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Improvement in Finite Sample Properties of the Hansen-Jagannathan Distance Test

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  • Yu Ren

    ()
    (Queen's University)

  • Katsumi Shimotsu

    ()
    (Queen's University)

Abstract

Jagannathan and Wang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-distance) proposed by Hansen and Jagannathan (1997), and develop a specification test of asset pricing models based on the HJ-distance. While the HJ-distance has several desirable properties, Ahn and Gadarowski (2004) find that the specification test based on the HJ-distance overrejects correct models too severely in commonly used sample size to provide a valid test. This paper proposes to improve the finite sample properties of the HJ-distance test by applying the shrinkage method (Ledoit and Wolf, 2003) to compute its weighting matrix. The proposed method improves the finite sample performance of the HJ-distance test significantly.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1126.pdf
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1126.

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Length: 38 pages
Date of creation: Jun 2007
Date of revision:
Handle: RePEc:qed:wpaper:1126

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Keywords: Covariance matrix estimation; Factor models; Finite sample properties; Hansen-Jagannathan distance; Shrinkage method;

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References

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Cited by:
  1. repec:wyi:journl:002162 is not listed on IDEAS
  2. Qihui Chen & Yu Ren, 2013. "Improvement in finite-sample properties of GMM-based Wald tests," Computational Statistics, Springer, vol. 28(2), pages 735-749, April.

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