A simulation analytics approach to dynamic risk monitoring
A simulation analytics approach to dynamic risk monitoring
复制标题
动态风险监控的模拟分析方法
DOI：
10.1109/wsc.2016.7822110
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Barry L. Nelson
中科院分区：
文献类型：
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作者：
Guangxin Jiang;L. J. Hong;Barry L. Nelson
模拟已经被广泛地用作估计金融投资组合的风险度量的工具。然而，在仿真研究中产生的样本路径往往被丢弃后的风险度量的估计获得。在这篇文章中，我们建议存储模拟数据，并提出了一种基于逻辑回归的方法来挖掘它们。我们表明，在任何时候，并在当时的市场条件下，我们可以快速估计投资组合的风险措施，并将投资组合分为低风险或高风险类别。我们称之为动态风险监控。我们研究我们的估计和分类的属性，并通过数值研究证明我们的方法的有效性。
Simulation has been widely used as a tool to estimate risk measures of financial portfolios. However, the sample paths generated in the simulation study are often discarded after the estimate of the risk measure is obtained. In this article, we suggest to store the simulation data and propose a logistic regression based approach to mining them. We show that, at any time and conditioning on the market conditions at the time, we can quickly estimate the portfolio risk measures and classify the portfolio into either low risk or high risk categories. We call this problem dynamic risk monitoring. We study the properties of our estimators and classifiers, and demonstrate the effectiveness of our approach through numerical studies.