开放式基金流动性风险的VaR方法研究
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摘要
文章研究了开放式基金流动性风险,对VaR模型进行了改进,选取了30支开放式基金2008年第一季度到2009年第一季度的数据进行了实证分析。
首先介绍了文章的选题背景和研究意义,然后对国内外开放式基金流动性风险理论进行了综述,总结分析了20世纪90年代以来国内外理论界在开放式基金流动性风险方面取得的研究成果。
其次介绍了流动性风险的定义及其衡量指标,说明流动性风险的含义,并介绍了开放式基金的发展历程。在开放式基金流动性风险的研究方法中选取了几个有代表性的并且和本文研究密切相关的流动性风险衡量理论进行了介绍,其中包括传统VaR计算方法历史模拟法、方差-协方差法、Monte-Carlo法,另外介绍了极值理论模型并对以上模型进行评价。
再次,对我国开放式基金流动性风险进行了实证研究。首先收集数据并进行预处理,计算30支样本基金的基于价格波动的换手率并对它们的分布特征进行分析,得到其分布均不服从正态分布并普遍存在正偏斜、尖峰现象的结论。因此基于正态假设的方差-协方差法失效。对此,文章采用针对极端数据的极值法替代经典的参数法方差-协方差法。同时,对历史模拟法进行加权得到改进后的历史模拟法。通过采用基于VaR改进的历史模拟法和对极值理论法进行计算,得出实证结果,在不同置信水平下,极值法与改进后的历史数据法有效性略有差别,并对上述计算方法进行有效性对比。
最后是文章的结束语。指出了研究结论、不足及今后的研究问题。根据现阶段我国开放式基金流动性风险所存在的问题提出几项建议。
The paper discusses the liquidity risk of open-end funds, It improves VaR model. Then make empirical research on liquidity risk of open-end funds by using data of 30 open-end funds from January,2008 to March,2009.
Firstly, the paper outlines the liquidity risk of open-end funds on background, goals, domestic and foreign related fundamental research.The paper analyzes these theories in detail of liquidity risk of open-end funds.
Secondly, It introduces definition and index of liquidity risk of open-end funds and introduces the history of open-end funds. In the part of methods of open-end funds researching, it elects some theories of liquidity risk which is representational and correlative, including Historical Simulation, Variance-Covariance Method and Monte-Carlo Method.It also introduces EVT.Then it estimates all above them.
Thirdly, It makes an emoirical research on liquidity risk of domestic open-end funds. It elects 30 mutual funds and computes the turnover ratio of them. All of their kurtosis index and skewness index differ with the normal distribution. Based on the distribution of data,It can not use the classic parametric method-the model of variance and coefficient variance.So it choses POT model based on the extreme theory.As the classic model of historical has some defaults,there add exponentially weight to revise it. Then it compares the results of Historical Simulation with the results extreme theory. It gets the conclusion that VaR model based on the extreme theory is valid in high confidence levels. And invalid in low confidence levels,the model of revised historical is on the contrary.
In the end, it is the ending.Point out the conclusion,the shortages and the further research. Considering the situation of china liquidity risk of open-end funds, the paper makes some pieces of advice at last.
首先介绍了文章的选题背景和研究意义,然后对国内外开放式基金流动性风险理论进行了综述,总结分析了20世纪90年代以来国内外理论界在开放式基金流动性风险方面取得的研究成果。
其次介绍了流动性风险的定义及其衡量指标,说明流动性风险的含义,并介绍了开放式基金的发展历程。在开放式基金流动性风险的研究方法中选取了几个有代表性的并且和本文研究密切相关的流动性风险衡量理论进行了介绍,其中包括传统VaR计算方法历史模拟法、方差-协方差法、Monte-Carlo法,另外介绍了极值理论模型并对以上模型进行评价。
再次,对我国开放式基金流动性风险进行了实证研究。首先收集数据并进行预处理,计算30支样本基金的基于价格波动的换手率并对它们的分布特征进行分析,得到其分布均不服从正态分布并普遍存在正偏斜、尖峰现象的结论。因此基于正态假设的方差-协方差法失效。对此,文章采用针对极端数据的极值法替代经典的参数法方差-协方差法。同时,对历史模拟法进行加权得到改进后的历史模拟法。通过采用基于VaR改进的历史模拟法和对极值理论法进行计算,得出实证结果,在不同置信水平下,极值法与改进后的历史数据法有效性略有差别,并对上述计算方法进行有效性对比。
最后是文章的结束语。指出了研究结论、不足及今后的研究问题。根据现阶段我国开放式基金流动性风险所存在的问题提出几项建议。
The paper discusses the liquidity risk of open-end funds, It improves VaR model. Then make empirical research on liquidity risk of open-end funds by using data of 30 open-end funds from January,2008 to March,2009.
