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Higher-Moment Model with Errors-in-Variables: An Examination with Cross Section of Expected Returns

This paper proposes measures of systematic skewness and systematic kurtosis as symmetric measures of risk by extending the work of Kraus and Litzenberg (1976). We examine an asset pricing model that incorporates systematic skewness and systematic kurtosis to test the cross section of asset returns within the context of the Fama and MacBeth (1973) two-pass estimation methodology. However, this estimation suffers from the errors-in-variables (EIV) problems that could attenuate the significance of risk premium betas. We propose the Dagenais and Dagenais (1997) higher-moment estimators as a solution for the EIV problems. Our results suggest that although the EIV correction leads to a diminished role of the market beta, the systematic skewness and systematic kurtosis still retain their significance in explaining the cross section of expected returns.