Multifactor Asset Pricing Model for Pakistani Equity Market
This study explores the multifactor asset pricing models in Pakistani equity market for the period June 2004 – June2013. All the non-financial firms were the sample for this study. This study proposed a six factor model for pricing of financial assets. The proposed six factor model was first applied to the whole stock exchange and then to individual industries. CAPM’s validity was first checked through Fama Macbeth (1973) methodology and was found invalid in Pakistani stock market, therefore there arises a need to add more risk indicators into the capital asset pricing model. We tested the role of market risk premium, size premium, value premium, asset growth premium, investor sentiment premium & media coverage premium in predicting the future returns of the securities and all except market risk premium were found priced. Asset growth premium, investor sentiment premium and media coverage premium all had negative signs indicating the negative relationship between these risk premiums and their respective rewards. The famous notion of “higher the risk higher will be the reward” does not stand valid for these risk factors. Safer stocks yield higher returns and riskier stocks yield lower returns, therefore, a negative relationship between risk and return was found. These results were consistent with the survey of managers of U.S based firms. According to this study the direction of returns premium for all the factors proved to be verifying the theories regarding their directions. For example, small firms earn higher returns than big firms. High BMR firms yields higher returns than low BMR firms. Low asset growth firms yield higher returns than high asset growth firms. Low sentiment firms earn more than the high sentiment firms and finally no media coverage firms earn more than the firms covered by media. Multicollinearity may exist if there are more than one risk premium in the asset pricing model. It may lead to misguided results, therefore, variance inflationary factor (VIF) was calculated for all these variables and the results lie within the acceptable range of tolerance limits. It implied that multicollinearity did not exist among these variables and that these six variables could be simultaneously used in one asset pricing model to predict the future returns of the financial assets.
One pass and two pass both were applied on the proposed six factor model. The explanatory power of the proposed six factor model according to one pass was almost 70% while it is 37% for the second pass which is considered as worth mentioning. It was great achievement of this study to develop such a model which could help the investors through a successful investment decision and efficient allocation of resources. Investors can base their investment decision on these five factors and can minimize the uncertainty involved in estimating the future returns.
In this study we also applied Fama Macbeth methodology keeping portfolios of various characters like S, B, S/H, S/L, B/H, & B/L as dependant variables. Asset Growth was the only variable which was priced in every subset of portfolio. Therefore, asset growth premium can be used by investors for strategic investment decision without any hesitation.
After applying the proposed six factor model to the individual industries, it was revealed that this model does not predict the returns of industries. Results were inclined towards the notion that “multifactor asset pricing models does not predict industry returns”.