Firstly, the paper outlines the liquidity risk of open-end funds on background, goals, domestic and foreign related fundamental research.The paper analyzes these theories in detail of liquidity risk of open-end funds.
Secondly, It introduces definition and index of liquidity risk of open-end funds and introduces the history of open-end funds. In the part of methods of open-end funds researching, it elects some theories of liquidity risk which is representational and correlative, including Historical Simulation, Variance-Covariance Method and Monte-Carlo Method.It also introduces EVT.Then it estimates all above them.
Thirdly, It makes an emoirical research on liquidity risk of domestic open-end funds. It elects 30 mutual funds and computes the turnover ratio of them. All of their kurtosis index and skewness index differ with the normal distribution. Based on the distribution of data,It can not use the classic parametric method-the model of variance and coefficient variance.So it choses POT model based on the extreme theory.As the classic model of historical has some defaults,there add exponentially weight to revise it. Then it compares the results of Historical Simulation with the results extreme theory. It gets the conclusion that VaR model based on the extreme theory is valid in high confidence levels. And invalid in low confidence levels,the model of revised historical is on the contrary.
In the end, it is the ending.Point out the conclusion,the shortages and the further research. Considering the situation of china liquidity risk of open-end funds, the paper makes some pieces of advice at last.
引文
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2.Warther,V..Aggregate Mutual Fund Flows and Security Returns[J],Journal of Financial Economics.1995,39(2):209-235.
3.Edelen.Investor Flows and The Assessed Perfomance of Open-end Mutual Funds[J], Journal of Financial Economics.1999,53(9):439-466.
4.Barelay.M.J., William.G.C., Jeffrey.H.H., Eugene.K.&Paul.H.S. Effects of Market Reform on The Trading Costs and Depths of Nasdaq Stocks[J], Journal of Finance,1999,54(1):1-34.
5.James Tobin.Liquidity Preference as Behavior towards Risk[J],Review of Economic Studies,1958,25(7):65-86.
6.Kyle S..Continuous Actions and Insider Trading[J], Econometrical,1985, 53(5):1310-1325.
7.Warther,V..Aggregate Mutual Fund Flows and Security Returns[J],Journal of Financial Economics.1995,39(2):209-235.
8.Froot S..The Portfolio Flows of International Investors[J], Typescript, 1998,16(4):32-37.
9.Sunder C..Growth Prospects of Mutual Funds and Investor Perception with Special Reference to Kathari Pioneer Mutual Fund,Project Report[M], Andhra: Andhra University,1998:555-628.
10.Almgren R.,N.Chriss,Value Under Liquidation[R], Working Paper,1999, 10(5):1-10.
11.Bangia,A.,FX.Dibeold,. T.Shumerann,J.D.Stroughair.Modeling Liuqidity Risk [R], Financial institutions center,the warton school, working paper,1999, (6): 68-73.
12.Vikram Nanda, Narayanan. Liquidity, Investment Ability and Mutual Fund Structure [J], Journal of Financial Economics.2000,57(1):417-443.
13.Annaert B.,Vennet J.Determinants of Mutual Fund Performance:A Bayesian Stochastic Frontier Approach[J],Working Paper at Union Collide in Schenectady,2001,12(7):87-92.
