During this time period pools and corners were used for manipulation. The result of this was the stock exchange crash in the year 1929. Finally the daring speculative ventures of investors were declared illegal in the US by the Securities Act of 1934. Second phase began in the year 1930. The phase was of professionalism. After coming up of the Securities Act, the investment industry began the process of upgrading its ethics, establishing standard practices and generating a good public image. As a result the investments market became safer place to invest and the people in different income group started investing. Investors began to analyze the security before investing. During this period the research work of Benjamin Graham and David L. Dood was widely publicized and publicly acclaimed. They published a book ―Security Analysis in 1934, which was highly sought after. There research work was considered first work in the field of security analysis and acted as the base for further study. They are considered as pioneers of security analysis as a discipline. Third phase was known as the scientific phase.

The foundation of modern portfolio theory was laid by Markowitz. His pioneering work on portfolio management was described in his article in the Journal of Finance in the year 1952 and subsequent books published later on. He tried to quantify the risk. He showed how the risk can be minimized through proper diversification of investment which required the creation of the portfolio. He provided technical tools for the analysis and selection of optimal portfolio. For his work he won the Noble Prize for

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Economics in the year 1990. The work of Markowitz was extended by the William Sharpe, John Linter and Jan Mossin through the development of the Capital Asset Pricing Model (CAPM). If we talk of the present the last two phases of Professionalism and Scientific Analysis are currently advancing simultaneously with investment in various financial instruments becoming safer, with proper knowledge to each and every investor.

2.4 Literature on Capital Asset Pricing Model

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The literature on estimating a return on portfolio is quite extensive. We focus our review on methods that use mostly historical stock return data but limited stock fundamental information such as the industry classifications in the estimation process.

A fundamental question in finance is how the risk of an investment should affect its expected return. The Capital Asset Pricing Model (CAPM) provided the first coherent framework for answering this question. The CAPM was developed in the early 1960s by William Sharpe (1964), Jack Treynor (1962), John Lintner (1965) and Jan Mossin (1966). The CAPM is based on the idea that not all risks should affect asset prices. In particular, a risk that can be diversified away when held along with other investments in a portfolio is, in a very real way, not a risk at all. The CAPM gives us insights about what kind of risk is related to return. This paper lays out the key ideas of the Capital Asset Pricing Model, places its development in a historical context, and discusses its applications and enduring importance to the field of finance. After all, stock and option markets had been in existence at least since 1602 when shares of the East India Company began trading in Amsterdam (de la Vega, 1688); and organized insurance markets had become well developed by the 1700s (Bernstein, 1996). By 1960, insurance businesses had for centuries been relying on diversification to spread risk. But despite the long history of actual risk-bearing and risk-sharing in organized financial markets, the Capital Asset Pricing Model was developed at a time when the theoretical foundations of decision making under uncertainty were relatively new and when basic empirical facts about risk and return in the capital markets were not yet known.

Rigorous theories of investor risk preferences and decision-making under uncertainty emerged only in the 1940s and 1950s, especially in the work of von Neumann and Morgenstern (1944) and Savage (1954). Portfolio theory, showing how investors can create portfolios of individual investments to optimally trade off risk versus return, was not developed until the early 1950s by Harry Markowitz (1952, 1959) and Roy (1952). Equally noteworthy, the empirical measurement of risk and return was in its infancy until the 1960s, when sufficient computing power became available so that researchers were able to collect, store and process market data for the purposes of scientific investigation. The first careful study of returns on stocks listed on the New York Stock Exchange was that of Fisher and Lorie (1964) in which they note: "It is surprising to realize that there have been no measurements of the rates of return on investments in common stocks that could be considered accurate and definitive." In that paper, Fisher and Lorie report average stock market returns over different holding periods since 1926, but not the standard deviation of those returns. They also do not report any particular estimate of the equity risk premium that is, the average amount by which the stock market outperformed risk-free investments although they do remark that rates of return on common stocks were "substantially higher than safer alternatives for which data are available."

Measured standard deviations of broad stock market returns did not appear in the academic literature until Fisher and Lorie (1968). Carefully constructed estimates of the equity risk premium did not appear until Ibbotson and Sinquefield (1976) published their findings on long-term rates of return. They found that over the period 1926 to 1974, the (arithmetic) average return on the Standard and Poor's 500 index was 10.9 percent per annum, and the excess return over U.S. Treasury bills was 8.8 percent per annum.

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The first careful study of the historical equity risk premium for UK stocks appeared in Dimson and Brealey (1978) with an estimate of 9.2 percent per annum over the period 1919-1977. In the 1940s and 1950s, prior to the development of the Capital Asset Pricing Model, the reigning paradigm for estimating expected returns presupposed that the return that investors would require (or the "cost of capital") of an asset depended primarily on the manner in which that asset was financed (for example, Bierman and Smidt, 1966). There was a "cost of equity capital" and a "cost of debt capital," and the weighted average of these based on the relative amounts of debt and equity financing represented the cost of capital of the asset. The costs of debt and equity capital were inferred from the long-term yields of those instruments. The cost of debt capital was typically assumed to be the rate of interest owed on the debt, and the cost of equity capital was backed out from the cash flows that investors could expect to receive on their shares in relation to the current price of the shares. A popular method of estimating the cost of equity this way was the Gordon and Shapiro (1956) model, in which a company's dividends are 1. These are arithmetic average returns. Ibbotson and Sinquefield (1976) were also the first to report the term premium on long-term bonds: 1.1 percent per annum average return in excess of Treasury bills over the period 1926-1974 assumed to grow in perpetuity at a constant rate g. In this model, if a firm's current dividend per share is D, and the stock price of the firm is P, then the cost of equity capital r is the dividend yield plus the dividend growth rate: r = D/P + g.i

From the perspective of modern finance, this approach to determining the cost of capital was anchored in the wrong place. At least in a frictionless world, the value of a firm or an asset more broadly does not depend on how it is financed, as shown by Modigliani and Miller (1958). This means that the cost of equity capital likely is determined by the cost of capital of the asset, rather than the other way around. Moreover, this process of inferring the cost of equity capital from future dividend growth rates is highly subjective. There is no simple way to determine the market's forecast of the growth rate of future cash flows, and companies with high dividend growth rates will be judged by this method to have high costs of equity capital. Indeed, the Capital Asset Pricing Model will show that there need not be any connection between the cost of capital and future growth rates of cash flows. In the pre-CAPM paradigm, risk did not enter directly into the computation of the cost of capital. The working assumption was often that a firm that can be financed mostly with debt is probably safe and is thus assumed to have a low cost of capital; while a firm that cannot support much debt is probably risky and is thus assumed to command a high cost of capital. These rules-of-thumb for incorporating risk into discount rates were ad hoc at best. As Modigliani and Miller (1958) noted: "No satisfactory explanation has yet been provided as to what determines the size of the risk [adjustment] and how it varies in response to changes in other variables."

In short, before the arrival of the Capital Asset Pricing Model, the question of how expected returns and risk were related had been posed, but was still awaiting an answer.

Diversification, Correlation and Risk

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The notion that diversification reduces risk is centuries old. In eighteenth-century English language translations of Don Quixote, Sancho Panza advises his master, "It is the part of a wise man to ... not venture all his eggs in one basket." According to Herbison (2003), the proverb "Do not keep all your eggs in one basket" actually appeared as far back as Torriano's (1666) Common Place of Italian Proverbs. However, diversification was typically thought of in terms of spreading your wealth across many independent risks that would cancel each other if held in sufficient number (as was assumed in the new ventures example). Harry Markowitz (1952) had the insight that, because of broad economic influences, risks across assets were correlated to a degree. As a result, investors could eliminate some but not all risk by holding a diversified portfolio. Markowitz wrote: "This presumption that the law of large numbers applies to a portfolio of securities, cannot be accepted. The returns from securities are too inter correlated. Diversification cannot eliminate all variance." Markowitz (1952) went on to show analytically how the benefits of diversification depend on correlation. The correlation between the returns of two assets measures the degree to which they fluctuate together. Correlation coefficients range between 1.0 and -1.0. When the correlation is 1.0, the two assets are perfectly positively correlated. They move in the same direction and in fixed proportions (plus a constant). In this case, the two assets are substitutes for one another. When the correlation is -1.0, the returns are perfectly negatively correlated meaning that when one asset goes up, the other goes down and in a fixed proportion (plus a constant). In this case, the two assets act to insure one another. When the correlation is zero, knowing the return on one asset does not help you predict the return on the other.

These are Harry Markowitz's important insights: 1) that diversification does not rely on individual risks being uncorrelated, just that they be imperfectly correlated; and 2) that the risk reduction from diversification is limited by the extent to which individual asset returns are correlated. If Markowitz were restating Sancho Panza's advice, he might say: It is safer to spread your eggs among imperfectly correlated baskets than to spread them among perfectly correlated baskets.ii

In finance, 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-diversifiablerisk(also known as systematic risk or market risk), often represented by the quantity beta (β) in the financial industry, as well as the expected return of the market and the expected return of a theoretical risk-free asset.

2.5 Background:

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http://en.wikipedia.org/wiki/Risk-free_interest_rate

http://en.wikipedia.org/wiki/Expected_return

http://en.wikipedia.org/wiki/Beta_(finance)

http://en.wikipedia.org/wiki/Market_risk

http://en.wikipedia.org/wiki/Systematic_risk

http://en.wikipedia.org/wiki/Risk

http://en.wikipedia.org/wiki/Diversification_(finance)

http://en.wikipedia.org/wiki/Portfolio_(finance)

http://en.wikipedia.org/wiki/Asset

http://en.wikipedia.org/wiki/Rate_of_return

http://en.wikipedia.org/wiki/Finance


The model was introduced by Jack Treynor (1961, 1962), William Sharpe (1964), John Lintner (1965) and Jan Mossin (1966) independently, building on the earlier work of Harry Markowitz on diversification and modern portfolio theory. One of the fundamental tenants in financial theory is the CAPM as developed by Sharpe (1964), Lintner (1965) and Black (1972). The CAPM’s impact over the decades on the financial community has led several authors inclusive of Fama and French (2004) to suggest that the development of the CAPM marks “the birth of Asset Pricing models”. The CAPM is an ex-ante, static (one period) model. The model’s main prediction is that a market portfolio of invested wealth is mean-variance efficient resulting in a linear cross-sectional relationship between mean excess returns and exposures to the market factor. The model draws on the portfolio theory as developed by Harry Markowitz (1959).

Estimation of the CAPM and the Security Market Line (purple) for the Dow Jones Industrial Average over the last 3 years for monthly data.

