On the properties of the constrained Hansen–Jagannathan distance

Nikolay Gospodinov, Raymond Kan and Cesare Robotti

Journal of Empirical Finance, 2016, vol. 36, issue C, 121-150

Abstract: 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 stochastic discount factor (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 evaluate and rank models. We also study the asymptotic and finite-sample properties of the sample constrained HJ-distance. Finally, we demonstrate the practical relevance of our theoretical findings in an empirical illustration of some popular asset-pricing models.

Keywords: No-arbitrage; Constrained Hansen-Jagannathan distance; Asset-pricing models; Linear SDFs; Equity pricing (search for similar items in EconPapers)
JEL-codes: C12 C13 G12 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:36:y:2016:i:c:p:121-150

DOI: 10.1016/j.jempfin.2015.10.001

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