Kernel-based goodness-of-fit tests for copulas with fixed smoothing parameters
AbstractWe study a test statistic based on the integrated squared difference between a kernel estimator of the copula density and a kernel smoothed estimator of the parametric copula density. We show for fixed smoothing parameters that the test is consistent and that the asymptotic properties are driven by a U-statistic of order 4 with degeneracy of order 1. For practical implementation we suggest to compute the critical values through a semiparametric bootstrap. Monte Carlo results show that the bootstrap procedure performs well in small samples. In particular, size and power are less sensitive to smoothing parameter choice than they are under the asymptotic approximation obtained for a vanishing bandwidth.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 98 (2007)
Issue (Month): 3 (March)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Other versions of this item:
- Olivier Scaillet, 2005. "Kernel Based Goodness-of-Fit Tests for Copulas with Fixed Smoothing Parameters," FAME Research Paper Series rp145, International Center for Financial Asset Management and Engineering.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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- G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
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