The CAPM is a model for pricing an individual security or a portfolio. For individual securities, we make use of the security market line(SML) and its relation to expected return and systematic risk (beta) to show how the market must price individual securities in relation to their security risk class. The SML enables us to calculate the reward-to-risk ratio for any security in relation to that of the overall market. Therefore, when the expected rate of return for any security is deflated by its beta coefficient, the reward-to-risk ratio for any individual security in the market is equal to the market reward-to-risk ratio, thus:

The market reward-to-risk ratio is effectively the market risk premium and by rearranging the above equation and solving for E(Ri), we obtain the Capital Asset Pricing Model (CAPM).

where:

is the expected return on the capital asset

is the risk-free rate of interest such as interest arising from government bonds (the beta) is the sensitivity of the expected excess asset returns to the expected excess

market returns, or also ,

is the expected return of the market

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http://en.wikipedia.org/wiki/Sensitivity_and_specificity

http://en.wikipedia.org/wiki/Beta_(finance)



http://en.wikipedia.org/wiki/Security_market_line

http://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

http://en.wikipedia.org/wiki/Modern_portfolio_theory


http://en.wikipedia.org/wiki/Harry_Markowitz

http://en.wikipedia.org/wiki/Harry_Markowitz

http://en.wikipedia.org/wiki/Jan_Mossin

http://en.wikipedia.org/wiki/John_Lintner

http://en.wikipedia.org/wiki/John_Lintner

http://en.wikipedia.org/wiki/William_Forsyth_Sharpe

http://en.wikipedia.org/wiki/Jack_L._Treynor

http://en.wikipedia.org/wiki/File:CAPM-SML.svg


is sometimes known as the market premium or risk premium (the difference between the expected market rate of return and the risk-free rate of return).

Note 1: the expected market rate of return is usually estimated by measuring the Geometric Average of the historical returns on a market portfolio (e.g. S&P 500, BSE Sensex ).Note 2: the risk free rate of return used for determining the risk premium is usually the arithmetic average of historical risk free rates of return and not the current risk free rate of return.

The CAPM model assumes a linear relationship between the expected return in a risky asset and its β and further assumes that β is an applicable and sufficient measure of risks that captures the cross section of average returns, that is, the model assumes that assets can only earn a high average return if they have a high market β. β drives average returns because β measures how much the inclusion of additional stock to a well diversified portfolio increases the inherent risk and volatility of the portfolio.

2.6 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.

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http://en.wikipedia.org/wiki/Security_market_line

http://en.wikipedia.org/wiki/Geometric_Average

http://en.wikipedia.org/wiki/Geometric_Average


The relationship between β and required return is plotted on the securities market line (SML) which shows expected return as a function of β. 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.

Once the expected/required rate of return, E(Ri), 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.

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 observed price is higher than the CAPM valuation, then the asset is overvalued (and undervalued 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 t is , a higher expected return than what CAPM suggests indicates that Pt is too low (the asset is currently undervalued), assuming that at time t + 1 the asset returns to the CAPM suggested price.

The CAPM returns the asset-appropriate required return or discount rate—i.e. the rate at which future cash flows produced by the asset should be discounted given that asset's relative riskiness. Betas exceeding one signify more than average "riskiness"; betas below one indicate lower than average. Thus, a more risky stock will have a higher beta and will be discounted at a higher rate; less sensitive stocks will have lower betas and be discounted at a lower rate. Given the accepted concave utility function, the CAPM is consistent with intuition—investors (should) require a higher return for holding a more risky asset.

Since beta reflects asset-specific sensitivity to non-diversifiable, i.e. market risk, the market as a whole, by definition, has a beta of one. Stock market indices are frequently used as local proxies for the market—and in that case (by definition) have a beta of one. An investor in a large, diversified portfolio (such as a mutual fund), therefore, expects performance in line with the market.

2.7 Risk & Diversification

23

http://en.wikipedia.org/wiki/Mutual_fund

http://en.wikipedia.org/wiki/Risk

http://en.wikipedia.org/wiki/Utility_function


The risk of a portfolio comprises systematic risk, also known as undiversifiable risk, and unsystematic risk which is also known as idiosyncratic risk or diversifiable risk. Systematic risk refers to the risk common to all securities—i.e. market risk. Unsystematic risk is the risk associated with individual assets. Unsystematic risk can be diversified away to smaller levels by including a greater number of assets in the portfolio (specific risks "average out"). The same is not possible for systematic risk within one market. Depending on the market, a portfolio of approximately 30-40 securities in developed markets such as UK or US will render the portfolio sufficiently diversified such that risk exposure is limited to systematic risk only. In developing markets a larger number is required, due to the higher asset volatilities.

A rational investor should not take on any diversifiable risk, as only non-diversifiable risks are rewarded within the scope of this model. Therefore, the required return on an asset, that is, the return that compensates for risk taken, must be linked to its riskiness in a portfolio context - i.e. its contribution to overall portfolio riskiness - as opposed to its "stand alone riskiness." In the CAPM context, portfolio risk is represented by higher variance i.e. less predictability. In other words the beta of the portfolio is the defining factor in rewarding the systematic exposure taken by an investor.

The (Markowitz) efficient frontier. CAL stands for the capital allocation line.

The CAPM assumes that the risk-return profile of a portfolio can be optimized—an optimal portfolio displays the lowest possible level of risk for its level of return. Additionally, since each additional asset introduced into a portfolio further diversifies the portfolio, the optimal portfolio must comprise every asset, (assuming no trading costs) with each asset value-weighted to achieve the above (assuming that any asset is infinitely divisible). All such optimal portfolios, i.e., one for each level of return, comprise the efficient frontier.Because the unsystematic risk is diversifiable, the total risk of a portfolio can be viewed as beta.

2.8 Market Portfolio

An investor might choose to invest a proportion of his or her wealth in a portfolio of risky assets with the remainder in cash—earning interest at the risk free rate (or indeed may borrow money to fund his or her purchase of risky assets in which case there is a negative cash weighting). Here,

24

http://en.wikipedia.org/wiki/Beta_coefficient


http://en.wikipedia.org/wiki/Infinite_divisibility

http://en.wikipedia.org/wiki/Capital_allocation_line

http://en.wikipedia.org/wiki/Efficient_frontier

http://en.wikipedia.org/wiki/Variance

http://en.wikipedia.org/wiki/Return_on_investment


http://en.wikipedia.org/wiki/Market_risk

http://en.wikipedia.org/wiki/Unsystematic_risk


http://en.wikipedia.org/wiki/Portfolio_(finance)

http://en.wikipedia.org/wiki/File:Markowitz_frontier.jpg


the ratio of risky assets to risk free asset does not determine overall return—this relationship is clearly linear. It is thus possible to achieve a particular return in one of two ways:

1. By investing all of one's wealth in a risky portfolio,2. or by investing a proportion in a risky portfolio and the remainder in cash (either

borrowed or invested).

For a given level of return, however, only one of these portfolios will be optimal (in the sense of lowest risk). Since the risk free asset is, by definition, uncorrelated with any other asset, option 2 will generally have the lower variance and hence be the more efficient of the two.This relationship also holds for portfolios along the efficient frontier: a higher return portfolio plus cash is more efficient than a lower return portfolio alone for that lower level of return. For a given risk free rate, there is only one optimal portfolio which can be combined with cash to achieve the lowest level of risk for any possible return. This is the market portfolio.

2.9 ASSUMPTIONS OF CAPM:-

All investors: Aim to maximize economic utilities.

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http://en.wikipedia.org/wiki/Market_portfolio

http://en.wikipedia.org/wiki/Correlation


Are rational and risk-averse.

Are broadly diversified across a range of investments.

Are price takers, i.e., they cannot influence prices.

Can lend and borrow unlimited amounts under the risk free rate of interest.

Trade without transaction or taxation costs.

Deal with securities that are all highly divisible into small parcels.

Assume all information is available at the same time to all investors.

2.10 LIMITATIONS OF THE MODEL

The model assumes that either asset returns are (jointly) normally distributed random variables or that investor’s employ a quadratic form of utility. It is however frequently observed that returns in equity and other markets are not normally

26

http://en.wikipedia.org/wiki/Random

http://en.wikipedia.org/wiki/Normal_distribution

http://en.wikipedia.org/wiki/Normal_distribution


distributed. As a result, large swings (3 to 6 standard deviations from the mean) occur in the market more frequently than the normal distribution assumption would expect.

The model assumes that the variance of returns is an adequate measurement of risk. This might be justified under the assumption of normally distributed returns, but for general return distributions other risk measures (like coherent risk measures) will likely reflect the investors' preferences more adequately. Indeed risk in financial investments is not variance in itself, rather it is the probability of losing: it is asymmetric in nature.

The model assumes that all investors have access to the same information and agree about the risk and expected return of all assets (homogeneous expectations assumption).

The model assumes that the probability beliefs of investors match the true distribution of

returns. A different possibility is that investors' 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 (2001).

The model does not appear to adequately explain the variation in stock returns. Empirical studies show that low beta stocks may offer higher returns than the model would predict. Some data to this effect was presented as early as a 1969 conference in Buffalo, New York in a paper by Fischer Black, Michael Jensen, and Myron Scholes. Either that fact is itself rational (which saves the efficient-market hypothesis but makes CAPM wrong), or it is irrational (which saves CAPM, but makes the EMH wrong – indeed, this possibility makes volatility arbitrage a strategy for reliably beating the market).

The model assumes that given a certain expected return investors will prefer lower risk (lower variance) to higher risk and conversely given a certain level of risk will prefer higher returns to lower ones. It does not allow for investors who will accept lower returns for higher risk. Casino gamblers clearly pay for risk, and it is possible that some stock traders will pay for risk as well.

The model assumes that there are no taxes or transaction costs, although this assumption may be relaxed with more complicated versions of the model.

The market portfolio consists of all assets in all markets, where each asset is weighted by its market capitalization. This assumes no preference between markets and assets for individual investors, and that investors choose assets solely as a function of their risk-return profile. It also assumes that all assets are infinitely divisible as to the amount which may be held or transacted.

The market portfolio should in theory include all types of assets that are held by anyone as an investment (including works of art, real estate, human capital...) In practice, such a market portfolio is unobservable and people usually substitute a stock index as a proxy for the true market portfolio. Unfortunately, it has been shown that this substitution is not innocuous and can lead to false inferences as to the validity of the CAPM, and it has been

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http://en.wikipedia.org/wiki/Problem_gambling

http://en.wikipedia.org/wiki/Volatility_arbitrage

http://en.wikipedia.org/wiki/Efficient-market_hypothesis

http://en.wikipedia.org/wiki/Myron_Scholes

http://en.wikipedia.org/wiki/Michael_Jensen

http://en.wikipedia.org/wiki/Fischer_Black

http://en.wikipedia.org/wiki/Buffalo,_New_York

http://en.wikipedia.org/wiki/Buffalo,_New_York

http://en.wikipedia.org/wiki/David_Hirshleifer

http://en.wikipedia.org/wiki/David_Hirshleifer

http://en.wikipedia.org/wiki/Behavioral_finance

http://en.wikipedia.org/wiki/Coherent_risk_measure


said that due to the inobservability of the true market portfolio, the CAPM might not be empirically testable. This was presented in greater depth in a paper by Richard Roll in 1977, and is generally referred to as Roll's critique.

The model assumes just two dates, so that there is no opportunity to consume and

rebalance portfolios repeatedly over time. The basic insights of the model are extended and generalized in the intertemporal CAPM (ICAPM) of Robert Merton, and the consumption CAPM (CCAPM) of Douglas Breeden and Mark Rubinstein.

CAPM assumes that all investors will consider all of their assets and optimize one portfolio. This is in sharp contradiction with portfolios that are held by individual investors: humans tend to have fragmented portfolios or, rather, multiple portfolios: for each goal one portfolio — see behavioral portfolio theory and Maslowian Portfolio Theory.

