Hengjie Ai
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Preference, information and asset pricing

Information and long-run risk: asset pricing implications,   Journal of Finance, 2010, vol. 65, Issue 4, 1333-1367.

Asset pricing in a long-run risk model with learning. I show the effect of learning depends on IES and not risk-aversion. Learning explains many stylized facts in asset market returns.
  • Technical appendix
  • Numerical solution: the Markov chain approximation method
  • An earlier version that contains a decomposition of the welfare gain of information

Risk preferences and the macro announcement premium, with Ravi Bansal,  Volume86, Issue4, 
July 2018, Pages 1383-1430, Econometrica.

A revealed preference theory of the macro announcement premium. Generalized risk sensitivity is necessary to explain asset market fact. SFS Cavalcade 2017 best paper award in asset pricing.
  • The technical appendix for the paper
  • Slides for the paper
  • A simple proof for the main theorem in the finite dimensional case

Identifying preference for early resolution from asset market data, with Ravi Bansal, Hongye Guo, and Amir Yaron.​

Develop an asset pricing based test for preference for early resolution of uncertainty. Extend the revealed preference approach in Ai and Bansal (2018) to identify preference for early resolution of uncertainty from asset market data.

Information Acquisition and the Pre-Announcement Drift, with Ravi Bansal and Leyla Han.

A dynamic noisy rational expectations equilibrium model with endogenous information acquisition explains the pre-FOMC announcement drift and the volatility dynamics around FOMC announcements.

Information driven volatility, with Lai Xu and Leyla Jianyu Han.

Stochastic volatility in macroeconomic fundamentals is unlikely to explain the high-frequency volatility dynamics on financial markets. Develop an information-based model of stochastic volatility that explains several volatility-related puzzles.
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