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

id:2093 时间:20131014 status:published 点击数:
杂志Journal of Empirical Finance   
作者Yu Ren, Katsumi Shimotsu
正文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.
JEL-Codes:C13; C52; G12.
关键词:Covariance matrix estimation; Factor models; Finite sample properties; Hansen-Jagannathan distance; Shrinkage method.
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