2.11 SUMMARY

The Capital Asset Pricing Model is a fundamental contribution to our understanding of the determinants of asset prices. The CAPM tells us that ownership of assets by diversified investors lowers their expected returns and raises their prices. Moreover, investors who hold undiversified portfolios are likely to be taking risks for which they are not being rewarded. As a result of the model, and despite its mixed empirical performance, we now think differently about the relationship between expected returns and risk; we think differently about how investors should allocate their investment portfolios; and we think differently about questions such as performance measurement and capital budgeting.

Chapter 3

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http://en.wikipedia.org/wiki/Maslowian_Portfolio_Theory

http://en.wikipedia.org/wiki/Maslowian_Portfolio_Theory

http://en.wikipedia.org/wiki/Behavioral_portfolio_theory

http://en.wikipedia.org/wiki/Roll's_critique

http://en.wikipedia.org/wiki/Richard_Roll


Capital Asset Pricing Model: Conceptual ResearchThere has been a lot of theoretical research already undertaken on Capital Asset Pricing Model. This dissertation throws a brief light on the various aspects that have been covered in the research undertaken till now.

3.1 Introduction & Background of Research

While relationships described by the CAPM have been the context of numerous empirical studies by many academics, its use in many present day applications by fund managers and in finance

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based course curricula, provides an insight on the significance of this finance model. Fama and French (2000) summarize the popularity of the CAPM by their statement:

“The attraction of the CAPM is that it offers powerful and intuitively pleasing predictions about how to measures risk and the relation between expected return and risk.”

Fama and French (2000) also offer their opinion on its relevance: “Unfortunately the empirical record of the model is poor – poor enough to invalidate the way it is used in applications.”

Whether the basic CAPM or one of its multifactor extensions is the "correct" model of asset prices is ultimately an empirical question, one that is discussed in detail by Fama and French in their companion paper in this journal. Initial tests of the CAPM by Black, Jensen and Scholes (1972) and Fama and MacBeth (1973) supported the theory in that high beta stocks were found to have had higher returns than low beta stocks. However, the relationship between beta and average returns was not as steep as indicated by the theoretical Securities Market Line. Since this early work, a vast body of research has looked for additional risk factors that affect expected returns. Most notably, Fama and French (1992) find that adding a "value" factor and a "size" factor (in addition to the overall market) greatly improves upon the explanatory power of the CAPM. The pervasiveness of these findings in follow-up research across time and other countries provides strong evidence that more than one systematic risk factor is at work in determining asset prices. However, the value and size factors are not explicitly about risk; at best, they are proxies for risk. For example, size per se cannot be a risk factor that affects expected returns, since small firms would then simply combine to form large firms.

Another criticism of the Fama-French findings is that their value effect is based on giving equal weight to small and large companies and is much stronger than observed in capitalization-weighted value indexes. Until the risks that underlie the Fama-French factors are identified, the forecast power of their model will be in doubt and the applications will be limited.

During the 1980’s several studies resulted in the identification of additional factors that provide explanatory power other than β for average stock returns. Variables that have no special standing in asset pricing theory were shown to have reliable power in explaining the cross section of returns (these variables are referred to as anomalies by Fama and French (1993, 1996)). Banz (1981) finds that Market Equity (ME) adds to the cross section of expected returns provided by the market β. Basu (1983) finds that low earnings-price ratios (E/P) stocks help explain the cross section of US stocks returns while high (E/P) stocks experiencing lower returns could be explained by the CAPM. DeBondt and Thaler (1985) find that stocks with abnormally low long term returns (average returns in three years) experience abnormally high long term future returns (average returns in the next three years) and vice versa. Bhandari (1988) finds a positive relationship between leverage and the cross section of average return. Rosenberg, Reid and Lanstein (1985) find a positive relationship between the average return and the ratio of a firm’s book value to market equity (BE/ME). Lakonishok, Sheifer and Vishny (1994) find a strong positive relationship between average returns and BE/ME and cashflow/price ratio (C/P). These relationships could not be explained by the CAPM.

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One of the major empirical arguments against the CAPM model is presented by Fama and French (1992). They find that the cross section of average equity returns in the US market shows little statistical relation to the βs of the original CAPM model. The authors evaluate the joint roles of the market β, firm Size (ME), (E/P), financial leverage and BE/ME in the cross section of average returns on the New York Stock Exchange (NYSE), American Stock Exchange (AMEX), and National Association of Securities Dealers Automated Quotations (NASDAQ) stocks. They find that the Size and BE/ME variables capture the cross sectional variation in average stock returns associated and conclude that the CAPM model is violated in its predication of a cross sectional relationship between mean excess returns and exposures to the market factor. Fama and French (1993) find that five (5) common risk factors explain the returns in both stocks and bonds. In testing the relationship between risk factors and stocks returns, the authors use the Black, Jensen and Scholes (1972) time series regression model to identify these factors. They find that two (2) factors, namely; firm Size and BE/ME portfolios explain the differences in the average cross section returns of stocks. Fama and French (1996) also observe that abnormal patterns of asset returns experienced during the 1980’s and 1990’s could not be explained by the CAPM but are however due to mis-specification in the expected returns model. They find that two other variables, SMB (Small Minus Big - the Size proxy) and HML (High Minus Low - the BE/ME proxy), inclusive of the market factor, explains significant return patterns on Lakonishok, Shleifer, and Vishny (1994) portfolios. The resultant model is being coined the Fama and French Three Factor Model (TFM) in financial literature.

3.2 Portfolio Theory, Riskless Lending and Borrowing and Fund Separation

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To arrive at the CAPM, we need to examine how imperfect correlation among asset returns affects the investor's tradeoff between risk and return. While risks combine nonlinearly (because of the diversification effect), expected returns combine linearly. That is, the expected return on a portfolio of investments is just the weighted average of the expected returns of the underlying assets.

Imagine two assets with the same expected return and the same standard deviation of return. By holding both assets in a portfolio, one obtains an expected return on the portfolio that is the same as either one of them, but a portfolio standard deviation that is lower than any one of them individually. Diversification thus leads to a reduction in risk without any sacrifice in expected return. Generally, there will be many combinations of assets with the same portfolio expected return but different portfolio risk; and there will be many combinations of assets with the same portfolio risk but different portfolio expected return. Using optimization techniques, we can compute what Markowitz coined the "efficient frontier." For each level of expected return, we can solve for the portfolio combination of assets that has the lowest risk. Or for each level of risk, we can solve for the combination of assets that has the highest expected return.

The efficient frontier consists of the collection of these optimal portfolios, and each investor can choose which of these best matches their risk tolerance. The initial development of portfolio theory assumed that all assets were risky. James Tobin (1958) showed that when investors can borrow as well as lend at the risk-free rate, the efficient frontier simplifies in an important way. (A "risk-free" instrument pays a fixed real return and is default free. U.S. Treasury bonds that adjust automatically with inflation called Treasury inflation-protected instruments, or TIPS and short-term U.S. Treasury bills are considered close approximations of risk-free instruments.) To see how riskless borrowing and lending affects investors' decision choices, consider investing in the following three instruments: risky assets M and H, and the riskless asset, where the expected returns and risks of the assets. Suppose first that you had the choice of investing all of your wealth in just one of these assets. Which would you choose? The answer depends on your risk tolerance.

You would choose the riskless asset has no risk but also the lowest expected return. You would choose to lend at the risk-free rate if you had a very low tolerance for risk. An Asset may have an intermediate risk and expected return, and you would choose this asset if you had a moderate tolerance for risk. Suppose next that you can borrow and lend at the risk-free rate,that you wish to invest some of your wealth and the balance in riskless lending or borrowing.iii

3.3 Capital Asset Pricing Model

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The rule for improving the Sharpe Ratio of a portfolio allows us to derive the Capital Asset Pricing Model in a straightforward and intuitive way. We begin with four assumptions. First, investors are risk averse and evaluate their investment portfolios using the Capital Asset Pricing Model The rule for improving the Sharpe Ratio of a portfolio allows us to derive the Capital Asset Pricing Model in a straightforward and intuitive way.

We begin with four assumptions.

Investors are risk averse and evaluate their investment portfolios solely in terms of expected return and standard deviation of return measured over the same single holding period.

Capital markets are perfect in several senses: all assets are infinitely divisible; there are no transactions costs, short selling restrictions or taxes; information is costless and available to everyone; and all investors can borrow and lend at the risk-free rate.

Investors all have access to the same investment opportunities.

Investors all make the same estimates of individual asset expected returns, standard deviations of return and the correlations among asset returns.

These assumptions represent a highly simplified and idealized world, but are needed to obtain the CAPM in its basic form. The model has been extended in many ways to accommodate some of the complexities manifest in the real world. But under these assumptions, given prevailing prices, investors all will determine the same highest Sharpe Ratio portfolio of risky assets. Depending on their risk tolerance, each investor will allocate a portion of wealth to this optimal portfolio and the remainder to risk-free lending or borrowing. Investors all will hold risky assets in the same relative proportions. For the market to be in equilibrium, the price (that is, the expected return) of each asset must be such that investors collectively decide to hold exactly the supply of the asset. If investors all hold risky assets in the same proportions, those proportions must be the proportions in which risky assets are held in the market portfolio the portfolio comprised of all available shares of each risky asset. In equilibrium, therefore, the portfolio of risky assets with the highest Sharpe Ratio must be the market portfolio. If the market portfolio has the highest attainable Sharpe Ratio, there is no way to obtain a higher Sharpe Ratio by holding more or less of any one asset.

This formula is the one that Sharpe, Treynor, Lintner and Mossin successfully set out to find. It is the relationship between expected return and risk that is consistent with investors behaving according to the prescriptions of portfolio theory. If this rule does not hold, then investors will be able to outperform the market (in the sense of obtaining a higher Sharpe Ratio) by applying the portfolio improvement rule, and if sufficiently many investors do this, stock prices will adjust to the point where the CAPM becomes true. Another way of expressing the CAPM equation is

Sharpe Ratio of Asset S= p X Sharpe Ratio of the Market Portfolio

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In other words, in equilibrium, the Sharpe Ratio of any asset is no higher than the Sharpe Ratio of the market portfolio (since p < 1). Moreover, assets having the same correlation with the market portfolio will have the same Sharpe Ratio. The Capital Asset Pricing Model tells us that to calculate the expected return of a stock, investors need know two things: the risk premium of the overall equity market (assuming that equities are the only risky assets) and the stock's beta versus the market. The stock's risk premium is determined by the component of its return that is perfectly correlated with the market that is, the extent to which the stock is a substitute for investing in the market. The component of the stock's return that is uncorrelated with the market can be diversified away and does not command a risk premium.

The Capital Asset Pricing Model has a number of important implications:-

First, perhaps the most striking aspect of the CAPM is what the expected return of an asset does not depend on. In particular, the expected return of a stock does not depend on its stand-alone risk. It is true that a high beta stock will tend to have a high stand-alone risk because a portion of a stock's stand-alone risk is determined by its beta, but a stock need not have a high beta to have a high stand-alone risk. A stock with high stand-alone risk therefore will only have a high expected return to the extent that its stand-alone risk is derived from its sensitivity to the broad stock market.

