随机极限正态分布下的GCVaR风险度量研究

Study on Risk Measure of GCVaR under Random Limit Normal Distribution

摘要: 本文阐明经典的概率统计理论和方法，在不确定性金融风险度量领域的不完全适用性及相应风险度量模型不确定性存在的根源。进而在非线性期望理论基础上，通过构建随机极限正态分布G-正态分布，结合VaR、CVaR风险度量模型，定义了随机极限风险度量模型GVaR和GCVaR。最后，理论上证明了以上两种风险度量模型是合理的、恰当的一致性风险度量。

Abstract: This paper first illustrates classical probability statistics theory and method, the incomplete applicability in the field of uncertainty financial risk measurement, and the origin of the uncertainty of the coherent risk measurement model. Then, based on the nonlinear expectation theory, by constructing the G-normal distribution of the random limit normal distribution, combining the VaR and CVaR risk measurement model, we define the random limit risk measurement model GVaR and GCVaR. Finally, the above two risk measurement models are proved to be reasonable and appropriate coherent risk measurements.