Generalized Recovery

66 Pages Posted: 5 Feb 2018

See all articles by David Lando

David Lando

Copenhagen Business School

Lasse Heje Pedersen

AQR Capital Management, LLC; Copenhagen Business School - Department of Finance; New York University (NYU); Centre for Economic Policy Research (CEPR)

Christian Skov Jensen

Bocconi University

Multiple version iconThere are 2 versions of this paper

Date Written: January 2018

Abstract

We characterize when physical probabilities, marginal utilities, and the discount rate can be recovered from observed state prices for several future time periods. We make no assumptions of the probability distribution, thus generalizing the time-homogeneous stationary model of Ross (2015). Recovery is feasible when the number of maturities with observable prices is higher than the number of states of the economy (or the number of parameters characterizing the pricing kernel). When recovery is feasible, our model is easy to implement, allowing a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return and other recovered statistics.

Keywords: asset pricing theory, financial economics, pricing kernel, risk aversion

JEL Classification: G00, G1, G12, G13, G17

Suggested Citation

Lando, David and Pedersen, Lasse Heje and Jensen, Christian Skov, Generalized Recovery (January 2018). CEPR Discussion Paper No. DP12665. Available at SSRN: https://ssrn.com/abstract=3118293

David Lando (Contact Author)

Copenhagen Business School ( email )

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark
+45 3815 3600 (Fax)

Lasse Heje Pedersen

AQR Capital Management, LLC ( email )

Greenwich, CT
United States

Copenhagen Business School - Department of Finance ( email )

Solbjerg Plads 3
Frederiksberg, DK-2000
Denmark

New York University (NYU) ( email )

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Christian Skov Jensen

Bocconi University ( email )

Via Roentgen 1
Milano, MI 20136
Italy

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