Second, beta offers a method of measuring the risk of an asset that cannot be diversified away. We saw earlier that any risk measure for determining expected returns would have to satisfy the requirement that the risk of a portfolio is the weighted average of the risks of the holdings in the portfolio. Beta satisfies this requirement. For example, if two stocks have market betas of 0.8 and 1.4, respectively, then the market beta of a 50/50 portfolio of these stocks is 1.1, the average of the two stock betas. Moreover, the capitalization weighted average of the market betas of all stocks is the beta of the market versus itself. The average stock therefore has a market beta of 1.0. On a graph where the risk of an asset as measured by beta is on the horizontal axis and return is on the vertical axis, all securities lie on a single line the so-called Securities Market Line. If the market is in equilibrium, all assets must lie on this line. If not, investors will be able to improve upon the market portfolio and obtain a higher Sharpe Ratio. In contrast, presented earlier measured risk on the horizontal axis as stand-alone risk, the standard deviation of each stock, and so stocks were scattered over the diagram. But remember that not all of the stand-alone risk of an asset is priced into its expected return, just that portion of its risk, pas, that is correlated with the market portfolio.

Third, in the Capital Asset Pricing Model, a stock's expected return does not depend on the growth rate of its expected future cash flows. To find the expected return of a company's shares, it is thus not necessary to carry out an extensive financial analysis of the company and to forecast its future cash flows. According to the CAPM, all we need to know about the specific company is die beta of its shares, a parameter that is usually much easier to estimate than the expected future cash flows of the firm.iv

3.4 Is CAPM Useful

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The Capital Asset Pricing Model is an elegant theory with profound implications for asset pricing and investor behavior. But how useful is the model given the idealized world that underlies its derivation. There are several ways to answer this question.

First, we can examine whether real world asset prices and investor portfolios conform to die predictions of the model, if not always in a strict quantitative sense, and least in a strong qualitative sense.

Second, even if the model does not describe our current world particularly well, it might predict future investor behavior for example, as a consequence of capital market frictions being lessened through financial innovation, improved regulation and increasing capital market integration.

Third, the CAPM can serve as a benchmark for understanding the capital market phenomena that cause asset prices and investor behavior to deviate from die prescriptions of the model. Suboptimal Diversification Consider the CAPM prediction that investors all will hold the same (market) portfolio of risky assets. One does not have to look far to realize that investors do not hold identical portfolios, which is not a surprise since taxes alone will cause idiosyncratic investor behavior.

On one hand, popular index funds make it possible for investors to obtain diversification at low cost. On the other hand, many workers hold concentrated ownership of company stock in employee retirement savings plans and many executives hold concentrated ownership of company stock options. Common explanations are that obtaining broad diversification can be costly, in terms of direct expenses and taxes, and that investors are subject to behavioral biases and lack of sophistication. None of these reasons, if valid, would mean that the CAPM is not useful. The CAPM tells us that investors pay a price for being undiversified in that they are taking risks for which they are not being compensated. Thus, there exists the potential for port? folio improvement, which in turn creates opportunities for investor education and financial innovation. Indeed, foreign ownership of equities in many countries has more than doubled over the last 20 years, most likely due to the increased availability of low-cost vehicles to invest globally and greater investor appreciation of the need for diversification. Investors today seem to be much better diversified than in decades past, a trend that appears likely to continue.

Performance Measurement

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One of the earliest applications of the Capital Asset Pricing Model was to performance measurement of fund managers. Consider two funds, A and B, that are actively managed in the hope of outperforming the market. Suppose that the funds obtained returns of 12 percent and 18 percent, respectively, during a period when the risk-free rate was 5 percent and the overall market returned 15 percent.

Assume further that the standard deviation of funds A and B were 40 percent per annum and 30 percent per annum, respectively. Which fund had the better performance. At first glance, fund A had greater risk and a lower return than fund B, so fund B would appear to have been the better performing fund. However, we know from the CAPM that focusing on stand-alone risk is misleading if investors can hold diversified portfolios. To draw a firmer conclusion, we need to know how these funds are managed: Suppose that fund A consists of a high-risk but "market-neutral" portfolio that has long positions in some shares and short positions in others, with a portfolio beta of zero. Fund B, on the other hand, invests in selected high beta stocks, with a portfolio beta of 1.5. Instead of investing in funds A and/or B, investors could have held corre sponding mimicking or "benchmark" portfolios. For fund A, since its beta is zero, the benchmark portfolio is an investment in the risk-free asset; for fund B, the benchmark is a position in the market portfolio leveraged 1.5:1 with borrowing at the risk-free rate. The benchmark portfolios respectively would have returned 5 percent and 20 percent (= 5 percent + 1.5 X (15 percent 5 percent)). Fund A thus outperformed its benchmark by 7 percent, while fund B underperformed its benchmark by 2 percent.

In terms of the CAPM framework, funds A and B had alphas of 7 percent and 2 percent, respectively, where alpha is the difference between a fund's performance and that predicted given the beta of the fund. Appropriately risk adjusted, fund A's performance (alpha = 7 percent) exceeded that of fund B (alpha = 2 percent). An investor who held the market portfolio would, at the margin, have obtained a higher return for the same risk by allocating money to fund A rather than to fund B.

The key idea here is that obtaining high returns by owning high beta stocks does not take skill, since investors can passively create a high beta portfolio simply through a leveraged position in the market portfolio. Obtaining high returns with low beta stocks is much harder, however, since such performance cannot be replicated with a passive strategy. Investors therefore need to assess performance based on returns that have been appropriately risk adjusted. The CAPM and Discounted Cash Flow Analysis According to the CAPM, the appropriate discount rate for valuing the expected future cash flows of a company or of a new investment project is determined by the risk-free rate, the market risk premium and the beta versus the market of the company or project. Accuracy in estimating these parameters matters greatly for real world decisionmaking since, for long-dated cash flows, an error in the discount rate is magnified manyfold when calculating the net present value. Beta is usually estimated with use of linear regression analysis applied to historical stock market returns data. Beta can in many circumstances be accurately measured this way even over a relatively short period of time, provided that there is sufficient high-frequency data. When die company or project being valued is not publicly traded or there is no relevant return history, it is customary to infer beta from comparable entities whose betas can be estimated.

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The hardest of all parameters to estimate is usually the market risk premium. The historical risk premium is estimated from the average of past returns and, unlike variance-related measures like beta, average returns are very sensitive to the beginning and ending level of stock prices. The risk premium must therefore be measured over long periods of time, and even this may not be sufficient if the risk premium varies over time. None of these measurement questions poses a problem for the CAPM per se, however. The market risk premium is common to all models of cash flow valuation, and its estimation needs to be performed regardless of the difficulty of the task.

Provided that the CAPM is the "right" model, beta too needs to be estimated, irrespective of difficulty. Extensions of the CAPM The Capital Asset Pricing Model has been extended in a variety of ways. Some of the best-known extensions include allowing heterogeneous beliefs; eliminating the possibility of risk-free lending and borrowing; having some assets be nonmarketable; allowing for multiple time periods and investment opportunities that change from one period to the next; extensions to international investing ; and employing weaker assumptions by relying on arbitrage pricing. In most extensions of the CAPM, no single portfolio of risky assets is optimal for everyone. Rather, investors allocate their wealth differentially among several risky portfolios, which across all investors aggregate to the market portfolio. To illustrate, consider the International Capital Asset Pricing Model. This model takes into account that investors have consumption needs particular to the country in which they are resident. Thus, British investors will worry about the purchasing power of pounds while American investors worry about the purchasing power of dollars, which means that British and American investors will differently assess the incremental contribution that any particular asset makes to portfolio risk. As a result, they will hold somewhat different portfolios.

In the basic CAPM, investors care about only one risk factor the overall market. In this international version of the model, they are also concerned about real currency fluctuations. This insight leads to a model of expected returns involving not only the beta of an asset versus the overall market, but also the betas of the asset versus currency movements and any other risk that is viewed differently by different investor segments. Almost all variants of the CAPM have a multi-beta expression. v

Chapter 437


Core Chapter: Use of CAPM in BSE Sensex: An Empirical Study

The objective of this chapter is to make a comprehensive research on the application of CAPM as a true reflector of returns as shown by the stock over a period of time and not just he stock but the returns of the portfolio.

In this particular case, the top heavy weights of BSE Sensex (30 Companies) from diversified sectors are considered and their return over a period of time is calculated using Risk free return, Risk Premium and Beta( Correlation of the market risk and security risk).

4.1 EMPIRICAL STUDY OF APPLICABILITY OF CAPM ON BSE SENSEX

38


Table 1:Risk Free Rate

Market Rate

Risk Premium BETA CAPM

364 T- Bill Rate Cost of Equity

Bajaj Auto Ltd.

2000 10.10% -10.10% 0.91 0.90900%2001 7.35% -7.35% 0.91 0.66150%2002 5.62% -5.62% 0.91 0.50580%2003 4.55% -4.55% 0.91 0.40950%2004 5.79% -5.79% 0.91 0.52110%2005 5.60% -5.60% 0.91 0.50400%2006 7.22% -7.22% 0.91 0.64980%2007 6.07% -6.07% 0.91 0.54630%2008 7.06% 20.05% 12.99% 0.91 18.88090%2009 3.24% 279.44% 276.20% 0.91 254.58200%2010 7.68% 60.48% 52.80% 0.91 55.72757%


Market Rate



Bharat Heavy

39


Electricals Ltd

2000 10.10% 0.82% -9.28% 1.01 0.727200%2001 7.35% 5.63% -1.72% 1.01 5.612800%2002 5.62% 22.04% 16.42% 1.01 22.204200%2003 4.55% 124.77% 120.22% 1.01 125.972200%2004 5.79% 39.88% 34.09% 1.01 40.220900%2005 5.60% 42.80% 37.20% 1.01 43.172000%2006 7.22% 20.39% 13.17% 1.01 20.521700%2007 6.07% 79.70% 73.63% 1.01 80.436300%2008 7.06% 5.62% -1.44% 1.01 5.605600%2009 3.24% -2.65% -5.89% 1.01 -2.708900%2010 7.68% -19.86% -27.54% 1.01 -20.135352%


Market Rate



Bharti Airtel Ltd.

2000 10.10% -10.10% 0.68 3.23200%2001 7.35% -7.35% 0.68 2.35200%2002 5.62% -51.66% -57.28% 0.68 -33.33040%2003 4.55% 286.06% 281.51% 0.68 195.97680%2004 5.79% 82.62% 76.83% 0.68 58.03440%2005 5.60% 19.52% 13.92% 0.68 15.06560%2006 7.22% 35.43% 28.21% 0.68 26.40280%2007 6.07% 11.01% 4.94% 0.68 9.42920%2008 7.06% 26.39% 19.33% 0.68 20.20440%2009 3.24% -88.85% -92.09% 0.68 -59.38120%2010 7.68% -8.08% -15.76% 0.68 -3.03834%


Market Rate



Cipla

40


Ltd.2000 10.10% -3.93% -14.03% 0.51 2.944700%2001 7.35% 27.35% 20.00% 0.51 17.550000%2002 5.62% -23.53% -29.15% 0.51 -9.246500%2003 4.55% -24.79% -29.34% 0.51 -10.413400%2004 5.79% 7.33% 1.54% 0.51 6.575400%2005 5.60% -0.20% -5.80% 0.51 2.642000%2006 7.22% -4.68% -11.90% 0.51 1.151000%2007 6.07% -61.43% -67.50% 0.51 -28.355000%2008 7.06% 41.57% 34.51% 0.51 24.660100%2009 3.24% -0.20% -3.44% 0.51 1.485600%2010 7.68% -6.24% -13.92% 0.51 0.578448%


Market Rate



D L F Ltd.

