Abstract
Following Hansen and Jagannathan (J. Finance 52 (1997) 557), Jagannathan and Wang (J. Finance 51 (1996) 3) propose a distance measure that estimates the maximum pricing error generated by a linear asset model. Jagannathan and Wang propose a test of this HJ-distance using an empirical p-value as an alternative generalized method of moments (GMM) measure to Hansen's (Econometrica 50 (1982) 1029) GMM specification test. Using Monte Carlo analysis, we examine the finite sample properties of these specification tests. While the Hansen test mildly overrejects correct models in commonly used sample size, the empirical p-value of the HJ-distance rejects correct models too severely in such samples to provide a valid test of such models.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 109-132 |
| Number of pages | 24 |
| Journal | Journal of Empirical Finance |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2004 |
Keywords
- Empirical p-value
- Finite sample properties
- Generalized method of moments
- Hansen-Jagannathan distance
- Pricing error
ASJC Scopus subject areas
- Finance
- Economics and Econometrics
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Ahn, S., & Gadarowski, C. (2004). Small sample properties of the GMM specification test based on the Hansen-Jagannathan distance. Journal of Empirical Finance, 11(1), 109-132. https://doi.org/10.1016/j.jempfin.2002.09.001