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 estimation of loss probability of portfolio is a prerequisite to calculating VaR, which is a percentile of the loss distribution. The simulation result shows the algorithm has more much effectiveness of computational efficiency than the standard Monte Carlo simulation, and can lead to large variance reductions when estimating the loss probability of portfolio.