2000 10.10% -10.10% 1.63 -6.36300%2001 7.35% -7.35% 1.63 -4.63050%2002 5.62% -5.62% 1.63 -3.54060%2003 4.55% -4.55% 1.63 -2.86650%2004 5.79% -5.79% 1.63 -3.64770%2005 5.60% -5.60% 1.63 -3.52800%2006 7.22% -7.22% 1.63 -4.54860%2007 6.07% 42.21% 36.14% 1.63 64.97820%2008 7.06% -21.06% -28.12% 1.63 -38.77560%2009 3.24% -52.32% -55.56% 1.63 -87.32280%2010 7.68% -36.13% -43.81% 1.63 -63.72728%

Table 6:Market Rate


41


Risk Free Rate


H D F C Bank Ltd

2000 10.10% 59.42% 49.32% 0.92 55.474400%2001 7.35% 19.71% 12.36% 0.92 18.721200%2002 5.62% -4.96% -10.58% 0.92 -4.113600%2003 4.55% -3.43% -7.98% 0.92 -2.791600%2004 5.79% 31.34% 25.55% 0.92 29.296000%2005 5.60% -7.24% -12.84% 0.92 -6.212800%2006 7.22% 4.47% -2.75% 0.92 4.690000%2007 6.07% 15.46% 9.39% 0.92 14.708800%2008 7.06% 10.50% 3.44% 0.92 10.224800%2009 3.24% -9.48% -12.72% 0.92 -8.462400%2010 7.68% 21.43% 13.75% 0.92 20.330000%

42


43


Market Rate

Risk Premium BETA CAP

364 T- Bill Rate Cost Cost of Equity

Hero Honda Motors Ltd

2000 10.10% -1.24% -11.34% 0.44 5.110400%2001 7.35% 67.70% 60.35% 0.44 33.904000%2002 5.62% 9.60% 3.98% 0.44 7.371200%2003 4.55% 4.87% 0.32% 0.44 4.690800%2004 5.79% 19.26% 13.47% 0.44 11.716800%2005 5.60% 12.69% 7.09% 0.44 8.719600%2006 7.22% -55.37% -62.59% 0.44 -20.319600%2007 6.07% -53.31% -59.38% 0.44 -20.057200%2008 7.06% 70.41% 63.35% 0.44 34.934000%2009 3.24% 35% 31.76% 0.44 17.214400%2010 7.68% 4.98% -2.70% 0.44 6.489312%


Market Rate



Hindalco Industries Ltd.

2000 10.10% 12.91% 2.81% 1.33 13.837300%2001 7.35% 5.87% -1.48% 1.33 5.381600%2002 5.62% -8.62% -14.24% 1.33 -13.319200%2003 4.55% 71.48% 66.93% 1.33 93.566900%2004 5.79% -8.22% -14.01% 1.33 -12.843300%2005 5.60% -36.92% -42.52% 1.33 -50.951600%2006 7.22% -21.37% -28.59% 1.33 -30.804700%2007 6.07% -22.12% -28.19% 1.33 -31.422700%2008 7.06% -20.75% -27.81% 1.33 -29.927300%2009 3.24% 133.78% 130.54% 1.33 176.858200%2010 7.68% 36.83% 29.15% 1.33 46.451084%



Market Rate



Hindustan Unilever Ltd.

2000 10.10% 13.55% 3.45% 0.47 11.721500%2001 7.35% 28.50% 21.15% 0.47 17.290500%2002 5.62% -21.06% -26.68% 0.47 -6.919600%2003 4.55% -55.20% -59.75% 0.47 -23.532500%2004 5.79% -41.13% -46.92% 0.47 -16.262400%2005 5.60% -2.71% -8.31% 0.47 1.694300%2006 7.22% -34.33% -41.55% 0.47 -12.308500%2007 6.07% -43.84% -49.91% 0.47 -17.387700%2008 7.06% 70.50% 63.44% 0.47 36.876800%2009 3.24% -72.40% -75.64% 0.47 -32.310800%2010 7.68% 3.30% -4.38% 0.47 5.618856%


Market Rate



Housing Development Finance Corpn. Ltd.

2000 10.10% 114.49% 104.39% 0.92 106.138800%2001 7.35% 42.55% 35.20% 0.92 39.734000%2002 5.62% 8.90% 3.28% 0.92 8.637600%2003 4.55% 11.96% 7.41% 0.92 11.367200%2004 5.79% 9.93% 4.14% 0.92 9.598800%2005 5.60% 18.50% 12.90% 0.92 17.468000%2006 7.22% -12.12% -19.34% 0.92 -10.572800%2007 6.07% 31.85% 25.78% 0.92 29.787600%2008 7.06% 4.06% -3.00% 0.92 4.300000%2009 3.24% 1.28% -1.96% 0.92 1.436800%2010 7.68% 20.18% 12.50% 0.92 19.179616%

44



Market Rate


364 T- Bill Rate

Cost of Equity

I T C Ltd.

2000 10.10% 56.88% 46.78% 0.47 32.086600%2001 7.35% -6.65% -14.00% 0.47 0.770000%2002 5.62% -4.05% -9.67% 0.47 1.075100%2003 4.55% -20.84% -25.39% 0.47 -7.383300%2004 5.79% 23.01% 17.22% 0.47 13.883400%2005 5.60% 23.26% 17.66% 0.47 13.900200%2006 7.22% -19.88% -27.10% 0.47 -5.517000%2007 6.07% -25.22% -31.29% 0.47 -8.636300%2008 7.06% 32.97% 25.91% 0.47 19.237700%2009 3.24% -32.15% -35.39% 0.47 -13.393300%2010 7.68% 26.71% 19.03% 0.47 16.621556%

45



Market Rate


364 T- Bill Rate

Cost of Equity

Infosys Technologies Ltd.

2000 10.10% -10.10% 0.45 5.55500%2001 7.35% -10.40% -17.75% 0.45 -0.63750%2002 5.62% 14.39% 8.77% 0.45 9.56650%2003 4.55% -55.29% -59.84% 0.45 -22.37800%2004 5.79% 40.40% 34.61% 0.45 21.36450%2005 5.60% 2.95% -2.65% 0.45 4.40750%2006 7.22% 4.51% -2.71% 0.45 6.00050%2007 6.07% -67.70% -73.77% 0.45 -27.12650%2008 7.06% 17.80% 10.74% 0.45 11.89300%2009 3.24% 55.02% 51.78% 0.45 26.54100%2010 7.68% 17.31% 9.63% 0.45 12.01086%

46


Market Rate


364 T- Bill Rate

Cost of Equity

I C I C I Bank Ltd.

2000 10.10% 135.72% 125.62% 1.38 183.455600%2001 7.35% -22.89% -30.24% 1.38 -34.381200%2002 5.62% 58.70% 53.08% 1.38 78.870400%2003 4.55% 47.67% 43.12% 1.38 64.055600%2004 5.79% 14.64% 8.85% 1.38 18.003000%2005 5.60% 19.32% 13.72% 1.38 24.533600%2006 7.22% 9.97% 2.75% 1.38 11.015000%2007 6.07% -7.21% -13.28% 1.38 -12.256400%2008 7.06% -10.45% -17.51% 1.38 -17.103800%2009 3.24% 17.15% 13.91% 1.38 22.435800%2010 7.68% 15.17% 7.49% 1.38 18.018024%



Market Rate


364 T- Bill Rate

Cost of Equity

Jindal Steel & Power Ltd.

2000 10.10% -19.41% -29.51% 1.45 -32.689500%2001 7.35% 6.46% -0.89% 1.45 6.059500%2002 5.62% 127.14% 121.52% 1.45 181.824000%2003 4.55% 195.66% 191.11% 1.45 281.659500%2004 5.79% 30.84% 25.05% 1.45 42.112500%2005 5.60% 32.52% 26.92% 1.45 44.634000%2006 7.22% 0.89% -6.33% 1.45 -1.958500%2007 6.07% 533.76% 527.69% 1.45 771.220500%2008 7.06% -17.58% -24.64% 1.45 -28.668000%2009 3.24% 282.88% 279.64% 1.45 408.718000%2010 7.68% -15.94% -23.62% 1.45 -26.566840%

47


Market Rate

Risk Premium

BETA

CAPM

364 T- Bill Rate

Cost of Equity

Jaiprakas



Market Rate


364 T- Bill Rate

Cost of Equity

Larsen & Toubro Ltd.

2000 10.10% -43.43% -53.53% 1.2 -54.13600%2001 7.35% 18.66% 11.31% 1.2 20.92200%2002 5.62% 12.68% 7.06% 1.2 14.09200%2003 4.55% 80.82% 76.27% 1.2 96.07400%2004 5.79% 24.96% 19.17% 1.2 28.79400%2005 5.60% 45.70% 40.10% 1.2 53.72000%2006 7.22% 14.11% 6.89% 1.2 15.48800%2007 6.07% 144.49% 138.42% 1.2 172.17400%2008 7.06% -9.95% -17.01% 1.2 -13.35200%2009 3.24% 37.37% 34.13% 1.2 44.19600%2010 7.68% 1.24% -6.44% 1.2 -0.04704%

Market Rate

Risk Premium

BETA CAPM

48


Market Rate

Risk Premium

BETA

CAPM

364 T- Bill Rate

Cost of Equity

Mahindra &


Table 18:Risk Free Rate364 T- Bill Rate

Cost of Equity

Maruti Suzuki

2000 10.10% -10.10% 0.74 2.62600%2001 7.35% -7.35% 0.74 1.91100%2002 5.62% -5.62% 0.74 1.46120%2003 4.55% 56.49% 51.94% 0.74 42.98560%2004 5.79% 11.87% 6.08% 0.74 10.28920%2005 5.60% -4.37% -9.97% 0.74 -1.77780%2006 7.22% 0.75% -6.47% 0.74 2.43220%2007 6.07% -39.76% -45.83% 0.74 -27.84420%2008 7.06% 5.32% -1.74% 0.74 5.77240%2009 3.24% 119.65% 116.41% 0.74 89.38340%

2010 7.68%

-25.90% -33.58% 0.74 -17.17045%

49


50


Market Rate


364 T- Bill Rate

Cost of Equity

N T P C Ltd.

2000 10.10% -10.10% 0.69 3.13100%2001 7.35% -7.35% 0.69 2.27850%2002 5.62% -5.62% 0.69 1.74220%2003 4.55% -4.55% 0.69 1.41050%2004 5.79% 4% -1.79% 0.69 4.55490%2005 5.60% -10.20% -15.80% 0.69 -5.30200%2006 7.22% -21.41% -28.63% 0.69 -12.53470%2007 6.07% 40.16% 34.09% 0.69 29.59210%2008 7.06% 24.18% 17.12% 0.69 18.87280%2009 3.24% -48.38% -51.62% 0.69 -32.37780%2010 7.68% -30.71% -38.39% 0.69 -18.81059%



Market Rate


364 T- Bill Rate

Cost of Equity

Reliance Communications Ltd.

