risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to …

. Options whose lives span political events tend to be more expensive. Such options provide valuable protection against the risk … associated with political events, including not only price risk but also variance and tail risks. This protection is more …

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 across stocks. Our tail measure is … significantly correlated with tail risk measures extracted from S&P 500 index options, but is available for a longer sample since it …

classes such as corporate and sovereign bonds, derivatives, commodities, and currencies. Our intermediary capital risk factor … is strongly pro-cyclical, implying counter-cyclical intermediary leverage. The price of risk for intermediary capital …

We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news … change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk … approaches to managing climate risk …

exposure to latent risk factors, IPCA will identify the corresponding latent factors. If no such factors exist, IPCA infers … that the characteristic effect is compensation without risk and allocates it to an "anomaly" intercept. Studying returns …