Research

Publications

Conditional risk and the pricing kernel (with David Schreindorfer) (Journal, SSRN, online appendix, code)

Journal of Financial Economics, forthcoming
SIX Best Paper Award, Annual Conference of the Swiss Society for Financial Market Research, 2023
We propose a methodology for jointly estimating the pricing kernel and conditional physical return densities from option prices. Pricing kernel estimates show that negative stock market returns are significantly more painful to investors in low-volatility periods. Density estimates reflect a significantly positive risk–return trade-off, and provide new evidence on equity premium bounds, variance premium’s predictive power for returns as well as the co-movement between higher return moments.
Presentations (including coauthor presentations): Arizona State, Stockholm School of Economics, McGill, Princeton, Carnegie Mellon University, Goethe University, University of Oregon, University of Amsterdam, ITAM, Michigan State, University of Georgia, University of Iowa, University of Oregon, University of Virginia, Vanderbilt University, BMRG Conference on Macro and Financial Economics, Virtual Derivatives Workshop, EFA, CICF, SoFIE annual conference, BI-SHoF Conference, Junior European Finance Seminar, FMA Conference on Derivatives and Volatility, MFA, SGF, AFA

Working Papers

We find that the expected return of the underlying stock fails to forecast option returns, but does explain cross-sectional variation in option prices. These findings challenge canonical option pricing models and suggest that options are not a suitable instrument to harvest stock risk premia.

Presentations: Virtual Derivatives Workshop, CFF Finance Conference

I show that non-linear pricing of market risk can explain many prominent cross-sectional stock return anomalies such as momentum, betting-against-beta, idiosyncratic volatility, and liquidity. A key feature of the model is a sizable upside risk premium of approximately 4% per annum. The results can be explained with a compensation for exposure to systematic variance risk.
Scheduled for Presentation at: FMA/CBOE Derivatives and Volatility 2024
Presentations: WFA, SFS Cavalcade NA, European Winter Finance Summit, ESSFM in Gerzensee, SGF, SED, JEF Conference, DGF, Swedish Conference in Economics, NFN, Asset Pricing Conference by LTI (Turin), FMA/CBOE Derivatives and Volatility, Erasmus Rotterdam, Arizona State, Göteborg, Princeton

We show that, with priced variance risk, expected returns of out-of-the-money calls are negative and decreasing in moneyness. Furthermore, we provide a new perspective on the relationship between idiosyncratic volatility and expected call returns varies. While expected returns are decreasing in idiosyncratic volatility for at-the-money calls, we show that, for out-of-the-money calls, the opposite is true. Finally, our results offer an explanation for several option return anomalies previously attributed to lottery preferences.
Presentations: Liverpool Workshop in Option Markets, Virtual Derivatives Workshop, FMA/CBOE Derivatives and Volatility, NFN Young Scholars Finance Webinar Series, Carnegie Mellon University, University of Alabama

Based on a novel GARCH model with structural breaks, I show that the pricing kernel is consistently U-shaped. The main driver of the change in results is a correction of otherwise biased return volatility forecast of standard GARCH models.
Presentations: AFA, TADC, NFA, SGF, AFFI, Carnegie Mellon University, Collegio Carlo Alberto, Goethe University, Nova School of Business and Economics, Stockholm School of Economics, University of Toronto, University of Zurich, Warwick University

Work in Progress

Machine Learning Option Returns, joint with Adrien d'Avernas, Christian Schlag, Martin Waibel and Chunjie Wang

The Pricing of Higher Moment Risk in Stock Returns – New Evidence, joint with Caio Almeida and Gustavo Freire

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