Pricing and hedging basket options with exact moment matching
提出一种利用Hermite多项式展开精确匹配篮子收益前m阶矩的方法，用于标的资产价格服从带跳跃的位移对数正态过程时的篮子期权定价与对冲，效果优于传统方法。
Theoretical models applied to option pricing should take into account the empirical characteristics of financial time series. In this paper, we show how to price basket options when the underlying asset prices follow a displaced log-normal process with jumps, capable of accommodating negative skewness and excess kurtosis. Our technique involves Hermite polynomial expansion that can match exactly the first m moments of the model-implied basket return. This method is shown to provide superior results for basket options not only with respect to pricing but also for hedging.