使用混合序列实现去偏估计

IF 0.8 Q3 STATISTICS & PROBABILITY

Monte Carlo Methods and Applications Pub Date : 2020-10-02 DOI:10.1515/mcma-2020-2075

Arun Kumar Polala, G. Ökten

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引用次数: 1

摘要

摘要我们描述了使用混合序列的去偏估计器的实现；这些是从伪随机序列和低差异序列获得的序列。我们使用这种实现来数值求解计算金融中的一些随机微分方程。当混合序列与布朗桥或主成分分析结构相结合时，其收敛速度明显优于蒙特卡罗实现。

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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Implementing de-biased estimators using mixed sequences

Abstract We describe an implementation of the de-biased estimator using mixed sequences; these are sequences obtained from pseudorandom and low-discrepancy sequences. We use this implementation to numerically solve some stochastic differential equations from computational finance. The mixed sequences, when combined with Brownian bridge or principal component analysis constructions, offer convergence rates significantly better than the Monte Carlo implementation.

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来源期刊

Monte Carlo Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.20

自引率

22.20%

发文量