Empirical likelihood based confidence intervals for copulas

Jian Chen, Liang Peng and Yichuan Zhao

Journal of Multivariate Analysis, 2009, vol. 100, issue 1, 137-151

Abstract: Copula as an effective way of modeling dependence has become more or less a standard tool in risk management, and a wide range of applications of copula models appear in the literature of economics, econometrics, insurance, finance, etc. How to estimate and test a copula plays an important role in practice, and both parametric and nonparametric methods have been studied in the literature. In this paper, we focus on interval estimation and propose an empirical likelihood based confidence interval for a copula. A simulation study and a real data analysis are conducted to compare the finite sample behavior of the proposed empirical likelihood method with the bootstrap method based on either the empirical copula estimator or the kernel smoothing copula estimator.

Keywords: primary; 62G05 secondary; 62E20 Confidence interval Copula Empirical likelihood Normal approximation (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (15)

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