蒙特卡罗方差减少。重要性抽样技术

2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2009-09-26 DOI:10.1109/SYNASC.2009.56

Olariu S. Emanuel Florentin

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引用次数: 1

摘要

本文研究了一些重要抽样策略，并首次将其应用于价差期权的定价。我们比较了最小二乘法和f散度法来选择重要抽样函数。我们的数值结果表明，散度的使用往往是计算量少，时间昂贵。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Monte Carlo Variance Reduction. Importance Sampling Techniques

In this paper we investigate some Importance Sampling strategies and we apply them for the first time to the pricing of the spread options. We compare the Least Squares method to the f-divergence method in order to choose the importance sampling functions. Our numerical results reveals that the use of the divergences is frequently less computationally and time costly.

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来源期刊

2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

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