Evidence to Support Multifactor Asset Pricing Models: Case of Indian Stock Market
Emerging stock market returns have been extensively studied by 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 basic objective of the study is to evaluate the power and performance of multi factor asset pricing models (three and four factor model) over the traditional one factor CAPM, using the data from one of the fastest growing emerging market: 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, evaluate 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 multi dimensional nature of risk and suggest the use of multi factor 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 than traditional one factor CAPM. Though, liquidity augmented four factor model was found to be slightly better in explaining Indian stock returns as compared to Fama and French three factor model.