Risk measurement of global stock markets: a factor copula-based GJR-GARCH approach

Abstract

Financial crisis in 2008 caused huge loss and one of the accusations is the misprediction of risk measurement. Considering the important role the stock markets play, and the trend of globalization in economy, we propose forecasting Value at Risk of G20’s (except European Union) stock indexes in three periods, pre-crisis, during crisis and post-crisis, via factor copula model. Unlike those models based on multivariate normality, factor copula is based on the assumption that there exists a or several common factors which lead to the change of stock prices. In this paper, different levels of dependence among 19 countries are presented and the results indicate that, during crisis countries with higher values of coefficients tend to have larger loss than others. Also, the large numbers of violations to VaR may be an indicator of the upcoming financial crisis.

Conditional Dynamic Dependence and Risk Spillover between Crude Oil Prices and Foreign Exchange Rates: New Evidence from a Dynamic Factor Copula Model

“…Therefore, we try to adopt the factor copula model to characterize the dependence structure between crude oil and exchange rate markets, under the assumption that there exists at least one common factor related to the change of oil prices as well as exchange rates [29]. In other words, we combine the factor analysis and copula model to identify the interdependence across the crude oil and exchange rate returns of oil exporters and importers, respectively.…”