51


Market Rate


364 T- Bill Rate

Cost of Equity

O N G C Videsh Ltd.

2000 10.10% -17.68% -27.78% 10.100%2001 7.35% 37.82% 30.47% 7.350%2002 5.62% 166.74% 161.12% 5.620%2003 4.55% 70.72% 66.17% 4.550%2004 5.79% -5.80% -11.59% 5.790%2005 5.60% 5.79% 0.19% 5.600%2006 7.22% -34.02% -41.24% 7.220%2007 6.07% -0.71% -6.78% 6.070%2008 7.06% 8.01% 0.95% 7.060%2009 3.24% 0.20% -3.04% 3.240%2010 7.68% -3.65% -11.33% 7.675%


Market Rate


364 T- Bill Rate

Cost of Equity

Reliance Industries Ltd.

2000 10.10% 67.31% 57.21% 1.03 69.026300%2001 7.35% 9% 1.65% 1.03 9.049500%2002 5.62% -2.46% -8.08% 1.03 -2.702400%2003 4.55% 23.15% 18.60% 1.03 23.708000%2004 5.79% -16.82% -22.61% 1.03 -17.498300%2005 5.60% 28.29% 22.69% 1.03 28.970700%2006 7.22% 74.04% 66.82% 1.03 76.044600%2007 6.07% 81.51% 75.44% 1.03 83.773200%2008 7.06% -4.10% -11.16% 1.03 -4.434800%2009 3.24% -2.89% -6.13% 1.03 -3.073900%2010 7.68% -19.66% -27.34% 1.03 -20.480056%


2000 10.10% -10.10% 1.31 -3.13100%2001 7.35% -7.35% 1.31 -2.27850%2002 5.62% -5.62% 1.31 -1.74220%2003 4.55% -4.55% 1.31 -1.41050%2004 5.79% -5.79% 1.31 -1.79490%2005 5.60% -5.60% 1.31 -1.73600%2006 7.22% 14.17% 6.95% 1.31 16.32450%2007 6.07% 11.39% 5.32% 1.31 13.03920%2008 7.06% -16.79% -23.85% 1.31 -24.18350%2009 3.24% -104.73% -107.97% 1.31 138.2000%2010 7.68% -33.07% -40.75% 1.31 -45.70101%

Risk Free Rate

Market Rate


364 T- Bill Rate

Cost of Equity

Reliance Infrastructure Ltd.

2000 10.10% 26.12% 16.02% 1.54 34.770800%2001 7.35% 19.94% 12.59% 1.54 26.738600%2002 5.62% 10.75% 5.13% 1.54 13.520200%2003 4.55% 62.22% 57.67% 1.54 93.361800%2004 5.79% -8.56% -14.35% 1.54 -16.309000%2005 5.60% -28.02% -33.62% 1.54 -46.174800%2006 7.22% -60.46% -67.68% 1.54 -97.007200%2007 6.07% 267.30% 261.23% 1.54 408.364200%2008 7.06% -21.88% -28.94% 1.54 -37.507600%2009 3.24% 17.95% 14.71% 1.54 25.893400%2010 7.68% -43.48% -51.16% 1.54 -71.103808%

52



Market Rate


364 T- Bill Rate

Cost of Equity

State Bank Of India

2000 10.10% 7.34% -2.76% 1.08 7.119200%2001 7.35% 14.95% 7.60% 1.08 15.558000%2002 5.62% 55.27% 49.65% 1.08 59.242000%

53

Table 23:


2003 4.55% 21.81% 17.26% 1.08 23.190800%2004 5.79% 6.87% 1.08% 1.08 6.956400%2005 5.60% 1.88% -3.72% 1.08 1.582400%2006 7.22% -5.63% -12.85% 1.08 -6.658000%2007 6.07% 45.22% 39.15% 1.08 48.352000%2008 7.06% 10.56% 3.50% 1.08 10.840000%2009 3.24% -1.96% -5.20% 1.08 -2.376000%2010 7.68% 8.18% 0.50% 1.08 8.220384%


Market Rate


364 T- Bill Rate

Cost of Equity

Tata Consultancy Services Ltd.

2000 10.10% -10.10% 0.49 5.15100%

54


Market Rate

Risk Premium

BETA

CAPM

364 T- Bill Rate

Cost of Equity

Sterlit


2001 7.35% -7.35% 0.49 3.74850%2002 5.62% -5.62% 0.49 2.86620%2003 4.55% -4.55% 0.49 2.32050%2004 5.79% 23.97% 18.18% 0.49 14.69820%2005 5.60% -11.49% -17.09% 0.49 -2.77410%2006 7.22% -3.54% -10.76% 0.49 1.94760%2007 6.07% -57.26% -63.33% 0.49 -24.96170%2008 7.06% -1.32% -8.38% 0.49 2.95380%2009 3.24% 138.80% 135.56% 0.49 69.66440%2010 7.68% 41.90% 34.22% 0.49 24.44535%


Market Rate


364 T- Bill Rate

Cost of Equity

Tata Motors Ltd.

2000 10.10% -35.62% -45.72% 1.16 63.13520%2001 7.35% 54.52% 47.17% 1.16 47.36720%2002 5.62% 58.15% 52.53% 1.16 55.31480%2003 4.55% 113.11% 108.56% 1.16 121.3796%2004 5.79% 1.60% -4.19% 1.16 10.65040%2005 5.60% -8.84% -14.44% 1.16 22.35040%2006 7.22% -8.09% -15.31% 1.16 24.97960%2007 6.07% -63.06% -69.13% 1.16 86.26080%2008 7.06% -25.37% -32.43% 1.16 44.67880%2009 3.24% 324.23% 320.99% 1.16 369.1084%2010 7.68% 49.96% 42.28% 1.16 41.37516%

55



Market Rate


364 T- Bill Rate

Cost of Equity

Tata Power Co. Ltd.

2000 10.10% 65.03% 54.93% 1.01 65.579300%2001 7.35% 43.93% 36.58% 1.01 44.295800%2002 5.62% -1.98% -7.60% 1.01 -2.056000%2003 4.55% 119.81% 115.26% 1.01 120.962600%2004 5.79% 13.31% 7.52% 1.01 13.385200%2005 5.60% -27.22% -32.82% 1.01 -27.548200%2006 7.22% -15.98% -23.20% 1.01 -16.212000%2007 6.07% 119.33% 113.26% 1.01 120.462600%2008 7.06% 1.28% -5.78% 1.01 1.222200%2009 3.24% 5.10% 1.86% 1.01 5.118600%2010 7.68% -17.42% -25.10% 1.01 -17.670952%

56



Market Rate


364 T- Bill Rate

Cost of Equity

Wipro Ltd.

2000 10.10% 13.19% 3.09% 0.75 12.417500%2001 7.35% -15.52% -22.87% 0.75 -9.802500%2002 5.62% -1.70% -7.32% 0.75 0.130000%2003 4.55% -66.22% -70.77% 0.75 -48.527500%2004 5.79% 18.40% 12.61% 0.75 15.247500%2005 5.60% -18.99% -24.59% 0.75 -12.842500%2006 7.22% -15.92% -23.14% 0.75 -10.135000%2007 6.07% -58.94% -65.01% 0.75 -42.687500%2008 7.06% -1.82% -8.88% 0.75 0.400000%

57


Market Rate


364 T- Bill Rate

Cost of Equity

Tata Steel Ltd.

2000 10.10% 12.53% 2.43% 1.45 13.623500%2001 7.35% -12.73% -20.08% 1.45 -21.766000%2002 5.62% 83.79% 78.17% 1.45 118.966500%2003 4.55% 135.26% 130.71% 1.45 194.079500%2004 5.79% 22.48% 16.69% 1.45 29.990500%2005 5.60% -41.52% -47.12% 1.45 -62.724000%2006 7.22% -14.40% -21.62% 1.45 -24.129000%2007 6.07% 77.96% 71.89% 1.45 110.310500%2008 7.06% -23.66% -30.72% 1.45 -37.484000%2009 3.24% 115.27% 112.03% 1.45 165.683500%2010 7.68% -5.73% -13.41% 1.45 -11.762340%


2009 3.24% 112.94% 109.70% 0.75 85.515000%2010 7.68% 3.89% -3.79% 0.75 4.836300%

4.2 INFERENCES FROM EMPIRICAL STUDY

Sector Wise Analysis:-

Information Technology:- Companies like TCS, Infosys & Wipro provided a very low return on Equity during the period of 2000- 2003 period. The revenue & profit margins were deeply affected by Dot Com bubble which is basically reflected in the return provided by these stocks providing negative and returns close to zero and using the CAPM parameters this is reflected truly in the actual returns. Companies like TCS provide return 5%, 3% & 2% in ’00, ’01 & ’02. Stocks like Infosys provided return as 5%, 0%, 9% & -22% during dot com bubble. These companies seemed to have revived post ’04 posting higher return with Infosys as the market leader in return. The returns were 21% for year ’04 in case of Infosys and the returns of Wipro & TCS were close to that Infosys. However in ’07 due to US Subprime crisis the return were affected. But since the revival of economy all these stocks have shown robust performance which is reflected in the returns of CAPM model. Wipro posted a return of 85% by Wipro, 69% by TCS & 26% by Infosys in ’09.

Telecommunication:- Telecommunications companies like Reliance Communication & Bharti Airtel have always driven on lower margins and higher cost. With introduction of more companies the telecom space has become more competitive. These stocks have been below average performer with a few exceptional year around ’03-’04 where they experienced high growth opportunities. Return on reliance communication has been consistently been around -1%.Recession had its own toll over telecom sector. Reliance provided heft return as 138% during ’09 period otherwise it has been below average performer. Bharti Airtel has performed well during growth years and provide returns as high as 159% in ’03 & followed it with return of 58% & 26% in subsequent years. During recent years they have experienced a better surge but that has been a consistent growth and so the returns by CAPM reflect the situation of companies like Reliance Communication & Bharti Airtel, though Airtel has shown a better performance compared to Reliance simply because of company fundamentals being better.

Banking & Financial Sector:- The banking and financial sector was booming in the period of 2000. The performance was sustained till the period of ’04 for the growing demand of ever expanding Indian economy. Stocks like SBI, HDFC, HDFC Bank, ICICI outperformed many of the other stocks and the returns through CAPM show the kind of hefty returns provided by these stocks. Stocks like SBI provided returns like 15%, 59% & 23& before ’05. Another heavyweight ICICI provided returns as high as 183%, 78%, 64% during the same period. However in post ’05 there was a decline in their return and post recession these stocks provided negative returns due to the coupling effect of economies of recession. Moreover, it was the financial crisis so the banking sector was hit the hardest. However, these stocks seemed to have revived and provided

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average returns since then a bit higher than to returns on government securities. The performance of these stocks is shown in returns on CAPM. SBI provided return close to 10%, -2% in ’08 & ’09. It revived to 8% in ’10 showing signs of recovery. HDFC provided returns as 4%, 1% in 08 & ’09 respectively & provided higher return in ’10 with returns close to 19%. Same was the case with HDFC bank providing returns as 10%, -8% & 20% during the same period.

