High Frequency Tail Risk
57 Pages Posted: 31 Jul 2018
Date Written: July 11, 2018
This paper proposes an alternative way to measure high-frequency Tail Risk directly extracted from stocks returns: A risk-neutral mean-adjusted expected shortfall. We rely on a non-parametric estimator for the state price density based on Hellinger's distance to risk-neutralize returns. Since the measure dispenses option prices, it can be potentially applied to a broader number of markets than corresponding option-based measures. Empirically, our tail risk factor extracted from S&P 500 returns has a 90% correlation with the VIX index. We document a persistent negative relation between tail risk and one-day ahead returns, for different assets. Consistent with the crash-insurance property of put options, tail risk predicts positive one-day ahead returns for portfolios long out-of-the-money, short in-the-money put options. An analysis of stock portfolios sorted on exposure to tail risk reveals a premium for bearing such a risk, even when controlling for known and established factors related to cross-section variability. The cross-sectional analysis is also robust to the inclusion of uncertainty indexes, macroeconomic and volatility measures.
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