14.Philipe Jorion.Value at Risk-The New Benchmark for Managing Financial Risk[J], Financial Markets and Portfolio Management,2007,21(3):397-399.
15.ICI (U.S. Investment ComPany Institute) [R], Understanding Shareholder Redemption Decision,1992,(15):13-21.
16.Gruber M..Another Puzzle:The Growth in Actively Managed Mutual Funds[J], Journal of Finance,1996,51(3):783-810.
17.Chordia,T..The Structure of Mutual Fund Charges[J], Journal of Financial Economics,1996,41 (1):3-39.
18.Bangia, Diebold, Schuermann. Modeling Liquidity Risk With Implications for Traditional Market Risk Measurement and Management[R],Wharton Financial Institutions Center Working Paper,1998,(11):1-16.
19. Harris.L.E..Liquidity, Trading Rules, and Electronic trading systems[J], Monograph Series in Finance and Economics,1990,(4):162-183.
20. Hasbrouck.J..Measuring The Information Content of Stock Trades[J], The Journal of Finance,1991,46(1):179-207.
21. Hasbrouek.J.,Sehwartz.R.A..Liquidity and Execution Costs in Equity Markets[J], Journal of Portfolio Management,1988,(14):10-16.
22.Engle Robert F.,Lange Joe. Predicting VNET: A Model of The Dynamics of Market Depth[J] Journal of Financial Markets,2001,4(2):113-142.
23.Bollersev,T..Generalized Autoregressive Condional Heteroseedastieity[J], Journal of Econometrics,1986,31 (3):07-27.
24.Longin.The Asymptotic Distribution of Extreme Stock Market Returns[J], Journal of Business,1996,69(3):383-408.
25.Longin. From Value-at-Risk to Stress Testing:the Extreme Vaule Approach [J], Journal of Money Banking and Finance,2000,24(7):1097-1130.
26.Artzner.P..Coherent Measures of Risk[J],Mathematical Finance,1999,9(3): 203-228.
27.Taylor.A Quantile Regression Approach to Estimating the Distribution of Multiperiod Returns [J], Journal of Derivatives,1999,(7):64-78.
28.Taylor.A Quantile Regression Neural Network approach to Estimating the Conditional Density of Mlultiperiod Returns[J], Journal of Forecasting,2000, 19(4):299-311.
29.Chen,M-Y.and J-E.Chen.Application of Quantile Regression to Estimation of Value at Risk[D],manuscript, Department of Economics.National Chung Cheng University,Taiwan,2002
30. Neftci.Value-at-Risk Calculations.Extreme Events and Tail Estimation[J], Journal of Derivatives,2000,7(23):23-38.
31.方汉平,汪浩.论开放式基金的流动性风险及其控制[J],湖北财经高等专科学校学报,2001,(10)：27-29.
32.艾志群.开放式基金流动性风险初探[J],吉林财税高等专科学校学报,2001,(4)：13-16.
33.龙文标.开放式基金的流动性风险初探[J],山西财政税务专科学校学报,2002,(4)：19-21.
34.杜海涛.中国股市流动性风险测度研究[J],证券市场导报,2002,(11)：38-43.
35.郭来生.开放式基金流动性风险评估与管理研究[N],中国证券报,2003.3.28(5).
36.赵旭,吴冲锋.开放式基金流动性赎回风险实证分析与评价[J],运筹与管理,2003,12(6)：1-6.
37.陈日华,吴磊.开放式基金流动性风险及其管理模型研究[J],华东经济管理,2005,19(9)：141-144.
38.张洪建.开放式基金流动性风险研究(D),大连东北财经大学,2007.
39.彭志刚.开放式基金：对市场影响有多大[J],金融信息参考,2001,(8)：27-28.
40.一夫.我国开放式基金的市场环境及流动性管理[J],财经科学,2002,(4)：32-34.
41.屈文洲,吴世农.中国股票市场微观结构的特征分析-买卖报价价差模式及影响因素的实证研究[J],经济研究,2002,(1)：6-63.
42.许崇正.中国金融市场创新再论,北京：中国财政经济出版社[M],2006,35-47.
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