Capital Asset Pricing Model (Capm)

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Capital asset pricing has always been an active area in the finance literature. Capital Asset Pricing Model (CAPM) is one of the economic models used to determine the market price for risk and the appropriate measure of risk for a single asset. The CAPM shows that the equilibrium rates of return on all risky assets are function of their covariance with the market portfolio. This theory helps us understand why expected returns change through time. Furthermore, this model is developed in a hypothetical world with many assumptions.

The Sharp-Lintner-Black CAPM states that the expected return of any capital asset is proportional to its systematic risk measured by the beta. (Iqbal and Brooks, 2007). Based on some simplifying assumptions the CAPM is expressed as a linear function of a risk free rate, beta and the expected risk premium. An important quantity required for decisions on evaluating public and private funded projects is an appropriate cost of capital. This discount rate is often estimated by a model of expected return. The CAPM has been extensively employed for estimating cost of capital and evaluating the performance of managed funds.

Various studies had been performed by various researchers on the capital asset pricing model in different type of markets across the countries around the world. Some of the studies manage to prove that there was a strong relationship between risk and return, while some of them conclude that there is actually no significant relationship between risk and return. However, it was the differences of the market that were tested that resulted in the various different results.

There are two fundamental hypotheses of the CAPM that will be discussed in this study. First is the linearity of the risk-return relationship and second is that beta is the only relevant risk variable explaining cross section variation in expected returns. In this paper, empirical test are performed to test the explanatory performance of the capital asset pricing model on two different markets, the Malaysian market that consist of companies listed on the Bursa Malaysia, and the other one is from the United Kingdom (UK) market. All the chosen companies are from the same industry; trading and services.


Returns may be calculated on holding periods of different lengths- a day, a week, a month, a quarter, a year and so on. For the purpose of this study, monthly closing prices of 20 stocks, the Kuala Lumpur Stock Exchange (KLSE) index and also the FTSE 100 index (UK) were collected. The period covers 5 years, which is equal to 60 months, from September 2003 to August 2008. In statistical analysis, it is generally better to have more rather than fewer observations, because using more observations generally leads to greater statistical confidence. However, the shorter the holding period, the more likely the data are to exhibit random ‘noise’. Also, the greater the number of years of data, the more likely it is that the company’s basic risk position has changed.


Time series regressions were run separately for each 20 companies to estimate the beta coefficient, which is the risk factor loading on each stock. The benchmark for a well-diversified stock portfolio is the market portfolio, which is a portfolio containing all stock. Therefore, the relevant risk of an individual stock, which is called its beta coefficient, is defined under CAPM as the amount of risk that the stock contributes to the market portfolio. (Bringham & Ehrhardt, 2005).

Then, those results were used to analyze if correct relationship exist between beta coefficients, non-systematic risk, and returns. Generally, 30-day Treasury bill rates and long-term Treasury bond rates are used to estimate the value of the risk-free rate. (Bringham & Ehrhardt, 2005).The following equation was applied for all selected stocks:

Ri = Rf + Beta x (Rm-Rf)

Where, Ri is the expected return on an individual security, Rf is...
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