Arbeitspapier
Goodness-of-fit test for specification of semiparametric copula dependence models
This paper concerns goodness-of-fit test for semiparametric copula models. Our contribution is two-fold: we first propose a new test constructed via the comparison between in-sample and out-of-sample pseudolikelihoods, which avoids the use of any probability integral transformations. Under the null hypothesis that the copula model is correctly specified, we show that the proposed test statistic converges in probability to a constant equal to the dimension of the parameter space and establish the asymptotic normality for the test. Second, we introduce a hybrid mechanism to combine several test statistics, so that the resulting test will make a desirable test power among the involved tests. This hybrid method is particularly appealing when there exists no single dominant optimal test. We conduct comprehensive simulation experiments to compare the proposed new test and hybrid approach with the best blank test shown in Genest et al. (2009). For illustration, we apply the proposed tests to analyze three real datasets.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2013-041
Hypothesis Testing: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Evaluation, Validation, and Selection
International Financial Markets
in-and-out-of sample likelihood
power
tail dependence
Okhrin, Ostap
Zhou, Qian M.
Song, Peter X.-K.
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:25 MESZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Zhang, Shulin
- Okhrin, Ostap
- Zhou, Qian M.
- Song, Peter X.-K.
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2013
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