FMCG:- This sector provides average returns. In the period of ’00 the returns were higher than average return but since then the returns have been quite low even negative for HUL consistently. HUL returns were -6%, -23% & -16%. ITC returns were close to 1%, 0% & -7%.A better performance during the period of ’04-’05 was shown by both the stocks HUL &ITC due to growing economic demand. ITC returns were hovering around 13% but slipped to -5% & -8% again and so was the case with HUL with returns as -12% & -17%. However, the demand slipped again and these sector have provided a negative returns with an exception of ’08 year and in last financial year. ITC returns in ’08 were 19% & in ’10 close to 16%.The performance of FMCG sector as a whole in the particular year has never been inspiring and government securities seems to be a safer bet. The Cost of Equity (return on stocks) using CAPM shows the kind of return thus ascertaining the position of FMCG sector as not a safe bet for investment and diversification of portfolio.

Automobile:- Companies like Bajaj Auto, Hero Honda, Maruti Suzuki have been providing low returns with the sole exception of Hero Honda & Tata Motors. The sales of Tata Motors have outperformed Indian car segment. Maruti Suzuki returns have hovered around 2% & 1% in 00’-’04 and same is the case with Bajaj Auto. Tata Motors returns were 63%,47%,55% 121% during ’00-’04 period. On the other hand, Hero Honda Motors have been providing par performance with the industry. The automobiles sales domestic and export market was hit hard because of recession and all companies sales declined resulting in negative returns. Maruti Suzuki returns were -27% in ’07 but seemed to have recover and gave returns as close to 89% in ‘09 However, the spurt in demand for automobiles in India because of higher disposable income post recession has ensured higher volumes for all companies & impressive growth for these companies and this is reflected in return calculated by CAPM model. Like in case of Tata Motors despite recessionary period it provided returns of 86%, 44% in ’07 & ’08 and a 369% return in ‘ post recession ’09 period.

Manufacturing Sector:- Manufacturing Sector has been one of the strong hold of the Indian economy thus substantiating the point of India being one of the fastest growing economies. This sector has been outperforming with a high growth post ’00. Sterlite have performed well with 65% & 44% returns in ’00 &’01. M&M posted a return of around 200% in ’03 and has been consistently hovering around 30%-50% return to pre-recession period. Companies have posted higher sales revenue and higher margins resulting in higher returns in not only stock returns but higher dividends as well. Companies faced a slight turbulence in ’04-’06 where certain stocks

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posted losses and their performance revived in first half of ’07 before they were affected by recession whose effect was felt in ’08. Sterlite again posted a good performance return in ’07 before being hit by recessionary phase. Larsen Toubro return in ’07 were 172%. But these companies fundamentals have been strong and they were able to quickly recover from it and again posted huge profit margins and higher returns for investor. Companies like Sterlite have provided as high as 1192% return in ’03 and a high returns as 200% after recession along with M&M whose return were close to 240%. L&T , Hindalco, BHEL &Reliance Industries have performed in correlation with Manufacturing Sector. RIL provided returns of around 34 & 26% in ’00-’01 with a high of 93% in ’03. It showed negative returns since’04 before a high of 408% in ’07. Snce then it has gradually recovered and provided average returns at par with industry.

Steel & Power Sector:- Steel & Power is another sector like Manufacturing sector that has been the stronghold of Indian economy. Again companies like Tata Steel, Tata Power, Jindal Steel & Power, Jaiprakash Associates have performed outstandingly with return as high as more than 100% in the financial year of ’03-’04. Tata Steel returns have been 118%, 194% & 29% form ’02-’04 along with Tata Power return as 120% in ‘03. Jindal Steel returns were 181 &281% during the same years These stocks have performed consistently well even before this period like Tata Power returns were 65% & 44& in ’00 & ‘01. However, they faced slight decline during the period of ’05-’06 where Tata Steel returns declined 62% & 24%. But they again performed exceedingly well in ’07 when the economy was at its high before the Subprime crisis hit the world. Stocks like Jindal Steel returns were outstanding like 707% returns, Tata Steel returns were 110% ,Tata Power returns were 120% in ’07 and JP Associates returns were 247% in the same year. The effects of which were felt in subsequent year. These stock being fundamentally strong with huge demand potential recovered by’09 and have performed well after that. Jindal Steel was the market leader with 408% return. Tata steel again outperformed the market with returns of 165% despite a -37% return in ’08. Tata Power return post Subprime crisis were 5% and 1%. Stocks of PSU like NTPC, ONGC have been providing returns at par with the benchmark rate of government securities. This is reflected in the CAPM return of these stocks.

Infrastructure Sector:- The need for infrastructure has been growing with economy expanding. Infrastructure has been booming and a robust performance was shown during the period of ’00-’04 but since then there has been a considerable slowdown in demand. These stocks correlated with market risk and market return have given positive returns till ’04 but the slow down has resulted in negative returns. Reliance Infrastructure provided return with 34%, 26% , 13% and as high as 93%. After ’04 these stocks seemed to decline with returns as -46% & -97% in ‘05 & ‘06 period. As an exception to recession the sector became a safer investment haven as compared to financial instruments and so outperformed the market return. Both DLF and Reliance Infra provided much higher return. Reliance Infra provided return close to 408% in ‘08 However, this phenomena was short lived and due to credit crunch problem these sectors again declined and have slightly reviewed after ’08-’09 and a better performance is expected. These performance are reflected in CAPM returns.

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Pharmaceutical:- This sector has been a laggard. The performance of Indian generic industry was average in ’00-’01. The sales further declined post this period with below average margins of pharma companies. Return on Cipla were 2%, 17%, -9% & -10% during the period of 2000-’04. The recession didn’t help the situation further as the generic version exports from Indian market as well domestic competition reduced margins for the companies. The regulations of patents and constant scrutiny of the generic version was another hinderance in the performance. They seemed to have revived but that even a slightly bit. These are shown in the result of CAPM return of pharmaceutical companies like Cipla in this case. In ’08 returns were 28% but post recession they have touched the lows of 1% & 0%.

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4.3 APPLICATION OF THE CAPM TO STRATEGIC PLANNING

The strategic portfolio planning problem of the firm involves two interdependent decisions. First, management must decide which businesses in the portfolio should be retained and which should be removed (divested). Second, for those businesses retained in or added to the portfolio, management must determine the amount to invest in each business. Under the CAPM framework, the primary strategic objective of management in making these two interdependent decisions is to maximize Vz, the expected value of the firm's common stock.

The first point to note about is that the company's management wields little or no influence over the risk-free interest rate i and the market price of risk p.

The three parameters over which management has at least partial control are the company's profit stream , the standard deviation of the company's rate of return and the correlation coefficient between the company's rate of return and the market rate of return.

The company's return from its entire portfolio of businesses depends not only on the variance of the returns of the businesses constituting the portfolio but also on the relationship between these businesses, which is denoted by the covariance . By diversifying its portfolio to include businesses with low positive covariances or even possibly negative covariances, a conglomerate can reduce the dispersion of the probability distribution of possible returns

In summary, in building a portfolio of businesses, a company should strive for high profits in each business, low variances of return , negative covariances of returns , and values of that are close to zero or negative.vi

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4.4 Building A Portfolio:-

Year Higher Return Stocks

2000 HDFC,HDFC Bank, Hindalco HUL,ITC, ICICI, ONGC, RIL Reliance Infra, Tata Power, Tata Motors, Sterlite

2001 HDFC, HDFC Bank, Hero Honda, HUL, L& T, Reliance Infra, SBI, Tata Power, Tata Motors, Sterlite

2002 BHEL,ICICI,JSPL,M&M, Tata Motors, Tata Steel, SBI2003 BHEL, Bharti Airtel, Hindalco, ICICI, JSPL, L&T,

M&M, Maruti Suzuki, RIL, SBI, Reliance Infra, Sterlite, Tata Power, Tata Motors, Tata Steel

2004 BHEL, Bharti Airtel, HDFC Bank, Hero Honda, Infosys, JSPL, L&T, M&M, TCS, Tata Power, Tata Steel Wipro

2005 BHEL, HDFC, ITC, ICICI, Jai prakash Associates, JSPL, L&T, M&M, RIL, Sterlite, Tata Motors

2006 Bharti Airtel, Jai prakash Associates, M&M, RIL, Reliance Communication, Sterlite, Tata Motor

2007 BHEL, DLF, HDFC Bank, Hero Honda, HDFC, Jai prakash Associates, JSPL, L&T, RIL, Reliance Infra, SBI, Sterlite, Tata Power, Tata Motor, Tata Steel

2008 Bharti Airtel, Cipla, HUL, ITC, Tata Motor

2009Bajaj Auto, Hindalco, ICICI, Infosys, Jai prakash Associates, JSPL, M&M, Maruti Suzuki, Reliance Communication, Reliance Infra, Sterlite, TCS, Tata Motor, Tata Steel, Wipro

2010 Bajaj Auto, HDFC Bank, Hindalco, HDFC, ICICI, M&M, TCS, Tata Motor

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4.5 SUMMARY

Although it has certain limitations, the capital asset pricing model appears to offer a company that owns a portfolio of risky businesses a useful conceptual framework for long-term strategic planning. However, the CAPM is merely one of several options available to strategic planners. Among the other options available are competitive strategy models, deterministic portfolio optimization models and corporate simulation models.

Competitive strategy models of the type proposed by the Boston Consulting Group, Arthur D. Little, McKinsey and more recently by Michael Porter all have a quite different focus. Whereas the capital asset pricing model concentrates on risk, return and the value of a business, the competitive strategy models apply such well-known concepts as the growth-share matrix and the experience curve to the overall problem of competitive strategy. That is, competitive strategy models emphasize the interdependence of a business with its competitors, not the interdependence of businesses within a multidivisional firm. Clearly, competitive strategy is an important element in a company's overall strategic plan.

On the other hand, corporate simulation models enable management to examine a variety of strategic options, and to evaluate their consequences on a multiplicity of financial marketing and production indicators. To be useful to management, capital asset pricing models must be linked to some type of corporate simulation model. That is, one can envisage a series of business simulation models, one for each business in the company's portfolio, each of which generates a value for the stream of profits, and the variability of return for that business as well as other output variables of interest to management. A corporate consolidation model that computes the value of the company would also be needed. This consolidated model must in addition treat the interdependencies among the businesses in the company's portfolio.

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Chapter 5Summary & Conclusion from the Study

The following summarizes the various concepts that are understood in the dissertation and the Conclusion about CAPM as an effective tool for measurement of returns on stocks and portfolios.

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CONCLUSION

This study discussed the basic framework for applicability of Capital Asset Pricing Model in Indian stock Market. Better return can be obtained by diversification and using CAPM as a means for estimating the return can be effectively used. The major findings of the study as follows:-

i. Among the various model for estimating the return, CAPM emphasis the strategy of incorporating both risk free return, the return premium for risk undertaken & correlation of return on individual stock & Market return (Beta).

ii. Higher risk does not always guarantee higher return. The optimal portfolio selection results from a well balanced multi-criteria approach rather than a single variable factor.

iii. The contribution of fundamental analysis for selecting a stock in a portfolio is a pivotal factor in selecting appropriate mix of stocks.

However, the study had certain limitations like limiting the kind of stocks for determining the portfolio and the time frame considered. Given these limitations, future research can concentrate on this model to evaluate risk and return of portfolios. Another aspect that can be researched in depth is considering the correlation of market return and individual stock return considering the actual returns provided by the companies over a period of time. This information will further substantiate the robustness of CAPM model. A further area of research can be the application of approach to other decision making situations like merger & acquisition and other corporate decision like capital structure & dividends distribution.

