本文主旨在對最小平方蒙地卡羅模擬法提出修正。在進行評價後發現，在單一資產方面，與Choi和Song(2008)所提出之修正方法進行計算速度方面的評比，發現仍可再提升10%至14%的速度。在多資產方面，在以Anderson和Broadie(2004)之方法做為比較對象，本文所建立之95%信賴區間皆能涵蓋真實價值並節省平均94%的計算時間；當進一步結合Sobol序列，節省之時間可達99%。

This article derives improvements to the LSMC for derivatives pricing. For single asset pricing, the results imply that our method can even raise computational speed by 10% to 14% more than that of Choi and Song (2008). We also extend our model for multi-asset pricing and make a comparison with Anderson and Broadie’s (2004) approach in valuing rainbow options. The benchmark values can be exactly covered in 95% confidence intervals and the computational time is reduced by about 94%. Further, we use the Sobol’ sequence to reduce 99% computational time under 0.04%~0.9% pricing errors.