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

Author

Listed:
  • Gong Jinguo

    (School of Statistics, Southwestern University of Finance and Economics, Chengdu, China)

  • Wu Weiou

    (Department of Economics, Kemmy Business School, University of Limerick, Limerick, Ireland)

  • 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)

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.

Suggested Citation

  • Gong Jinguo & Wu Weiou & McMillan David & Shi Daimin, 2015. "Non-parametric estimation of copula parameters: testing for time-varying correlation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 93-106, February.
    • Handle: RePEc:bpj:sndecm:v:19:y:2015:i:1:p:93-106:n:4
    DOI: 10.1515/snde-2012-0089
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    References listed on IDEAS

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    1. Hafner, Christian M. & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2609-2627, November.
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    5. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 125-154.
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    More about this item

    Keywords

    dynamic dependence; kernel estimate; local likelihood estimation; stock returns; time-varying copula;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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