基于分形市场理论的基金投资风格漂移及其风险测度研究
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摘要
经过2008年美国次贷危机的巨大冲击,全球金融业发展面临着严峻挑战,美国金融全球霸主地位开始动摇,以亚洲为中心的新兴资本市场迅速崛起。2010年,我国作为亚洲最大的新兴资本市场发生了深刻变化,股指期货、融资融券等做空机制的推出增加了市场深度,基金产品的不断大量创新发行为我国基金业发展打开了空间,基金产品的开发有望成为我国基金业发展中的一道亮丽风景线。在金融危机与分形市场的现实背景下,我国基金业发展该如何去迎接挑战,寻找新的发展机遇——对基金产品进行定位、把握产品创新设计的灵魂?美国基金市场的发展经历了从无序到有序,从有序到有效的过程。在基金产品设计定位方面,经历了从提供理财服务转向提供产品与提供理财服务相结合的过程;在理财目标方面,基金投资者经历了从追求超额收益转向追求满意收益,再到追求风险收益的过程;在理财策略方面,经历了从依赖基金经理个人能力转向依赖投资风格理念,再到依赖投资风格理论的过程。在当今欧美资本市场中,基金投资风格与风格投资等理念已经完全被接受,逐步深入人心。未来我国基金业的发展又该如何从量变到质变,在产品设计与投资风格理念上走向世界的前列?
     国外对基金投资风格漂移研究始于20世纪90年代初,至今仍是个热点问题,在理论上已取得了丰硕成果,在实践上也得到了广泛应用。但与美国基金市场相比,我国基金发展初具规模,在基金产品设计灵魂上没有表现出显著的差异性,在投资运作过程中,基金投资风格趋同导致发生风格漂移现象。新兴市场的分形特征为基金发生投资风格漂移提供了现实可行性,基金经理宁愿违背宣称时的投资风格而发生所谓的风格漂移,意味着其背后折射出有获得短期超额收益的机遇,但机遇与风险并存,其中可能带来的漂移风险的可控性也就成了风格漂移能否成功的关键。本文基于此,引入分形理论来探索研究我国开放式基金投资风格漂移现象,对投资风格漂移收益的非线性特征及其风险测度进行系统研究,构建出科学的投资风格识别方法与漂移风险测度模型,以期为监管部门、基金公司、基金经理和投资者对投资风格漂移收益分形特征与所带来的漂移风险进行量化及控制提供方法基础,同时为我国未来基金业的繁荣发展提供理论指导。
     本文研究主要得出以下4点结论:
     1、通过引入非线性科学中的分形理论构建了分形市场现实背景下的基金投资风格理论分析框架,实证检验了我国股市风格资产存在长记忆性、标度不变性等分形特征;
     2、在我国资本市场呈分形特征的基础上,运用基于盒子分形维的基金投资风格识别方法与基于弹性分形维的基金投资风格漂移分析法对我国基金投资风格漂移进行了系统研究,一致得出我国基金普遍存在漂移现象,该结论也符合分形市场的现实背景;
     3、运用滑动窗口MF-DFA方法对我国开放式基金投资风格漂移收益进行了多重分形分析,得出基金投资风格漂移收益具有多重分形特征,进一步得出我国基金市场是非完全有效的,呈一定的分形特征,这为基金发生投资风格漂移提供了现实可行性;
     4、基金投资风格漂移是把双刃剑,在获取短期超额收益的同时,其背后也折射出巨大的风格漂移风险。通过构建多重分形波动率MF-VaR测度模型对基金投资风格漂移风险进行了测度,结果得出我国开放式基金普遍存在较大的风格漂移风险,这为监管部门进一步控制较严重的风格漂移现象,规范基金产品发行与投资行为提供理论支持。
     国内外学者已在基金投资风格识别、投资风格漂移的影响因素及其对基金业绩的影响等方面做了大量研究,但都是基于有效市场理论线性研究范式下开展的,在分形市场理论非线性研究范式下的基金投资风格漂移及其风险测度研究至今仍是空白。比较已有的相关研究成果,本文主要创新之处与贡献点如下:
     1、通过引入分形理论对基金投资风格理论体系做修正探索研究,构建了基金投资风格的分形分析框架,实证检验了股市风格资产的长记忆性、标度不变性等分形特征;
     2、在比较两种主流投资风格识别方法的基础上,结合我国资本市场的分形特征,提出了盒子分形维的投资风格识别方法FDSR与投资风格漂移程度的量化指标CIS,该方法相比传统识别方法能够避免风格资产多重共线性、缺乏T统计量显著检验等缺陷;
     3、提出了基于弹性分形维的基金投资风格漂移分析方法,推导出弹性分形维的计算公式,通过挖掘出其经济含义给出了投资风格漂移的阀值,为研究基金投资风格漂移提供了一种新范式,这可能成为测度与控制基金投资风格漂移风险的新工具;
     4、对基金投资风格漂移进行了量化,得到了投资风格漂移收益的计算公式。对传统MF-DFA方法进行了改进,提出了滑动窗口MF-DFA多重分形分析方法,该方法能在数据丢失与序列顺序倒置等方面得到改进,减少了分析结果的误差。并运用改进后的方法对我国开放式基金投资风格漂移收益的多重分形特征及其谱参数进行了研究;
     5、根据多重分形谱参数与奇异指数提炼出多重分形波动率测度,构建了投资风格漂移风险MF-VaR测度模型,并运用该模型对我国79只开放式基金投资风格漂移风险进行了测度,相比最新GARCH族高级计量模型,具有更高的测度精度与稳健性。
After the huge strike of U.S. subprime crisis in 2008, global financial industry faced serious challenges. While the role of the United States as a global hegemony in finance began to shake, Asia-centered emerging capital markets rapidly rose. As the largest emerging capital market in Asia,China underwent profound changes in 2010, when stock index futures, margin trading and other short mechanisms increased the depth of the market. The constant issuing innovation of fund-products widened the road for the funds development, which