Testing Conditional Asset Pricing Models: An Emerging Market Perspective

The CAPM as the benchmark asset pricing model generally performs poorly in both developed and emerging markets. We investigate whether allowing the model parameters to vary improves the performance of the CAPM and the Fama-French model. Conditional asset pricing models scaled by conditional variables such as Trading Volume and Dividend Yield generally result in small pricing errors. However, a graphical analysis shows that the predictions of conditional models are generally upward biased. We demonstrate that the bias in prediction may be caused by not accommodating frequent large variation in asset pricing models. In emerging markets, volatile institutional, political and macroeconomic conditions results in thick tails in the return distribution. This is characterized by excess kurtosis. It is found that the unconditional Fama-French model augmented with a cubic market factor performs the best among the competing models. This model is also more parsimonious compared to the conditional Fama-French model in terms of number of parameters

AN ANALYTICAL FRAMEWORK FOR EXPLAINING RELATIVE PERFORMANCE OF CAPM BETA AND DOWNSIDE BETA

Even though investors' view of risk is generally regarded as related to the downside of the return distribution the CAPM beta is still a widely used measure of systematic risk. A number of studies compare the empirical performance of CAPM beta and downside beta in explaining the variation in portfolio returns and report mixed results. This paper provides a basis for explaining such mixed results. Using data generating processes in the mean-variance and mean-lower partial moment frameworks, analytical relationships between the CAPM beta and downside beta are derived. The derived relationships reveal that the association between the two systematic risk measures is to a great extent dependent on the volatility of the market portfolio returns and the deviation of the target rate from the risk-free rate. How the relationships derived here may be used in practice is demonstrated using empirical data.CAPM beta, downside beta, equilibrium pricing models, data generating processes, asset pricing

Investment performance appraisal and asset pricing models

Abstract not availabl

Relationship between systematic-risk measured in the second-order and third-order co-moments in the downside framework

The difference between systematic risk measured in terms of the third-order and second-order co-moment of returns in the downside framework is influenced by a factor associated with the market portfolio returns. Empirical evidence reveals that the smaller the spread in the returns in the market portfolio, the greater the influence of this factor. When measuring systematic risk in the downside, the choice of the order of co-moment is influenced by the variation in abnormal returns in the portfolios.