基于极值块最小模型的期望缺口鲁棒性分析及算法

Shide Ou, D. Yi
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引用次数: 2

摘要

为了有效地度量股票市场的风险,采用极值块最小法提出了期望缺口的算法。将标准化最小收益在一定区间内的分布转化为普通最小收益的分布,导出了期望差额的计算公式。通过仿真和统计分析,找到了一个合适的区间长度,使该算法具有良好的鲁棒性。仿真结果表明,当区间长度不大于30时,基于该方法的风险值和期望缺口鲁棒性较好。该算法有效地度量了股票市场的预期缺口。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robustness Analysis and Algorithm of Expected Shortfall Based on Extreme-Value Block Minimum Model
To measure effectively the risk of stock market, the algorithm of expected shortfall is presented by using the extreme-value block minimum method. By transforming the distribution of standardized minimal return in an interval into the distribution of ordinary minimal return, the formula of expected shortfall is derived. By simulation and statistical analysis, an appropriate interval length is found out to make this algorithm robust. The simulation results show that the robustness of value at risk and expected shortfall based on this method is very good when the interval length isn’t more than 30. This algorithm measures effectively the expected shortfall of stock market.
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