基于最大熵方法的DaR风险度量模型  

A Maximum Entropy Model for Risk Measurement DaR

作　　者：徐文莉[1] 

机构地区：[1]上海电力学院数理系,上海200090

出　　处：《安徽师范大学学报（自然科学版）》2007年第1期21-24,共4页Journal of Anhui Normal University(Natural Science)

基　　金：上海电力学院青年科学基金(K2003-11)

摘　　要：提出了一种改进的DaR、CDaR风险度量模型.该估计直接从样本信息出发,不需要对损失函数的概率密度函数作任何假定,从而克服了现有风险度量方法的不足,并通过实例进行分析,表明这一模型和方法是有效的.The paper proposes an improving risk measurement model from DaR and CDaR. It directly uses information from sample data for the probabilty density function of Drawdown function. Unlike the common risk measurement methods, it does not need to choose probability distribution as an experienced or prior probability. Computational results of sample data demonstrate that results of maximum entropy model is manifest.

关 键 词：风险度量 DaR CDAR 最大熵 

分 类 号：O212[理学—概率论与数理统计]