Jessica A. Wachter is with the Department of Finance, The Wharton School. For helpful comments, I thank Robert Barro, John Campbell, Mikhail Chernov, Gregory Duffee, Xavier Gabaix, Paul Glasserman, Francois Gourio, Campbell Harvey, Dana Kiku, Bruce Lehmann, Christian Juillard, Monika Piazzesi, Nikolai Roussanov, Jerry Tsai, Pietro Veronesi, and seminar participants at the 2008 NBER Summer Institute, the 2008 SED Meetings, the 2011 AFA Meetings, Brown University, the Federal Reserve Bank of New York, MIT, University of Maryland, the University of Southern California, and The Wharton School. I am grateful for financial support from the Aronson+Johnson+Ortiz fellowship through the Rodney L. White Center for Financial Research. Thomas Plank and Leonid Spesivtsev provided excellent research assistance.
Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?
Article first published online: 20 MAY 2013
© 2013 the American Finance Association
The Journal of Finance
Volume 68, Issue 3, pages 987–1035, June 2013
How to Cite
WACHTER, J. A. (2013), Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?. The Journal of Finance, 68: 987–1035. doi: 10.1111/jofi.12018
- Issue published online: 20 MAY 2013
- Article first published online: 20 MAY 2013
- Accepted manuscript online: 30 JAN 2013 12:31PM EST
- Manuscript Accepted: 2 JAN 2013
- Manuscript Received: 3 MAR 2009
Why is the equity premium so high, and why are stocks so volatile? Why are stock returns in excess of government bill rates predictable? This paper proposes an answer to these questions based on a time-varying probability of a consumption disaster. In the model, aggregate consumption follows a normal distribution with low volatility most of the time, but with some probability of a consumption realization far out in the left tail. The possibility of this poor outcome substantially increases the equity premium, while time-variation in the probability of this outcome drives high stock market volatility and excess return predictability.