基于重要抽样技术的外汇期权组合非线性VaR模型

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,通过改变市场变量回报分布的期望向量和协方差矩阵,在相应区域产生更多的样本,使得该情形下不再是稀有事件Monte Carlo模拟,从而减少Monte Carlo模拟计算工作量,更精确地估计出组合的损失概率,而组合的损失概率是计算组合损失分布的分位点(VaR值)的必备条件.模拟结果表明,该算法比常用Monte Carlo模拟法的计算效率更有效,且能很大程度上减少所要估计的损失概率的方差.

Research on Nonlinear VaR Model of FX Options Portfolio Based on Importance Sampling Technique

To overcome the difficulty in estimating low probability,the paper proposes that importance sampling technique is developed upto non-linear VaR model of FX option portfolio.Producing more samples in corresponding region by changing expectation vector and covariance matrix of distribution of market factors returns,this makes the state not be rare event simulation.Accordingly,this decreases calculating effort in Monte Carlo simulation.Moreover,the loss probability of portfolio is estimated precisely.Precise e...