at the School Of Management, The University of Texas at Dallas, 800 W. Campbell Rd

Abstract In contrast to the current literature, we provide new evidence supporting a positive relation between idiosyncratic risk and the expected future market return. Since a large part of the idiosyncratic risk can be diversified away easily, the conventional aggregate idiosyncratic risk measures can only be noisy proxies for the undiversified idiosyncratic risk, which may be priced according to When Does Idiosyncratic Risk Really Matter? Abstract In contrast to the current literature, we provide new evidence supporting a positive relation between idiosyncratic risk and the expected future market return. Since a large part of the idiosyncratic risk can be diversified away easily, the conventional aggregate idiosyncratic risk measures can only be noisy proxies for the undiversified idiosyncratic risk, which may be priced according t

When Does Idiosyncratic Risk Really Matter? When Does Idiosyncratic Risk Really Matter?

Abstract Theories suggest that undiversified idiosyncratic risk can be priced, which implies its ability to predict future returns. However, existing empirical studies that use aggregate idiosyncratic risk measures as proxies for undiversified idiosyncratic risk have provided weak or ambiguous evidence. When undiversified idiosyncratic risk is relatively small, these proxies are likely to be dominated by noise. We propose a predictive regression using a simple dual-predictor (a pair of noisy proxies) to provide a more powerful test. The dual-predictor regression creates a noise-reduction mechanism from the highly correlated noise components in the pair of noisy proxies and uncovers a robust positive relationship between undiversified idiosyncratic risk and expected future market returns. Our dual predictor explains more than 4% of the variation in future market returns. Such predictive power is not only robust to the inclusion of other popular predictors, to the choices of sample periods and market indexes, and to the exclusion of extreme market movements, but also economically significant. Preprint submitted to Elsevier November 17, 2011 When Does Idiosyncratic Risk Really Matter? Abstract Theories suggest that undiversified idiosyncratic risk can be priced, which implies its ability to predict future returns. However, existing empirical studies that use aggregate idiosyncratic risk measures as proxies for undiversified idiosyncratic risk have provided weak or ambiguous evidence. When undiversified idiosyncratic risk is relatively small, these proxies are likely to be dominated by noise. We propose a predictive regression using a simple dual-predictor (a pair of noisy proxies) to provide a more powerful test. The dual-predictor regression creates a noise-reduction mechanism from the highly correlated noise components in the pair of noisy proxies and uncovers a robust positive relationship between undiversified idiosyncratic risk and expected future market returns. Our dual predictor explains more than 4% of the variation in future market returns. Such predictive power is not only robust to the inclusion of other popular predictors, to the choices of sample periods and market indexes, and to the exclusion of extreme market movements, but also economically significant