Jagannathan andWang (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
A common statistical problem in finance is measuring the goodness-of-fit of a given distribution to ...
Consider testing the null hypothesis that a given population has location parameter greater than or ...
The Kolmogorov Smirnov test (KS) is a well known test used to asses how a set of observations is sig...
Jagannathan andWang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ...
Jagannthan andWang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-...
We provide an in-depth analysis of the theoretical properties of the Hansen–Jagannathan (HJ) distanc...
We compare nonnested parametric specifications of the stochastic discount factor (SDF) using the con...
nested, overlapping, and nested models based on the second Hansen-Jagannathan distance, which requir...
We provide an in-depth analysis of the theoretical and statistical properties of the Hansen-Jagannat...
This paper promotes information theoretic inference in the context of minimum distance estimation. V...
We derive a corrected distance metric (DM) test of general restrictions. The correc-tion factor is a...
We study Kolmogorov–Smirnov goodness-of-fit tests for evaluating distributional hypotheses where unk...
A modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a sp...
peer reviewedWe develop a likelihood-ratio test for discriminating between the g-and-h and the g di...
In this article we introduce and evaluate testing procedures for specifying the number k of nearest ...
A common statistical problem in finance is measuring the goodness-of-fit of a given distribution to ...
Consider testing the null hypothesis that a given population has location parameter greater than or ...
The Kolmogorov Smirnov test (KS) is a well known test used to asses how a set of observations is sig...
Jagannathan andWang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ...
Jagannthan andWang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-...
We provide an in-depth analysis of the theoretical properties of the Hansen–Jagannathan (HJ) distanc...
We compare nonnested parametric specifications of the stochastic discount factor (SDF) using the con...
nested, overlapping, and nested models based on the second Hansen-Jagannathan distance, which requir...
We provide an in-depth analysis of the theoretical and statistical properties of the Hansen-Jagannat...
This paper promotes information theoretic inference in the context of minimum distance estimation. V...
We derive a corrected distance metric (DM) test of general restrictions. The correc-tion factor is a...
We study Kolmogorov–Smirnov goodness-of-fit tests for evaluating distributional hypotheses where unk...
A modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a sp...
peer reviewedWe develop a likelihood-ratio test for discriminating between the g-and-h and the g di...
In this article we introduce and evaluate testing procedures for specifying the number k of nearest ...
A common statistical problem in finance is measuring the goodness-of-fit of a given distribution to ...
Consider testing the null hypothesis that a given population has location parameter greater than or ...
The Kolmogorov Smirnov test (KS) is a well known test used to asses how a set of observations is sig...