infonet-economy

This paper proposes a new copula-based approach to test for asymmetries in the dependence structure of ¯nancial time series. Simply splitting observations into subsamples and comparing conditional correlations leads to spurious results due to the well-known conditioning bias. Our suggested framework is able to circumvent these problems. Applying our test to market data, we statistically con¯rm the widespread notion of signicant asymmetric dependence structures between daily changes of the VIX, VXN, VDAXnew, and VSTOXX volatility indices and their corresponding
equity index returns. A maximum likelihood method is used to perform a likelihood ratio test between the ordinary t-copula and its asymmetric extension. To the best of our knowledge, our study is the ¯rst empirical implementation of the skewed t-copula to generate meta skewed student t-distributions. Its asymmetry leads to signi¯cant improvements in the description of the dependence structure between equity returns and implied volatility changes.

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1310684