The article introduces a method to estimate Value-at-Risk (VaR) and Expected Shortfall (ES) for portfolios with changing risk factors using a mixture of generalized Laplace distributions. This method improves accuracy by considering the varying shapes and fat tails of the risk factors. The approach involves using conditional correlation multivariate GARCH to calculate Delta-GLD-VaR, Delta-GLD-ES, Delta-MGLD-VaR, and Delta-MGLD-ES. The findings suggest that this method can be useful for measuring price risk in agriculture, risk management, and financial portfolio optimization.