Ước lượng VaR và CVaR dạng hỗn hợp các phân phối xác suất thông qua mô phỏng Monte Carlo và ứng dụng trong phân tích giá chứng khoán Việt Nam - Lê Thanh Hoa (JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES, 2018)
VaR and CVaR are of great concern in risk measurement field applying for financial data. However, studies only stopped at the formula based on an approximation of data through a probability distribution, while the distribution of real data is usually a mixture of probability distributions. Therefore, it is necessary to study the VaR and CVaR estimating in the case of a mixture of probability distributions. Furthermore, the estimations also require short computational time so the author prefers to use the Monte Carlo simulation method. The author proposes the VaR and CVaR calculations in the case of probability distributions that are mixed by calibrating the Monte Carlo simulation method to suit a mixture of probability distributions. In addition, the author illustrates in cases where the simulation is known to distribute the probability of the component as well as the unknown case of the probability distribution of the component via the real data of the closing price of the Vietnam stock by a mixture of probability distributions. The algorithm-based estimation results that the author recommends is evaluated by the tail probability as well as standard deviation.