This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of … an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are … studied separately. We start from the historical trend in the magnitude of risk and then turn to the relation between …

IVOL and returns) is a missing risk factor. We show analytically that if IVOL proxies for a missing risk factor, then the … risk factors. Overall, our results suggest that both diversifiable (i.e., true idiosyncratic risk) and non …-diversifiable risk play a role in explaining the IVOL puzzle …

I use classification-based machine-learning methods to decompose 32 anomaly payoffsinto risk exposures and mispricing …. The component driven by risk earns statistically insignificantreturns, despite its efficacy in explaining the time … biased expectations, whereas risk exposures playan important role in explaining the time-series variation in anomaly returns …

idiosyncratic risk is priced, greater price inefficiency could be associated with higher expected returns. Consistent with this … price inefficiency is not explained by traditional risk factors, illiquidity, or transactions costs. It is also evidently … expected stock returns, and new supporting evidence that idiosyncratic risk is priced …