Non-Parametric Estimation of Copula Parameters: Testing for Time-Varying Correlation
Journal article
Gong, J., Wu, W., McMillan. D and Shi, D. (2014). Non-Parametric Estimation of Copula Parameters: Testing for Time-Varying Correlation. Studies in Nonlinear Dynamics & Econometrics. 19 (1), pp. 93-106. https://doi.org/10.1515/snde-2012-0089
Authors | Gong, J., Wu, W., McMillan. D and Shi, D. |
---|---|
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 |
Year | 2014 |
Journal | Studies in Nonlinear Dynamics & Econometrics |
Journal citation | 19 (1), pp. 93-106 |
Publisher | De Gruyter |
ISSN | 1558-3708 |
Digital Object Identifier (DOI) | https://doi.org/10.1515/snde-2012-0089 |
Web address (URL) | https://www.degruyter.com/document/doi/10.1515/snde-2012-0089/html?lang=en |
Publication dates | |
30 May 2014, 00:00 | |
Publication process dates | |
Deposited | 22 Feb 2024 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/966q3
Download files
32
total views12
total downloads1
views this month0
downloads this month