The article explores a new method to estimate the risk of investment portfolios called Value at Risk (VaR). By combining different statistical techniques like Copula functions, Extreme Value Theory (EVT), and GARCH-GJR models, the researchers studied the relationship between two stock market indices. They found that the copula model was more successful in capturing the portfolio's risk compared to traditional methods.