TITLE:
Risk Correlation Based on Time-Varying Copula Function and Extreme Value Theory
AUTHORS:
Xinlong Ji, Lu Zhou
KEYWORDS:
Time-Varying Copula, SV-t-EVT Model, Risk, Correlation
JOURNAL NAME:
Theoretical Economics Letters,
Vol.7 No.7,
December
18,
2017
ABSTRACT: The dependence structure of financial assets in
financial risk measurement is very important, the tail relations in
particular. Authors of extant studies in this field tended to focus on the
linear analysis of the financial assets, rarely considering nonlinear,
asymmetric and thick-tail characteristics. Here, we apply the copulas
connection function with time-varying factors to discuss the risk dependency
relationship between financial assets. Moreover, we develop an SV-EVT model to
fit variables’ marginal distribution combined with stochastic volatility and
extreme value theory. Finally, we present an empirical comparative study of
static and dynamic copula models applied to the sample comprising of the
Chinese mainland A-shares and Hong Kong stock market. The results show that the
CSJC copulas connection function describes the tail features of stock index
better than the normal copulas connection function. Similarly, the time-varying
model outperforms the static copulas model. Furthermore, we observe an
asymmetry dependence change rule between Chinese mainland A-shares market and
the Hong Kong stock market; the correlation of lower tail is significantly
higher than that of the upper tail, and the bear market effect is remarkable.
These findings indicate that time-varying Copulas-SV-EVT model can depict the
correlation of financial asset tails exactly, and can thus be used to control
investment risk and forecast abnormal fluctuations.