might be expected to become a beautiful landscape in fund industry. In the background of fractal market and financial crisis, how can Chinese fund industry meet the challenge and find new development opportunities-positioning fund products and grasping the soul of product innovation? The development of the U.S. fund market has gone through disorder to order, and then to effective process. At the aspect of product design and position, fund industry has experienced a shift from the product provision to a combination of financial services and product provision; at the aspect of financial goal, the fund investors’pursuit has changed from excess returns to satisfactory returns,and then to risk returns; at the aspect of financial strategy, there has been a conversion from relying on the ability of managers to dependend on investment style philosophy, and then to investment style theory. In today's capital market in Europe and America, philosophy such as investment style and style investment has been fully accepted, and gradually popular. How can the fund-industry development in China transform from quantity to quality? How can the concept of product design and investment style be on the forefront of the world?
     Foreign research on fund investment style drift began in the early 1990s, which is still a hot issue so far. The research in this field has achieved fruitful results in theory, it also has been widely used in practice. Compared with U.S. fund market, China's fund development just begins to take shape. The funds do not show significant difference in the soul of product design in China. What’s more, the investment-style convergence results in style drift in the course of investment operation. It is the fractal characteristic of emerging markets that provides a realistic possibility for fund investment style drift. Contrary to the claimed investment style, fund managers might prefer to the so-called style drift, reflecting an underlying opportunity of short-term excess returns. However, opportunities coexist with risk, and the controllability of the drift risk will become the key factor to the success of style drift. Based on this, this paper use fractal theory to explore investment style drift of the open-end funds.Besides,this paper does a systematic study on the nonlinear characteristic of investment style drift return, and constructs a scientific model to measure the investment style drift risk. The study is expected to offer methods of quantifying the fractal characteristics of investment style drift return and drift risk for regulators, fund companies, fund managers and investors, as well as to provide theoretical guidance for the prosperous development of the fund industry in the future.
