PAWEL BILINSKI AND DANIELLE LYSSIMACHOU b1 The Risk Interpretation of the CAPM’s Beta: Evidence from a New Research Method

This study tests the validity of using the CAPM beta as a risk control in cross-sectional accounting and finance research. We recognize that high risk stocks should experience either very good or very bad returns more frequently compared to low risk stocks, i.e. high risk stocks should cluster in the tails of the cross-sectional return distribution. Building on this intuition, we test the risk interpretation of the CAPM’s beta by examining if high beta stocks are more likely than low beta stocks to experience either very high or very low returns. Our empirical results indicate that beta is a strong predictor of large positive and large negative returns, which confirms that beta is a valid empirical risk measure and that researchers should use beta as a risk control in empirical tests. Further, we show that because the relation between beta and returns is U-shaped, i.e. high betas predict both very high and very low returns, linear cross-sectional regression models, e.g. Fama-MacBeth regressions, will fail on average to reject the null hypothesis that beta does not capture risk. This result explains why previous studies find no significant cross-sectional relation between beta and returns.

Key words: Market beta; New research method; Empirical accounting and finance research.

PAWEL BILINSKI (pawel.bilinski.1@city.ac.uk) and DANIELLE LYSSIMACHOU (danielle.lyssimachou.1@city.ac.uk) are Associate Professors of Accounting at Cass Business School, City University London. The authors would like to thank Michael Brennan, Paul Griffin, Gilad Livne and Peter Pope for helpful comments.

INTRODUCTION The capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965) lies at the heart of empirical accounting and finance research.1