Tail Risk and Asset Prices
提出一种直接从个股截面收益率估计时变尾部风险的新方法，发现该指标能预测市场回报，且高尾部风险暴露的股票年化超额收益比低暴露股票高5.4%。
We propose a new measure of time-varying tail risk that is directly estimable from the cross-section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk among individual stocks. Our tail measure is significantly correlated with tail risk measures extracted from S&P 500 index options and negatively predicts real economic activity. We show that tail risk has strong predictive power for aggregate market returns. Cross-sectionally, stocks with high loadings on past tail risk earn an annual three-factor alpha 5.4% higher than stocks with low tail risk loadings. We explore potential mechanisms giving rise to these asset pricing facts.