Forecasting performance of capital asset pricing models in case of Pakistani market

This study empirically tests the conditional CAPM, conditional consumption CAPM and conditional multifactor CAPM model with individual stocks traded at Karachi Stock Exchange (KSE), the main equity market in Pakistan for the period 1993-2004. The ability of conditional CAPM models in forecasting asset returns is assessed through predictability of excess return for the period 2005-2006. The results show that the macroeconomic variables that capture business cycle fluctuations are better in explaining the cross-section variation in expected returns, they are found to have better forecasting ability for out-of-sample stock returns in case of Pakistani Market. The evaluation of forecasting ability of the conditional asset pricing models shows that the forecasting power of conditional multifactor CAPM is relatively better compared to conditional CAPM model and conditional consumption CAPM models. It follows, therefore, that the business cycle variables provide useful information for predicting the future direction of stock prices. These variables include market return, call money rate, term structure, industrial production growth, inflation rate, foreign exchange rate and growth in oil prices.