Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

Mario Cerrato, John Crosby, Minjoo Kim () and Yang Zhao

Working Papers from Business School - Economics, University of Glasgow

Abstract: 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 de- pendence 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 back- testing, 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 (search for similar items in EconPapers)
JEL-codes: C32 C53 G17 G32 (search for similar items in EconPapers)
Date: 2015-02
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2015_15

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