In this paper, genetic algorithm (GA) is put forward to improve the accuracy and robustness of the parameters estimation in GARCH models, and the results are applied to calculate value at risk. The computing examples of Dow Jones Index and exchange rate are presented, and the computation results indicate that VaR-GARCH model based on GA outperformed the conventional numerical method on the aspect of computational robustness and accuracy.