论文标题
使用多元条件概率进行压力测试和全身风险措施
Stress testing and systemic risk measures using multivariate conditional probability
论文作者
论文摘要
多元条件概率分布模拟了一组变量对另一组变量的统计属性的影响。在金融系统中系统性风险的研究中，可以通过量化从一组“压力”变量到另一组“压力”变量的损失的传播来使用多元条件概率分布来进行压力测试。在本文中，我描述了如何为庞大的多元椭圆形分布的家族计算这种条件概率分布，尤其是多元学生-T和多元正常分布。提出了压力影响和全身风险的度量。美国股票市场的应用说明了这种方法的潜力。
The multivariate conditional probability distribution models the effects of a set of variables onto the statistical properties of another set of variables. In the study of systemic risk in a financial system, the multivariate conditional probability distribution can be used for stress-testing by quantifying the propagation of losses from a set of `stressing' variables to another set of `stressed' variables. In this paper I describe how to compute such conditional probability distributions for the vast family of multivariate elliptical distributions, and in particular for the multivariate Student-t and the multivariate Normal distributions. Measures of stress impact and systemic risk are proposed. An application to the US equity market illustrates the potentials of this approach.
