Evidence to Support Multifactor Asset Pricing Models: Case of Indian Stock Market

Abstract

Emerging stock market returns have been extensively studied by the academic community over the past two decades. However, there is still no consensus among the researchers and practitioners as to which asset pricing models should be used to explain returns in these markets. The fundamental objective of the study is to evaluate the power and performance of multifactor asset pricing models (three-and four-factor models) over the traditional one-factor capital asset pricing model (CAPM), using the data from one of the fastest growing emerging markets: India. The study, using a large sample data of 470 listed stocks over a period of 16 years stretching from January 1997 to March 2013, evaluates the relevance of Fama and French three-factor model as well as liquidity augmented four-factor model in explaining the stock return variations in the Indian stock market. The study employs time series regression approach to examine the impact of market risk, size risk, value risk and liquidity risk on stock returns. The overall results of the study provide support to the multidimensional nature of risk and suggest the use of multifactor asset pricing models for consideration in investment decisions. Both Fama and French three-factor model and liquidity augmented four-factor model were found to be superior to traditional one-factor CAPM, though liquidity increased four-factor model was found to be slightly better in explaining Indian stock returns as compared with Fama and French three-factor model.