基于VaR的基金业绩指标修正及基金评价分析
Modification of Fund Performance Index Based on VaR and Its Application on Funds Evaluation
DOI: 10.12677/BGlo.2017.54011, PDF, HTML, XML, 下载: 1,592  浏览: 3,205 
作者: 贠欣屹, 陈 源, 金 辉:杭州电子科技大学经济学院,浙江 杭州
关键词: 基金业绩指标VaR模型GARCH模型GED分布t分布Fund Performance Index VaR Model GARCH Model GED Distribution T Distribution
摘要: 如何采取科学的业绩评价指标是合理评价基金业绩的关键。选取我国基金市场上不同投资风格的开放式股票基金作为样本,分别采取服从t分布和GED分布的GARCH(1,1)模型并运用参数法估计VaR,然后基于VaR修正夏普比率并对不同基金进行风险调整收益评价。实证结果表明,基金的下行风险可通过VaR值来度量并以修正的夏普比率评测基金业绩。同时发现,价值型基金的业绩相对较好;成长型基金的分布不均匀;平衡型基金并没有表现出介于成长型和价值型的特点;不同基金的差异较大。最后,对我国开放式股票型基金的评价提出了建议。
Abstract: How to take scientific index for performance evaluation of mutual-funds is the key to evaluate funds’ performance reasonably. Chosen the open-ended stock funds with different investment styles in the fund market of China as the samples, the GARCH (1,1) model, which follows the t distribution and GED distribution separately, is used to evaluate the VaR by using the parameter method. Based on VaR, the Sharpe ratio is modified and then the risk adjusted returns of different funds are evaluated. Empirical results show that the downside risk of the funds can be measured by VaR and the fund performance is evaluated at the modified Sharpe ratio. It is also found that the performance of the value-type fund is relatively good, the growth-type fund is not evenly distributed, the balanced-type fund does not show the characteristics of growth and value, and the individual differences are great for funds of different types. Finally, some suggestions are proposed for the development of Chinese open-ended stock funds.
文章引用:贠欣屹, 陈源, 金辉. 基于VaR的基金业绩指标修正及基金评价分析[J]. 商业全球化, 2017, 5(4): 88-96. https://doi.org/10.12677/BGlo.2017.54011

参考文献

[1] Dowd, K. (2000) Estimating Value at Risk: A Subjective Approach. Journal of Risk Finance, 1, 43-46.
https://doi.org/10.1108/eb043454
[2] Lau, W.Y. (2008) Investigating Equity Style Portfolio Risk Using VaR: An Empirical Study Based on Malaysian Mutual Funds. Osaka Economic Papers, 57, 100-118.
[3] Dulaney, T. and McCann, C. (2013) Robust Portfolio Optimization with Value-at-Risk Adjusted Sharpe Ratios. Journal of Asset Management, 14, 293-305.
https://doi.org/10.1057/jam.2013.21
[4] Tehrani1, R., Mirza, S., Mohammadi, N. and Nejadolhosseini, S. (2014) Value at Risk as a Tool for Mutual Funds Performance Evaluation. International Business Research, 7, 16-21.
https://doi.org/10.5539/ibr.v7n10p16
[5] 史敏, 汪寿阳, 徐山鹰. 修正的Sharpe指数及其在基金业绩评价中的应用[J]. 系统工程理论与实践, 2006, 26(7): 1-10.
[6] 刘沛欣, 田军, 周勇. 基于VaR和ES调整的Sharpe比率及在基金评价中的实证研究[J]. 数理统计与管理, 2012, 31(4): 735-750.
[7] 李凯琪, 沈蕾. 基于VaR模型的互联网金融产品的收益风险度量及绩效评价[J]. 征信, 2015, 33(7): 72-75.
[8] Goorbergh, V.P. (1999) Value-at-Risk: Analysis of Stock Returns Historical Simulation. Journal of Business, 3, 1-25.
[9] Angelidis, T., Benos, A. and Degiannakis, S. (2004) The Use of GARCH Models in VaR Estimation. Statistical Methodology, 1, 105-128.
https://doi.org/10.1016/j.stamet.2004.08.004
[10] Angelidis, T. and Degiannakis, S.A. (2007) BacktestingVaR Models: An Expected Shortfall Approach. Working Papers, 1-35.
[11] 唐振鹏, 彭伟. 基于CVaR的RAROC对我国开放式基金绩效评价[J]. 系统工程理论与实践, 2010, 30(8): 1403- 1413.
[12] 李贺, 叶中行. 极值理论与VaR计算[J]. 宁夏大学学报, 2007, 28(2): 124-127.
[13] 黄崇珍, 曹奇. 基于GARCH-VaR模型的开放式基金风险度量[J]. 财经纵横, 2017(1): 152-155.