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首页> 外文期刊>Journal of Mathematical Finance >Variance Reduction Techniques of Importance Sampling Monte Carlo Methods for Pricing Options
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Variance Reduction Techniques of Importance Sampling Monte Carlo Methods for Pricing Options

机译:期权定价重要抽样蒙特卡罗方法的方差降低技术

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摘要

In this paper we discuss the importance sampling Monte Carlo methods for pricing options. The classical importance sampling method is used to eliminate the variance caused by the linear part of the logarithmic function of payoff. The variance caused by the quadratic part is reduced by stratified sampling. We eliminate both kinds of variances just by importance sampling. The corresponding space for the eigenvalues of the Hessian matrix of the logarithmic function of payoff is enlarged. Computational Simulation shows the high efficiency of the new method.
机译:在本文中,我们讨论了用于定价选项的重要性抽样蒙特卡罗方法。经典重要性采样方法用于消除由收益的对数函数的线性部分引起的方差。分层采样可减少由二次部分引起的方差。我们仅通过重要性抽样来消除这两种方差。扩大了对数收益函数的Hessian矩阵特征值的对应空间。计算仿真表明了该新方法的高效率。

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