Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula
51 Pages Posted: 30 Jun 2014 Last revised: 20 Jun 2015
Date Written: February 24, 2015
We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct "high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From backtesting, we find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.
Keywords: Asymmetry; Tail dependence; Dependence dynamics; Dynamic skewed t copulas; VaR and ES forecasting
JEL Classification: C32, C53, G17, G32
Suggested Citation: Suggested Citation