     The main conclusions of this paper are as follows:
     1.By introducing fractal theory in non-linear science, this paper constructs a theoretical framework of fund investment style in the reality of fractal market, and empirical test finds that: the style asset of China's stock market has a fractal feature of both long memory and invariant scaling and so on;
     2.Considering fractal characteristics of Chinese capital market, this paper systematically studies the fund investment style drift by recognizing fund investment style based on the box-fractal dimension and analyze fund investment style drift based on elastic-fractal dimension. They draw the same conclusion that the investment style drift is a common phenomenon, which is also consistent with the real fractal market;
     3.Using sliding window MF-DFA method, this paper carries out multi-fractal analysis on investment style drift return of open-end funds. It is concluded that the investment style drift return shows multifractal characteristics, and found fund market is non-fully effective in China, presenting fractal characteristic to some extent, which provides a realistic feasibility for fund investment style drift;
     4.The fund investment style drift is a double-edged sword. Along with obtaining short-term excess return, it also reflects the huge style drift risk. This paper measures the investment style drift risk by constructing multifractal volatility MF-VaR model. The result indicates that drift risk is generally high in the open-end funds, which provides theoretical support for regulators to control the serious style drift, as well as to regulate fund products issue and investment behavior.
     Scholars home and abroad have studied a lot on the fund investment style identification, investment style drift factors and its impact on the fund's performance, but they are all carried out under the linear paradigm based on efficient market theory. Comparatively, research on fund investment style drift and risk measurement under non-linear paradigm based on fractal market theory is still blank.Comparison of the existing research results, innovation and contribution of this paper are as follows:
     1.This paper introduces fractal theory to revise exploratory research on the field of fund investment style, constructs a fractal analytical framework of fund investment style, and proves that the Chinese stock style asset has a fractal feature of long memory and invariant scaling;
     2.After comparing the two traditional investment style identification methods, this paper recognizes fund investment style based on the box-fractal dimension(FDSR) and analyzes fund investment style drift based on the elastic-fractal dimension CIS, according to the fractal characteristic of capital market. Compared to the previous identification method, this method is able to avoid style assets having multi-collinearity or lacking T-statistic significant test and other defects;
     3.This paper proposes analysis the fund investment style drift method based on elastic- fractal dimension, and deduces the computing formula of elastic-fractal dimension.In addition, this paper gives the threshold of investment style drift by mining its economic implications, which provides a new kind of research on fund investment style drift and may become a new tool to measure and control the fund investment style drift risk;
     4.This paper quantifies fund investment style drift and derives investment style drift return formula. It modifies the traditional MF-DFA and put forword the multi-fractal analysis method of sliding window MF-DFA. The method makes an improvement in data loss and sequence inversion and reduces analysis result error. And use the modified method to analyze the multi-fractal characteristic and spectrum parameter of investment style drift return;
     5.This paper extracts the multifractal volatility measurement according to multifractal spectrum parameter and singularity exponent, and constructs a MF-VaR model to measure investment style drift risk. This paper uses the MF-VaR model to measure investment style drift risk of 79 open-end funds, whose measurement results are more precise and robust than the latest GARCH family high-level econometric models.
引文
注7国内学者最早进行实证研究的见熊鹏,刘煜辉.近四成投资基金“言行不一”[J].新财富,2003,(11):40-42.
    [1]牛丽静.揭密基金风格漂移[N].财经时报,2006-08-21(B04).
    [2]高清海.基金投资风格漂移带来了什么[N].中国证券报,2007-06-04(A13).
    [3]付建利.刘治平:基金投资最大问题是风格漂移[N].证券时报,2009-11-09(B04).
    [4] Sharpe,W.F.Asset Allocation:Management Style and Performance Measurement[J].Journal of Portfolio Management,1992,18(2):7-19.
    [5] Fama,E.F&French,K.R.Common Risk Factors in the Returns on Bonds and Stocks[J]. Journal of Financial Economics,1993,33(2):3-56.
    [6] Gruber,M.J.Another Puzzle:The Growth in Actively Managed Mutual Funds[J].Journal of Finance,1996,51(3):783-810.
    [7] Carhart,M.M.On Persistence in Mutual Fund Performance[J].Journal of Finance,1997, 52(1):57-82.
    [8] Volkman,D.A.Market Volatility and Perverse Timing Performance Of Mutual Fund Managers[J].Journal of Financial Research,1999,22(4):449-470.
    [9] Mandelbrot B.B.A Multifractal Walk Down Wall Street[J].Scientific American,1999, 280(2):70-73.
    [10] Barkoulas J.T.,Baum C.F.&Travlos N.Long Memory in the Greek Stock Market[J]. Applied Financial Economics,2000,10(2):177-184.
