Cross-sectional Predictability of Indian Stock Returns: A Factor Analytical Approach
Keywords
asset pricing, returns predictability, Fama-MacBeth regression, arbitrage pricing, principal componentsAbstract
This article's core objective is to analyze how firm characteristics collectively effect the risk-adjusted returns of Indian stocks. It aims to understand the simultaneous explanatory power of multiple variables that have shown to predict the cross-sectional returns in prior studies. We include eight firm characteristics as determinants of expected returns - size, book-to-market equity, reciprocal of share price, volume traded, dividend yield and 3 lagged returns. The data consists of monthly returns and firm characteristics for a sample of listed securities which constitute the National Stock Exchange’s (NSE) NIFTY 100 Index. We use Arbitrage Pricing Theory with Connor and Korajczyk (1988) benchmark factors for risk adjusting returns on individual securities. We conduct Fama-MacBeth regressions to determine the statistical significance of the firm characteristics. We find that lags of size, book to market, dividend yield, and momentum have strong residual pricing power and in-sample predictability of risk adjusted returns. We also find that the intercepts are positive and highly significant. Thus, the average stock in the sample underperforms the risk model by a substantial amount. The results lead us to categorically reject Arbitrage Pricing Model with Connor and Korajczyk factors as a risk model for Indian stock returns.
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