We derive a model-free option-based formula to estimate the contribution of market frictions to expected returns (CFER) within an asset pricing setting. We estimate CFER for the U.S. optionable stocks. We document that CFER is sizable, it predicts stock returns and it subsumes the effect of...

This paper studies volatility spillovers in credit default swaps (CDS) between the corporate sectors and Latin American countries. Daily data from October 14, 2006, to August 23, 2021, are employed. Spillovers are computed both for the raw data and for filtered series which factor out the effect...

We examine whether the option market leads the stock market with respect to positive in addition to negative price discovery. We document that out-of-themoney (OTM) option prices, which determine the Risk-Neutral Skewness (RNS) of the underlying stock return's distribution, can embed positive...

This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models such as Generalized Autoregressive Conditional...

This paper decomposes the risk premia of individual stocks into contributions from systematic and idiosyncratic risks. I introduce an affine jump-diffusion model, which accounts for both the factor structure of asset returns and that of the variance of idiosyncratic returns. The estimation is...

This paper studies the information content of the S&P 500 and VIX markets on the volatility of the S&P 500 returns. We estimate a flexible affine model based on a joint time series of underlying indexes and option prices on both markets. An extensive model specification analysis reveals that...

We explore whether the market variance risk premium (VRP) can be predicted. First, we propose a novel approach to measure VRP which distinguishes the investment horizon from the variance swap's maturity. We extract VRP from actual rather than synthetic S&P 500 variance swap quotes, thus avoiding...