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Improvement in finite sample properties of the Hansen-Jagannathan distance test

Yu Ren and Katsumi Shimotsu

Journal of Empirical Finance, 2009, vol. 16, issue 3, pages 483-506

Abstract: Jagannathan and Wang [Jagannthan, R., and Wang, Z., "The conditional CAPM and the cross-section of expected returns." Journal of Finance, 51 (1996), 3-53] derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-distance) proposed by Hansen and Jagannathan [Hansen, L.P., and Jagannathan, R., Assessing specific errors in stochastic discount factor models." Journal of Finance, 52 (1997), 557-590], 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 [Ahn, S.C., and Gadarowski, C., "Small sample properties of the GMM specification test based on the Hansen-Jagannathan distance." Journal of Empirical Finance, 11 (2004), 109-132] 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, O., and Wolf, M., "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection." Journal of Empirical Finance, 10 (2003), 603-621] to compute its weighting matrix. The proposed method improves the finite sample performance of the HJ-distance test significantly.

Keywords: Covariance; matrix; estimation; Factor; models; Finite; sample; properties; Hansen-Jagannathan; distance; Shrinkage; method (search for similar items in EconPapers)
Date: 2009

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Working Paper: Improvement in Finite Sample Properties of the Hansen-Jagannathan Distance Test (2007) Downloads
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