Job Market Paper:

Generalized Disappointment Aversion, Learning, and Asset Prices

    • Winner of the 2017 Young Economist of the Year Award, Czech Economics Society
    • Winner of the 2017 Best Paper in Theoretical Economics, Czech Econometric Society

Contrary to leading asset pricing theories, recent empirical evidence indicates that it was costless to hedge long-term volatility in aggregate stock market returns over the last two decades, whereas investors paid large premia for insurance against the unexpected realized variance. This paper offers a generalized disappointment aversion explanation that can also account for the variance and skew risk premiums in equity returns and the implied volatility skew of index options. The model captures other puzzling features of the data including the low risk-free rate, the high equity premium, excess stock market volatility, and return predictability patterns.

Working Papers:

Parameter Learning in Production Economies

with Roman Kozhan

We examine how parameter learning amplifies the impact of macroeconomic shocks on equity prices and quantities in a standard production economy where a representative agent has Epstein-Zin preferences. An investor observes technology shocks which follow a regime-switching process but does not know the underlying model parameters governing the short-term and long-run perspectives of economic growth. We show that rational parameter learning endogenously generates long-run productivity and consumption risks that help explain a wide array of dynamic pricing phenomena. The asset pricing implications of subjective long-run risks crucially depend on the introduction of a procyclical dividend process consistent with the data.

Option Prices and Learning about Productivity Dynamics | Preliminary draft available on request | Slides

with Roman Kozhan

We demonstrate that incorporating rational pricing of parameter uncertainty in a production economy can jointly explain index option prices, equity returns, the risk-free rate, and macroeconomic quantities. A representative investor learns about the true structure of a two-state Markov switching process for productivity growth. Rational parameter learning amplifies the conditional risk premium and volatility especially at the onset of recessions. We estimate the model based on the post-war U.S. data and find that it can capture the implied volatility surface and the variance premium. Intuitively, the agent pays a large premium for index options because they hedge future belief revisions.

Work in Progress:

Uncertainty, Time-Varying Beliefs, and the Exchange Rate

with Roman Kozhan

Learning about Productivity Slowdown