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Evaluating asset pricing models using the second Hansen-Jagannathan distance

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  • Li, Haitao
  • Xu, Yuewu
  • Zhang, Xiaoyan
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    Abstract

    We develop a specification test and a sequence of model selection procedures for non-nested, overlapping, and nested models based on the second Hansen-Jagannathan distance, which requires a good asset pricing model to not only have small pricing errors but also be arbitrage free. Our methods have reasonably good finite sample performances and are more powerful than existing ones in detecting misspecified models with small pricing errors but are not arbitrage-free and in differentiating models that have similar pricing errors of a given set of test assets. Using the Fama and French size and book-to-market portfolios, we reach dramatically different conclusions on model performances based on our approach and existing methods.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Financial Economics.

    Volume (Year): 97 (2010)
    Issue (Month): 2 (August)
    Pages: 279-301

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    Handle: RePEc:eee:jfinec:v:97:y:2010:i:2:p:279-301

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    Web page: http://www.elsevier.com/locate/inca/505576

    Related research

    Keywords: Stochastic discount factor Specification test Model selection Hansen-Jagannathan distance Arbitrage;

    References

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    Cited by:
    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2011. "Chi-squared tests for evaluation and comparison of asset pricing models," Working Paper 2011-08, Federal Reserve Bank of Atlanta.
    2. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    3. Hammami, Yacine & Lindahl, Anna, 2014. "An intertemporal capital asset pricing model with bank credit growth as a state variable," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 14-28.
    4. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.

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