Simulating Coherent Risk Measures

该项目将开发风险测量中的计算机模拟程序。这些程序将适用于模拟连贯的风险衡量标准，这是一种高级风险衡量标准，比标准差和风险价值等广泛使用的旧衡量标准更具优势。这些程序将是精确的，计算效率高，适应手头的问题，并且健壮。这项研究将增强现有的模拟某类连贯风险措施的程序，使其更具适应性和健壮性。它还将产生新的、更精确的程序，用于模拟一种特定的连贯风险指标，即条件尾部预期，这是一些与股市挂钩的保单的风险管理标准。这些程序的计算效率和统计有效性将在金融投资组合管理的例子中进行测试。这项工作预计将有助于改善银行、投资公司和保险公司的风险管理。良好的计算机模拟程序的可获得性将使风险经理采取最先进的风险措施更具吸引力。与标准差和风险价值不同，连贯的风险衡量方法可以清楚地量化最大潜在损失的大小。这项研究有可能改变风险管理实践，降低银行倒闭、保险公司资不抵债和金融市场灾难性中断的可能性。

This project will develop procedures for computer simulation in risk measurement. The procedures will apply to simulating coherent risk measures, which are an advanced class of risk measures that have advantages over older measures that are widely in use, such as standard deviation and value-at-risk. The procedures will be precise, computationally efficient, adaptive to the problem at hand, and robust. The research will enhance existing procedures for simulating a certain class of coherent risk measures, by making them more adaptive and robust. It will also produce new, more precise procedures for simulating one particular coherent risk measure known as conditional tail expectation, which is a risk management standard for some insurance policies that are linked to the stock market. Tests of the computational efficiency and statistical validity of the procedures will be conducted on examples of financial portfolio management.This work is expected to contribute to improvements in risk management by banks, investment firms, and insurers. The availability of good computer simulation procedures will make it more attractive for risk managers to adopt state-of-the-art risk measures. Coherent risk measures, unlike standard deviation and value-at-risk, can provide a clear quantification of the magnitude of the largest potential losses. The research has the potential to change risk management practice in a way that reduces the likelihood of bank failures, insolvency of insurers, and catastrophic disruption of financial markets.