ABSTRACT

Percentile is an important risk measure quantifying the stochastic system random behaviours. This paper studies a pooled percentile estimator, which is the sample percentile of detailed simulation outputs after directly pooling independent sample paths together. We derive the asymptotic representation of the pooled percentile estimator and further prove its normality. By comparing with the classical percentile estimator used in stochastic simulation, both theoretical and empirical studies demonstrate the advantages of the proposal under the context of parallel simulation.

中文翻译：

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用于并行模拟的合并百分位数估计器

摘要

百分位数是量化随机系统随机行为的重要风险度量。本文研究了一个池化百分位数估计器，它是直接将独立样本路径汇集在一起​​后详细模拟输出的样本百分位数。我们推导出合并百分位数估计量的渐近表示，并进一步证明其正态性。通过与随机模拟中使用的经典百分位估计量进行比较，理论和实证研究都证明了该方案在并行模拟背景下的优势。