This paper calibrates a class of jump-diffusion long-run risks (LRR) models to quantify how well they can jointly explain the equity risk premium and the variance risk premium in the U.S. financial markets, and whether they can generate realistic dynamics of riskneutral and realized...

We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

We study whether option-implied conditional expectation of market loss due to tail events, or tail loss measure, contains information about future returns, especially the negative ones. Our tail loss measure predicts future market returns, magnitude, and probability of the market crashes, beyond...

This paper introduces a new out-of-sample forecasting methodology for monthly market returns using the variance risk premium (VRP) that is both statistically and economically significant. This methodology is motivated by the `beta representation,' which implies that the market risk premium is...

This paper introduces a novel, option-free methodology to calculate the tail risk premium for individual stocks, and examines the characteristics of this premium in the cross section of stock returns. The existence of a premium for bearing negative tail risk is significantly associated with...

The risk premium of stocks due to priced variance risk is summarized to two variables -- the stock-specific price of variance risk (the difference between realized and option-implied variance) and the quantity (i.e., how stock prices respond to their variance shocks) of variance risk....

We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the quality of their return forecasts. In the low signal-to-noise environment of a one month horizon, we find that it is preferable to rely on a theory-based approach instead of engaging...

We examine the pricing of tail risk in international stock markets. We find that the tail risk of different countries is highly integrated. Introducing a new World Fear index, we find that local and global aggregate market returns are mainly driven by global tail risk rather than local tail...

We propose a novel method to estimate risk-neutral quantiles that uses sorting to minimize an objective function given by a convex combination of call and put option prices over the range of available strike prices. We demonstrate that this new method significantly improves the accuracy of...