Nonparametric Tail Risk, Stock Returns and the Macroeconomy

This paper introduces a new tail risk measure based on the risk-neutral excess expected shortfall. We propose a novel way to compute risky measures that incorporate risk neutral probabilities, without relying on option price information, from a cross section of assets returns. Empirically, we illustrate our methodology by estimating tail risk from the cross-section of the 25 Fama-French size and book-to-market portfolios. Our main results are twofold: from the assets cross-section perspective we find a premium related to downside risk, even when controlling for typical factors. Our tail risk index also provides meaningful information about future market returns and aggregate U.S. macroeconomic conditions and is straight-forwardly related to other tail downside risk measures. These results are robust to the choice of cross-sectional information retained to compute the tail risk measure. Moreover, our methodology is applicable to a broad set of assets and markets and can be used readily by regulators and risk managers.