The capital asset pricing model

Abstract

The purpose of this study is to estimate the systematic risk of Dubai Financial Market (DFM) listed stocks and to use the Capital Asset Pricing Model (CAPM) to estimate the equilibrium risk-return relationship for these stocks.

Chapter I discusses market efficiency in its different forms as classified by Fama (1973) and examines the applicability of the efficient market hypothesis with all its assumptions to the DFM.

Chapter II discusses the historical background of modern portfolio theory in general, leading up to the CAPM and the Arbitrage pricing Theory (APT).

Chapter III undertakes a risk analysis of the stocks listed on the DFM. Using historical data, the standard deviation, coefficient of variation and correlation coefficients of these stocks are estimated.

In chapter IV, Beta coefficients of the listed stocks are estimated in the Security Market Line (SML) to generate a risk-return benchmark for these stocks.

Chapter V presents a summary of the findings and limitations of this study. According to the estimations and computations, it was found that some securities are under-priced while others are over-priced. Moreover, it has been found that that there are negative coefficients of correlation among stock prices of companies within the same industry. While computing the difference between the Risk-Free Rate and the Market Rate, negative results were concluded implying the riskiness of investing in stocks whose returns are less than that of the Certificated of Deposits issued by the Central Bank.

These results could be referred to many limitations that have been encountered during the process of data collection, analysis and interpretation of results. One of the main limitations is the compilation of data. Upon collecting data, it was realized that prices of un-traded stocks on a certain trading day are not included. Also, the data included in the analysis refer to the period extending from March 2000 till November 2001. In addition, this data require certain adjustments before they are included in the methods of estimation and computation.

Finally, such studies are expected to give better results if a larger sample of stocks and data relating to the trading of these stocks can be compiled and included in the analysis. This would allow researchers and investors to trace weekly or periodical averages of stock prices and rely on sufficient historical data to reach proper decisions.