Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach

Abstract

The study forecast intraday portfolio VaR and CVaR using high frequency data of three pairs of stock price indices taken from three different markets. For each pair we specify both the marginal models for the individual return series and a joint model for the dependence between the paired series. We have used CGARCH-EVT-Copula model, and compared its forecasting performance with three other competing models. Backtesting evidence shows that the CGARCH-EVT-Copula type model performs relatively better than other models. Once the best performing model is identified for each pair, we develop an optimal portfolio selection model for each market, separately.