Published August 7, 2017
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An Agnostic and Practically Useful Estimator of the Stochastic Discount Factor
- Creators
- Pukthuanthong, Kuntara
- Roll, Richard
Abstract
We propose an estimator for the stochastic discount factor (SDF) which is agnostic because it does not require macroeconomic proxies or preference assumptions. It depends only on observed asset returns. Nonetheless, it is immune to the form of the multivariate return distribution, including the distribution's factor structure. Putting our estimator to work, we find that a unique positive SDF prices all U.S. asset classes and satisfies the Hansen/Jagannathan variance bound. In contrast, the Chinese and Indian equity markets do not share the same SDF and hence do not seem to be integrated.
Additional Information
Revised October 19, 2016. Acknowledgements: For many helpful comments and suggestions on previous drafts, we are indebted to Viral Acharya, Tobias Adrian, Serena Agoro-Menyang, Yakov Amihud, Antonio Bernardo, Michael Brennan, Menachem Brenner, Mikhail Chernov, Bhagwan Chowdhry, John Cochrane, Harry DeAngelo, Eric DeBodt, Federico Echenique, Robert Engle, Michael Ewens, Wayne Ferson, Steve Figlewski, Ben Gillen, Lars Hansen, Raymond Kan, Shiki Levy, Francis Longstaff, John McConnell, Hugh McCulloch, Tyler Muir, Andrew Patton, Michael O'Doherty, Stephen Ross, Grigory Vilkov, Kenneth Winston, Rui Yu, Goufu Zhou, and participants in the Caltech and UCLA Brown Bag seminars, the Amundi Paris Dauphine annual workshop and the Stern School Volatility Institute Seminar at New York University.Attached Files
Submitted - sswp1405.pdf
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Additional details
- Eprint ID
- 79412
- Resolver ID
- CaltechAUTHORS:20170726-110645423
- Created
-
2017-08-07Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 1405