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.
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