On the Hansen-Jagannathan Distance with a No-Arbitrage Constraint
Concordia University, Quebec - Department of Economics
Federal Reserve Bank of Atlanta; EDHEC Risk Institute
University of Toronto - Rotman School of Management
March 28, 2012
We provide an in-depth analysis of the theoretical properties of the Hansen-Jagannathan (HJ) distance that incorporates a no-arbitrage constraint. Under a multivariate elliptical distribution assumption, we present explicit expressions for the HJ-distance with a no-arbitrage constraint, the associated Lagrange multipliers, and the SDF parameters in the case of linear SDFs. This allows us to analyze the benefits and costs of using the HJ-distance with a no-arbitrage constraint to rank models. Finally, we demonstrate the practical relevance of our theoretical findings in an empirical illustration of some popular asset pricing models.
Number of Pages in PDF File: 53
Keywords: Hansen-Jagannthan distrance, no-arbitrage constraint, model comparison
JEL Classification: G12, C12, C13working papers series
Date posted: January 13, 2010 ; Last revised: April 2, 2012
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