- Empirical Asset Pricing
- Empirical Option Pricing
- Financial Econometrics
- Risk Management
Variance Premium, Downside Risk, and Expected Stock Returns , Nov. 2017 (with Bruno Feunou, Roméo Tédongap, Lai Xu), Online Appendix
Abstract: We decompose the total variance into a bad and good component and measure the premiums associated with their fluctuations using stock and corresponding option data from a large cross-section of firms. The total variance risk premium (VRP) represents the premium paid to insure against fluctuations in bad variance (called bad VRP) net of the premium received to compensate for fluctuations in good variance (called good VRP). Bad VRP provides a direct assessment of the degree to which asset downside risk may become extreme, while good VRP proxies for the degree to which asset upside potential may shrink. We find that bad VRP is important economically as in the cross-section, its two standard deviation increase is associated with an up to 25% rise in annualized expected excess returns. Simultaneously going long stocks with high and short stocks with low bad VRP yields an annualized risk-adjusted expected excess return of 18%. This result remains significant in double-sort strategies and cross-sectional regressions controlling for a host of firm characteristics and exposures to regular and downside risk factors.
Presented at: The 6th Annual OptionMetrics’ Research Conference; ESSEC Business School’s 4th Empirical Finance Workshop.
Option-implied Idiosyncratic and Systematic Risk in the Cross-section of Expected Stock Returns, Nov. 2015
Abstract: I introduce a model-based approach to estimate higher order idiosyncratic moments and co-moments (co-skewness and co-kurtosis) of individual equities exclusively from the cross-section of option prices, including the full spectrum of available maturities and strike prices. These estimates are forward-looking and can, thus, be interpreted as truly ex-ante conditional measures of risk. Using standard cross-sectional asset pricing tests, I show that ex-ante moments help explain the cross-section of expected stock returns beyond traditional asset pricing factors, firm characteristics, and ex-post measures of moments. Specifically, I find that idiosyncratic volatility, idiosyncratic skewness and co-skewness are significantly negatively related to expected returns, while co-kurtosis shows a significantly positive relationship. Ex-ante moments are economically significant. A one-standard-deviation increase in idiosyncratic volatility, for example, leads to a 4.44% drop in annual expected returns.
Presented at: The Society for Financial Econometrics Summer School at the Harvard Deparment of Statistics; Stockholm School of Economics; Stockholm Business School; Sveriges Riksbank; National PhD Workshop in Finance, Swedish House of Finance.
Option Pricing with Stochastic Conditional Skewness, Nov. 2015
Abstract: I develop an affine discrete time multivariate stochastic volatility model. The model allows for the leverage effect and time-varying conditional skewness. I show that this model keeps the same structure under the risk-neutral measure, which yields semi-closed form option prices. The flexibility of the model allows idiosyncratic or common shocks (or factor innovations) to drive a specific group of assets, as well as a particular asset being driven by one or several idiosyncratic shocks (or factor innovations). In a particular specification, I introduce a model for pricing individual equity options that allows for time-varying market betas and stochastic higher order moments. Finally, I show that this model provides a good fit of the option data for the S&P500 and a large cross-section of companies during the period of 1996 to 2012.
Presented at: The Society for Financial Econometrics Summer School at the Harvard Deparment of Statistics; Stockholm School of Economics; PhD Nordic Finance Workshop, Aalto University.