6. Default Risk and Option Returns with Aurelio Vasquez 

Management Science, 70.4 (2024): 2144-2167. 

Delta-hedged option returns have a negative relation with default risk measured by credit ratings or default probability. The results are consistent with a stylized capital structure model where the negative relation is driven by firm leverage and asset volatility.

5. Why Does Volatility Uncertainty Predict Equity Option Returns? 

with Jay Cao, Aurelio Vasquez and Xintong Zhan

Quarterly Journal of Finance (2023), 13.1: 2350005

Uncertainty of volatilities amplifies the model risk, leading to a higher option premium charged by dealers. Volatility of volatility-increases, rather than that of volatility-decreases, contributes to the effect of implied volatility uncertainty, supporting the gambling-preference channel. 

4. Implied Volatility Changes and Corporate Bond Returns with Jay Cao, Amit Goyal and Xintong Zhan

Management Science (2023),  69.3: 1375-1397 

Option implied volatility change has significant cross-sectional predictive power for the underlying firms’ bond returns. The sign of predictability is different for bond returns and stock returns, consistent with Merton's capital structure model. 

3. Equity Tail Risk and Currency Risk Premia, with Juan M. Londono and Zhenzhen Fan

Journal of Financial Economics (2022), 143.1: 484-503 

A portfolio that buys currencies with high equity tail beta and shorts those with low beta extracts the global component in the tail factor. The global tail factor is priced in currency carry and momentum portfolios, among other asset classes.

2. Moment Risk Premia and Stock Return Predictability  with Hao Zhou and Zhenzhen Fan

Journal of Financial and Quantitative Analysis (2022), 57.1: 1-27 

Combining the higher moment risk premia with the second moment risk premium improves the stock market predictability over multiple horizons, both in-sample and out-of-sample.

7. Common Factors in Equity Option Returns with Aurelio Vasquez and Alex Horenstein, R&R 2nd Round

FMA 2019, CICF 2019, EasternFA 2019, MidwestFA 2019

Project funded by Canadian Derivatives Institute

This paper studies the factor structure in the cross-section of delta-hedged equity option returns. Using latent factor techniques, we find strong evidence for the existence of a factor structure in equity options returns. We propose a four-factor model, which captures relevant latent factors and explains the time series and cross-section of equity option returns. The factors are the market volatility risk factor and three characteristic-based factors related to firm size, idiosyncratic volatility, and the difference between implied and historical volatilities. Stock return factors cannot price the cross-section of equity option returns. 

9. Factor Selection in the Cross-section with Chuanping Sun

We examine a new approach to selecting asset pricing factors in the factor zoo. Our novel method can: (1) identify a set of factors that have incremental information for explaining the cross-section of asset returns; (2) establish a hierarchical order to explain the importance of factors; (3) quantify unique contributions of each factor; and (4) address which factors can be subsumed by others and to what extent. In a simulation study with multiple settings for factor structures, we demonstrate that our method outperforms both stepwise regression (i.e., forward selection and backward selection) and LASSO regression. Empirically, we find that selected factors are dense instead of sparse in the stock market, corporate bond market, and options market.