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

作者：Gong, Jinguo; Wu, Weiou; McMillan, David^*; Shi, Daimin

来源：Studies in Nonlinear Dynamics and Econometrics, 2015, 19(1): 93-106.

DOI：10.1515/snde-2012-0089

• dynamic dependence
• kernel estimate
• local likelihood estimation
• stock returns
• time-varying copula

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.

• 出版日期2015-2
• 单位西南财经大学