Non-parametric estimation of copula parameters: testing for time-varying correlation

Gong Jinguo, Weiou Wu, McMillan David () and Shi Daimin
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Gong Jinguo: School of Statistics, Southwestern University of Finance and Economics, Chengdu, China
McMillan David: Accounting and Finance Division, Stirling Management School, University of Stirling, Stirling, UK
Shi Daimin: School of Statistics, Southwestern University of Finance and Economics, Chengdu, China

Studies in Nonlinear Dynamics & Econometrics, 2015, vol. 19, issue 1, 93-106

Abstract: The correlation structure of financial assets is a key input with regard to portfolio and risk management. In this paper, we propose a non-parametric estimation method for the time-varying copula parameter. This is achieved in two steps: first, displaying the marginal distributions of financial asset returns by applying the empirical distribution function; second, by implementing the local likelihood method to estimate the copula parameters. The method for obtaining the optimal bandwidth through a maximum pseudo likelihood function and a statistical test on whether the copula parameter is time-varying are also introduced. A simulation study is conducted to show that our method is superior to its contender. Finally, we verify the proposed estimation methodology and time-varying statistical test by analysing the dynamic linkages between the Shanghai, Shenzhen and Hong Kong stock markets.

Keywords: dynamic dependence; kernel estimate; local likelihood estimation; stock returns; time-varying copula (search for similar items in EconPapers)
JEL-codes: C58 G12 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1515/snde-2012-0089

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