References (63)


Citations (2)



Economic Implications of Nonlinear Pricing Kernels

Caio Almeida

Getulio Vargas Foundation

René Garcia

EDHEC Business School

July 15, 2015

AFA 2009 San Francisco Meetings Paper

Based on a family of discrepancy functions, we derive nonparametric stochastic discount factor (SDFs) bounds that naturally generalize variance (Hansen and Jagannathan, 1991), entropy (Backus, Chernov and Martin, 2011), and higher-moment (Snow, 1991) bounds. These bounds are especially useful to identify how parameters affect pricing kernel dispersion in asset pricing models. In particular, they allow us to distinguish between models where dispersion comes mainly from skewness from models where kurtosis is the primary source of dispersion. We analyze the admissibility of disaster, disappointment aversion and long-run risk models with respect to these bounds.

Number of Pages in PDF File: 41

Keywords: Stochastic Discount Factor, Information-Theoretic Bounds, Generalized Minimum Contrast Estimators, Implicit Utility Maximizing Weights

JEL Classification: C1, C5, G1

Open PDF in Browser Download This Paper

Date posted: March 25, 2008 ; Last revised: July 16, 2015

Suggested Citation

Almeida, Caio and Garcia, René, Economic Implications of Nonlinear Pricing Kernels (July 15, 2015). AFA 2009 San Francisco Meetings Paper. Available at SSRN: http://ssrn.com/abstract=1107997 or http://dx.doi.org/10.2139/ssrn.1107997

Contact Information

Caio Almeida (Contact Author)
Getulio Vargas Foundation ( email )
Praia de Botafogo 190, 11o andar
Rio de Janeiro, Rio de Janeiro 22250-900
5521-37995827 (Phone)
5521-2553-8821 (Fax)
HOME PAGE: http://www.fgv.br/professor/calmeida/
René Garcia
EDHEC Business School ( email )
58 rue du Port
Lille, 59046
Feedback to SSRN

Paper statistics
Abstract Views: 2,592
Downloads: 465
Download Rank: 44,532
References:  63
Citations:  2

© 2016 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollobot1 in 2.531 seconds