CAJ | 학술논문

为了克服极小概率事件发生概率估计的困难,提出了把重要抽样技术发展到外汇期权组合非线性VaR模型中,估计出组合损失概率.为了进一步达到减少模拟估计误差目的,在重要抽样技术基础上使用分层抽样技术,进行更有效的Monte Carlo模拟.数值结果表明,重要抽样技术算法比常用Monte Carlo模拟法的计算效率更有效;而重要抽样技术和分层抽样技术相结合算法比重要抽样技术算法更有效地减少模拟所要估计的组合损失概率的方差,有着更高的计算效率.
위료극복겁소개솔사건발생개솔고계적곤난,제출료파중요추양기술발전도외회기권조합비선성VaR모형중,고계출조합손실개솔.위료진일보체도감소모의고계오차목적,재중요추양기술기출상사용분층추양기술,진행경유효적Monte Carlo모의.수치결과표명,중요추양기술산법비상용Monte Carlo모의법적계산효솔경유효;이중요추양기술화분층추양기술상결합산법비중요추양기술산법경유효지감소모의소요고계적조합손실개솔적방차,유착경고적계산효솔.
To overcome the difficulty in estimating low probability,the importance samping technique is developed into non-linear VaR model of FX option portfolio,and the loss probability of portfolio is estimated precisely. Moreover,the algorithm combining importance samping technique with stratified samping technique is used to carry though more efficient Monte Carlo simulation. The simulation result shows the algorithm using importance samping technique has much more effectiveness of computational efficiency than the standard Monte Carlo simulation. And the algorithm combining importance samping with stratified samping has much more effectiveness of computational efficiency than the algorithm using importance samping technique,and can lead to larger variance reductions when estimating the loss probability of portfolio.