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基于CVaR风险度量的投资组合优化决策 被引量:3

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摘要 投资组合优化问题依赖于风险度量方法和投资组合收益率分布函数的选取。针对收益率通常不服从多元正态分布以及均值—方差模型低估了投资组合发生重大损失的风险,文章利用多元广义双曲线分布来拟合投资组合收益率,从而更加灵活地捕捉收益率数据的偏态和尖峰厚尾特征;使用CVaR代替方差和VaR来度量金融资产重大损失风险,进而建立均值—CVaR投资优化模型。实证研究结果表明,相对于均值—方差模型,均值—CVaR能够更好地反映投资组合收益率分布,提高投资者控制投资风险的能力。
出处 《统计与决策》 CSSCI 北大核心 2012年第15期39-42,共4页 Statistics & Decision
基金 国家自然科学基金资助项目(70901077) 国家自然科学基金资助项目(71002109) 教育部人文社会科学青年基金资助项目(09YJC790266) 南京审计学院人才引进项目(NSRC10014)
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参考文献15

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