A Decomposition of Conditional Risk Premia and Implications for Representative Agent Models

177 Pages Posted: 1 Dec 2020 Last revised: 29 Jun 2021

See all articles by Fousseni Chabi-Yo

Fousseni Chabi-Yo

University of Massachusetts Amherst - Isenberg School of Management

Johnathan Loudis

University of Notre Dame - Mendoza College of Business

Date Written: June 28, 2021

Abstract

We develop a methodology to decompose the conditional market risk premium and risk premia on higher-order moments of excess market returns into components related to contingent claims on down, up, and moderate market returns. The decompositions do not depend on assumptions about investor preferences, nor do they depend on assumptions about the market return distribution. Analogous decompositions implied by prominent representative agent models fail to match those implied by the data. Our results provide a host of new empirical facts regarding sources of conditional risk premia and identify a set of new challenges for representative agent models.

Keywords: Market risk premium; Variance risk premium; Crash risk; Conditioning information; Risk-neutral moments; Preferences; Stochastic Discount Factor

JEL Classification: E44; G1; G12; G13

Suggested Citation

Chabi-Yo, Fousseni and Loudis, Johnathan, A Decomposition of Conditional Risk Premia and Implications for Representative Agent Models (June 28, 2021). Available at SSRN: https://ssrn.com/abstract=3734689 or http://dx.doi.org/10.2139/ssrn.3734689

Fousseni Chabi-Yo

University of Massachusetts Amherst - Isenberg School of Management ( email )

Amherst, MA 01003-4910
United States

Johnathan Loudis (Contact Author)

University of Notre Dame - Mendoza College of Business ( email )

Notre Dame, IN 46556-5646
United States

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