The value of the model lies in the benefits that the integration of various techniques and approaches offer. The multi criterion function provides the company with a tool that optimizes its choices regarding selection of stocks. The model thereby enables to take appropriate investment decision after taking into account its impact on the portfolio as a whole. By using this model, even firms can improve their capital structure.

The development of this integrated model should not be seen as a once- off task with the aim of finding optimal portfolios. Once the optimal portfolio has been identified, the model should be used on regular basis to identify the changes to be incorporated. The model should be used when following situation take place because they would affect the company’s performance

i. Strategic:- Strategic changes can reflect in numerous ways. A company may declare dividends, go for a right issue/ bonus issue, stock split, merger & acquisition, change in capital structure can affect the returns provided by the company and can affect the overall return on portfolio.

ii. Financial:- Changes in the financial performance must be incorporated. Such changes can affect the availability of profits for distribution. The financial fundamentals if are

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brighter in the future would help in inject more & more capital and thus rising the overall market value of the stocks.

iii. Economic:- A fundamental change in economy ( e.g. exchange rate, inflation, business cycle etc.) may result in changes to optimal portfolio.

Considering such factors a stock should be selected. The model by incorporating “Beta” helps in bringing correlation to economic factors and so it remains as a powerful means for decision making process.

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REFERNCES

Brigham, E.F (1989). Fundamental of Financial Management, 5th edition, Dryden Press, Chicago

Elton, E.J. and Grubber M.J. (1987) Modern Portfolio theory and Investment Analysis, 3rd edition., Wiley, New York

Richard A. DeFusco, Jerald E. Pinto and David E. Runkle, 2001 edition, Quantitative Techniques in Portfolio Management, Aimr Publication

Reilly & Brown Investment Analysis & Portfolio Management, 7th edition, South Western College Publication

Rustagi R.P. Financial Management, 3rd edition, Galgotia Publications

Chandra Prassana, Investment Analysis & Portfolio management, 3rd edition , Tata McGraw Hill Publication

Pandey I.M. Financial Management, 9th edition, Vikas Publication

Edwin J. Elton, Martin J. Gruber, Stephen J. Brown, William N. Goetzmann, 8th edition, Modern Portfolio Theory & Investment Analysis

Charles P. Jones, 9th edition Investments: Analysis and Management

Prasad G B R K, How to Choose Winning Stocks: Rewriting Formulas for Investment

Bhalla V. K., 2008 edition, Portfolio Analysis and Management, S. Chand Publications

Khan M.Y. & Jain P.K.,11th edition, Financial Management, Tata McGraw Hill Publication

Fisher & Jordan, 6th edition, Security Analysis & Portfolio Management, Prentice Hall Publication

Kevin S., 2nd edition, Security Analysis & Portfolio Management, Prentice Hall

Pandian Punithavathy, 6th edition, Security Analysis & Portfolio Management, Vikas Publication

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www.rbi.org

www.bse.co.in

www.wikipedia.org

www.nse-india.com

Annual reports of top 30 BSE Sensex Companies

Research Papers & Journals from JStore

(i) CAPM Research paper – Andre F. Perold(ii) CAPM Model: Theory & Evidence - Eugene F. Fama and Kenneth R.

French(iii) CAPM vs. Three Factor Model - Riad Ramlogan(iv) CAPM – Lan Liu(v) Market Imperfections, Capital Market Equilibrium &

Corporate Finance – R.C. Stapleton & M.G. Subhramanyam(vi) CAPM as a Strategic Planning tool - Francis Tapon(vii) Benchmark Beta, CAPM & Pricing Anomalies – Eun(viii) Growth Options, Beta & Cost of Capital – Antonio E. Bernardo, Bhagwan

Chaudhary & Amit Goyal(ix) The Value Premium & CAPM – Fama & French

Prowess

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http://www.nse-india.com/

http://www.wikipedia.org/

http://www.bse.co.in/

http://www.rbi.org/


ANNEXURES

BETA CHART

BSE BSE BSE BSE BSE BSE BSE BSE BSE BSE BSE

No. No. No. No. No. No. No. No. No. No. No.Dec-00 Dec-01 Dec-02 Dec-03 Dec-04 Dec-05 Dec-06 Dec-07 Dec-08 Dec-09 Dec-10

Company Name Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Bajaj Auto Ltd. 0.91 0.91 0.91Bharat Heavy Electricals Ltd. 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01Bharti Airtel Ltd. 0.68 0.68 0.68 0.68 0.68 0.68 0.68 0.68 0.68Cipla Ltd. 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51D L F Ltd. 1.63 1.63 1.63 1.63H D F C Bank Ltd. 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92Hero Honda Motors Ltd. 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44 0.44Hindalco Industries Ltd. 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33Hindustan Unilever Ltd. 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47Housing Development Finance Corpn. Ltd. 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92 0.92I C I C I Bank Ltd. 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38 1.38I T C Ltd. 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47Infosys Technologies Ltd. 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45Jaiprakash Associates Ltd. 1.7 1.7 1.7 1.7 1.7 1.7 1.7Jindal Steel & Power Ltd. 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45Larsen & Toubro Ltd. 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2Mahindra & Mahindra Ltd. 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1Maruti Suzuki India Ltd. 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74N T P C Ltd. 0.69 0.69 0.69 0.69 0.69 0.69 0.69Oil & Natural Gas Corpn. Ltd. 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9Reliance Communications Ltd. 1.31 1.31 1.31 1.31 1.31Reliance Industries Ltd. 1.03 1.03 1.03 1.03 1.03 1.03 1.03 1.03 1.03 1.03 1.03Reliance Infrastructure Ltd. 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54 1.54State Bank Of India 1.08 1.08 1.08 1.08 1.08 1.08 1.08 1.08 1.08 1.08 1.08Sterlite Industries (India) Ltd. 1.41 1.41 1.41 1.41 1.41 1.41 1.41 1.41 1.41 1.41 1.41Tata Consultancy Services Ltd. 0.49 0.49 0.49 0.49 0.49 0.49 0.49Tata Motors Ltd. 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16Tata Power Co. Ltd. 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.01Tata Steel Ltd. 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45 1.45Wipro Ltd. 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75

Beta for top 30 Companies of BSE Sensex

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MARKET RETURN CHART

MARKET RETURNMARKET RETURNBSE BSE BSE BSE BSE BSE BSE BSE BSE BSE BSE

(%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%)Dec-00 Dec-01 Dec-02 Dec-03 DEC '04 Dec-05 Dec-06 Dec-07 Dec-08 Dec-09 Dec-10

Company NameBajaj Auto Ltd. 20.05 279.44 60.48Bharat Heavy Electricals Ltd. 0.82 5.63 22.04 124.77 39.88 42.8 20.39 79.7 5.62 -2.65 -19.86Bharti Airtel Ltd. -51.66 286.06 82.62 19.52 35.43 11.01 26.39 -88.85 -8.08Cipla Ltd. -3.93 27.35 -23.53 -24.79 7.33 -0.2 -4.68 -61.43 41.57 -0.2 -6.24D L F Ltd. 42.21 -21.06 -52.32 -36.13H D F C Bank Ltd. 59.42 19.71 -4.96 -3.43 31.34 -7.24 4.47 15.46 10.5 -9.48 21.43Hero Honda Motors Ltd. -1.24 67.7 9.6 4.87 19.26 12.69 -55.37 -53.31 70.41 35 4.98Hindalco Industries Ltd. 12.91 5.87 -8.62 71.48 -8.22 -36.92 -21.37 -22.12 -20.75 133.78 36.83Hindustan Unilever Ltd. 13.55 28.5 -21.06 -55.2 -41.13 -2.71 -34.33 -43.84 70.5 -72.4 3.3Housing Development Finance Corpn. Ltd. 114.49 42.55 8.9 11.96 9.93 18.5 -12.12 31.85 4.06 1.28 20.18I C I C I Bank Ltd. 135.72 -22.89 58.7 47.67 14.64 19.32 9.97 -7.21 -10.45 17.15 15.17I T C Ltd. 56.88 -6.65 -4.05 -20.84 23.01 23.26 -19.88 -25.22 32.97 -32.15 26.71Infosys Technologies Ltd. -0.68 -10.4 14.39 -55.29 40.4 2.95 4.51 -67.7 17.8 55.02 17.31Jaiprakash Associates Ltd. 58.08 68.15 46.89 148.02 -27.86 86.13 -45.03Jindal Steel & Power Ltd. -19.41 6.46 127.14 195.66 30.84 32.52 0.89 533.76 -17.58 282.88 -15.94Larsen & Toubro Ltd. -43.43 18.66 12.68 80.82 24.96 45.7 14.11 144.49 -9.95 37.37 1.24Mahindra & Mahindra Ltd. -44.06 -19.27 28.63 186.33 29.77 52.11 35.95 -50.73 -14.96 217.65 28.65Maruti Suzuki India Ltd. 56.49 11.87 -4.37 0.75 -39.76 5.32 119.65 -25.9N T P C Ltd. 4 -10.2 -21.41 40.16 24.18 -48.38 -30.71Oil & Natural Gas Corpn. Ltd. -17.68 37.82 166.74 70.72 -5.8 5.79 -34.02 -0.71 8.01 0.2 -3.65Reliance Communications Ltd. 14.17 11.39 -16.79 -104.73 -33.07Reliance Industries Ltd. 67.31 9 -2.46 23.15 -16.82 28.29 74.04 81.51 -4.1 -2.89 -19.66Reliance Infrastructure Ltd. 26.12 19.94 10.75 62.22 -8.56 -28.02 -60.46 267.3 -21.88 17.95 -43.48State Bank Of India 7.34 14.95 55.27 21.81 6.87 1.88 -5.63 45.22 10.56 -1.96 8.18Sterlite Industries (India) Ltd. 49.11 33.51 13.87 852.23 -28.11 24.55 118.43 43.28 -22.14 151.03 -30.3Tata Consultancy Services Ltd. 23.97 -11.49 -3.54 -57.26 -1.32 138.8 41.9Tata Motors Ltd. -35.62 54.52 58.15 113.11 1.6 -8.84 -8.09 -63.06 -25.37 324.23 49.96Tata Power Co. Ltd. 65.03 43.93 -1.98 119.81 13.31 -27.22 -15.98 119.33 1.28 5.1 -17.42Tata Steel Ltd. 12.53 -12.73 83.79 135.26 22.48 -41.52 -14.4 77.96 -23.66 115.27 -5.73Wipro Ltd. 13.19 -15.52 -1.7 -66.22 18.4 -18.99 -15.92 -58.94 -1.82 112.94 3.89

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i

CAPM Research paper – Andre F. Perold

ii CAPM Research paper – Andre F. Perold

iii CAPM Research paper – Andre F. Perold

iv CAPM Model: Theory & Evidence - Eugene F. Fama and Kenneth R. French

v Market Imperfections, Capital Market Equilibrium & Corporate Finance – R.C. Stapleton & M.G. Subhramanyam

vi CAPM as a Strategic Planning tool - Francis Tapon

Portfolio Managent_saurabh Chhabra

Documents

Transcript of Portfolio Managent_saurabh Chhabra