Primary: Asset Pricing (Macro-Finance, Derivatives, Empirical Asset Pricing)

Secondary: Macroeconomics (Business Cycles, Firm Investment) and Computational Methods


Macroeconomic Tail Risks and Asset Prices [RFS, SSRN, online appendix, code, errata]

  • Review of Financial Studies, August 2020, 33(8): 3541-3582

  • A parsimonious consumption-based asset pricing model that (i) rationalizes the equity premium based on low risk aversion and low consumption risk and (ii) is consistent with the main features of stock market risk premia implied by equity index options.

  • Presentations: AFA 2020, WFA 2018, SFS Cavalcade 2018, Arizona State University


Dissecting the Equity Premium, last updated 5/2021 [SSRN, online appendix]

with Tyler Beason

  • Revise & Resubmit at the Journal of Political Economy

  • We use options and return data to decompose risk premia into different parts of the return state space. This decomposition reveals that sources of the equity premium in leading asset pricing models differ substantially from those in the data. The discrepancy arises from unrealistically low risk prices for stock market tail events in the models.

  • Presentations: SITE 2021 -- Macro finance and Computation, SAFE Asset Pricing Workshop 2020, MFA 2020, Arizona State University, Carnegie Mellon University, University of Washington, University of Iowa, University of Alabama, Federal Reserve Board

Persistent Crises and Levered Asset Prices, last updated 9/2021 [SSRN]

with Lars-Alexander Kuehn and Florian Schulz

  • We structurally estimate an asset pricing model with persistent macroeconomic disasters and optimal capital structure decisions at the firm-level. The model replicates the behavior of bond and equity market risks DURING disasters -- a key data dimension that standard disaster models fail to capture.

  • Presentations (including coauthor presentations): AFA 2021, MFA 2021, SFS Cavalcade 2018, EFA 2018, Econometic Society Winter Meetings 2020, Minnesota Macro Asset Pricing conference 2017, FMA Conference on Derivatives and Volatility 2017, Unversity of Conneticut Risk Management Conference 2017, Arizona Jr Finance Conference 2020, Notre Dame, University of Muenster (Germany), University of Michigan, London Business School, City University of Hong Kong, University of Toronto

Volatility and the Pricing Kernel, NEW 11/2021 [SSRN]

with Tobias Sichert

  • We show empirically that negative stock market returns are significantly more painful to investors when they occur in periods of low volatility, which is reflected in a steeper pricing kernel. This fact is inconsistent with prominent explanations for the level and predictability of stock market returns.

  • Presentations (including coauthor presentations): Arizona State, Stockholm School of Economics, McGill, Princeton, Carnegie Mellon University (scheduled), Virtual Derivatives Workshop (scheduled), University of Oregon (scheduled)

Misallocation Cycles, last updated 11/2017 [paper]

with Cedric Ehouarne and Lars-Alexander Kuehn

  • A heterogeneous firm business cycle model with a power law in the firm size distribution. Idiosyncratic shocks cause recessions by inducing cyclical variation in the allocative efficiency of production factors.

  • Presentations: WFA 2017, AEA 2017, EFA 2016, SED 2016, Red Rock Finance Conference 2016, Duke-UNC Asset Pricing Conference 2016, Tepper-LAEF Conference 2015, Arizona Jr Finance Conference 2016, Arizona State University, Carnegie Mellon University, University of Southern California

Tails, Fears, and Equilibrium Option Prices (JMP), last updated 4/2016

  • A consumption-based asset pricing model with multifractal volatility in consumption growth. The model rationalizes the fact that excess returns are predictable at different frequencies by different predictors.

  • Presentations: SFS Cavalcade 2016, ESSFM Gerzensee 2016, Northwestern University, Duke University, Carnegie Mellon University Arizona State University, University of British Columbia, Penn State University, Georgetown University, HEC