Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance

Patrick Gagliardini*, Diego Ronchetti

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)
180 Downloads (Pure)

Abstract

We compare nonnested parametric specifications of the stochastic discount factor (SDF) using the conditional Hansen-Jagannathan (HJ-) distance. This distance measures the discrepancy between a parametric model-implied SDF and the admissible SDF's satisfying all the conditional (dynamic) no-arbitrage restrictions, instead of just few unconditional no-arbitrage restrictions for managed portfolios chosen through the instrument selection. We estimate the conditional HJ-distance by a generalized method of moments estimator and establish its large sample properties for model selection purposes. We compare empirically several SDF models including multifactor beta pricing specifications and some recently proposed SDF models that are conditionally linear in consumption growth.

Original languageEnglish
Pages (from-to)333-394
Number of pages62
JournalJournal of Financial Econometrics
Volume18
Issue number2
Early online date19-Apr-2019
DOIs
Publication statusPublished - 2020

Keywords

  • asset pricing model comparison
  • generalized method of moments
  • Hansen-Jagannathan distance
  • nonparametric estimation
  • stochastic discount factor
  • CROSS-SECTIONAL TEST
  • SPECIFICATION ERRORS
  • GENERALIZED-METHOD
  • TEMPORAL BEHAVIOR
  • RISK-AVERSION
  • SELECTION
  • TESTS
  • CONSUMPTION
  • INFERENCE
  • RETURNS

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