VaR、CVaR在基金RAROC绩效评价上的应用比较——以科创主题基金为例  

Comparison of VaR and CVaR in RAROC on the Fund Performance Evaluation:Taking science and innovation theme fund as an example

作　　者：郑丽青 ZHENG Liqing(Business School,Fuzhou Technology and Business University,Fuzhou 350003,China)

机构地区：[1]福州工商学院商学院,福州350003

出　　处：《科技和产业》2022年第1期103-108,共6页Science Technology and Industry

基　　金：2019年福建省中青年教师教育科研项目(JAT191059);2019年福建省本科高校重大教育教学改革研究项目(FBJG20190172)。

摘　　要：选取2020年8支科创主题基金为样本,基于基金收益率的尖峰厚尾特点,运用POT模型度量VaR、CVaR风险,比较基于VaR、CVaR的RAROC指标在基金绩效评价上的效果。实证结果发现:基于极值理论POT模型计算的VaR、CVaR可以很好地体现基金收益率的尾部风险;结合经验法与图示法选择的POT模型最佳门限能够得出有效的VaR、CVaR;基于CVaR的RAROC指标在基金绩效评价方面比基于VaR的RAROC指标表现更稳定,效果更佳,具有正向反映基金收益、规避风险的优点。8 science and technology themed funds in 2020 was selected as samples.Due to the peak and thick tail characteristics of fund returns,POT model of Extreme Value Theory was used to calculate VaR and CVaR risks.Comparing the effects of RAROC based on VaR and CVaR on fund performance evaluation,the results found that VaR and CVaR calculated based on POT model of the Extreme Value Theory can well reflect the tail risk of fund returns.The optimal threshold of the POT model selected by combining the empirical method and the graphical method can obtain effective VaR and CVaR.The RAROC indicator based on CVaR is more stable and effective in fund performance evaluation than the RAROC indicator based on VaR,and it can positively reflect fund returns and avoid risks.

关 键 词：VAR CVAR RAROC POT模型 基金绩效评价 

分 类 号：F830.91[经济管理—金融学] O212.1[理学—概率论与数理统计]