Market betas have a strong and positive relation with average stock returns on a handful of days every year. Such unique days, defined as leading earnings announcement days (LEADs), are times when an aggregate of influential S&P 500 firms disclose quarterly earnings news early in the earnings season. The positive return-to-beta relation holds for various test portfolios, individual stocks, and Treasuries; and is robust to different data frequencies and testing procedures. On days other than LEADs, the beta-return relation is flat. We conclude that waves of early earnings announcements by large firms clustered on LEADs significantly influence asset pricing.

In this study, we provide empirical evidence that firm-level jump-induced tail risk (measured by a jump-implied variance contribution index [JIVX]) prospectively predicts cross-sectional stock returns around earnings announcements. The effect size is nontrivial. A practical trading strategy that buys announcers with high pre-news JIVX values and sells announcers with low pre-news JIVX values, earns a net risk-adjusted average return of 82 basis points (bps) three days after the news release. Notably, the empirical success of the JIVX predictor is distinct from model-free implied skewness and kurtosis measures and withstands a battery of robustness checks.