A Cross-Sectional Investigation of the Conditional ICAPM

Abstract

This paper provides a cross-sectional investigation of the conditional and unconditional intertemporal capital asset pricing model (ICAPM). The results indicate that estimating the conditional ICAPM with a pooled panel of time series and cross-sectional data in a multivariate GARCH-in-mean framework is crucial in identifying the positive risk-return tradeoff. Different from the traditional literature, the paper decomposes the aggregate stock market portfolio into ten book-to-market portfolios and then estimates a cross-sectionally consistent slope coefficient on the conditional variance-covariance matrix. The riskaversion coefficient, restricted to be the same across all portfolios, is estimated to be positive and highly significant. This is the first study testing the cross-sectional consistency of the intertemporal relation by estimating the multivariate GARCH-in-mean model with different slopes. The statistical results indicate the equality of slope coefficients across all portfolios, supporting the empirical validity and sufficiency of the conditional ICAPM. The paper also provides evidence that the time-varying conditional covariances can explain the value premium because the average risk-adjusted return difference between the value and growth portfolios is economically and statistically insignificant within the conditional ICAPM framework.