    [11] Lim Kian-Ping&Venus Khim-Sen Liew.Nonlinear Mean Reversion in Stock Prices: Evidence from Asian Markets[J].Applied Financial Economics Letters,2007,3(1):25-29.
    [12] Matteo T.D.Multi-scaling in Finance[J].Quantitative Finance,2007,7(1):21-36.
    [13] Christopherson,J.A.Equity Style Classification[J].Journal of Portofolio Management, 1995,21(3):32-43.
    [14] Bernstein,R.Style Investing:Unique Insight into Equity Management[M].New York:John Wiley&Sons,1995.
    [15] Siegel,J.J.Stocks for the Long Run:The Definitive Guide to Financial Market Returns and Long Term Investment Strategies[M].New York:McGraw-Hill,1998.
    [16] Sharpe,W.F,Alexander,G.J&Bailey,J.V.Investments[M].Upper Saddle River:Prentice-Hall, 1999.
    [17] Schwob,R.Style and Style Analysis from a Practitioner’s Perspective:What is It and What does It Mean for European Equity Investors?[J].Journal of Asset Management,2000,1(1): 39-59.
    [18]戴志敏.我国开放式基金的风格趋同性研究[J].浙江大学学报(人文社会科学版), 2003,33(4):33-39.
    [19]刘朝晖.开放式基金产品风格剖析[N].上海证券报,2003-03-05(B04).
    [20]杨朝军.金融投资风格与策略[M].北京:中国金融出版社,2005.
    [21]叶莉,刘巍.我国开放式基金的风格趋同性研究[J].现代财经,2006,26(8):24-28.
    [22]郭文伟.开放式基金投资风格漂移及风格资产轮换策略研究[D].华南理工大学博士学位论文,2010.
    [23] Idzorek T.M&Bertsch F.The Style Drift Score[J].Journal of Portfolio Management,2004, 31(1):76-83.
    [24] Basu,S.The Investment Performance of Common Stocks in Relation to Their Price- Earnings Ratios:A Test of the Efficient Market Hypothesis[J].Journal of Finance,1977, 32(3):663-682.
    [25] Banz,R.The Relationship Between Return and Market Value of Common Stocks[J]. Journal of Financial Economics,1981,9(1):3-18.
    [26] Reinganum,M.Misspecification of Capital Asset Pricing:Empirical Anomalies Based on Earnings’Yield and Market Values[J].Journal of Financial Economics,1981,9(1):16-46.
    [27] Fama,E.F&French,K.R.The Cross-Section of Expected Stock Returns[J].Journal of Finance,1992,47(2):427-465.
    [28] Stattman&Dennis.Book values and stock returns[J].The Chicago MBA:A Journal of Selected Papers,1980,(4):25-45.
    [29] Ariel,R.A Monthly Effects in Stock Returns[J].Journal of Financial Economics,1987, 18(1):161–174.
    [30] Bhandari,L.Debt/Equity Ratio and Expected Common Stock Returns:Empirical Evidence [J].Journal of Finance,1988,43(2):507-28.
    [31] Aggarwal,R&Rivoli,P.Seasonal and Day of the Week Effects in Four Emerging Stock Markets[J].Financial Review,1989,24(4):541-550.
    [32] Jaffe,J.,Keim D&Westerfield R.Earnings Yields,Market Values and Stock Returns[J]. Journal of Finance,1989,44(1):135-148.
    [33]林天中.台湾股票市场三因子:系统风险、公司规模及净值市价比实证研究[D].台湾:国立清华大学硕士学位论文,1997.
    [34]赵家敏,严雄.中国股票市场换月效应及其成因的实证研究[J].南方经济,2010,(2): 42-52.
    [35] Tobin,J.Liquidity Preference as Behavior Towards Risk[J].Review of Economic Studies,1958,25(1):65-86.
    [36] Sharpe,W.F.Capital Asset Prices:A Theory of Market Equilibrium under Conditions of. Risk[J].Journal of Finance,1964,19(3):425-442.
    [37] Lintner,J.The Valuation of Risky Assets and The Selection of Risky Investment in Stock Portfolios and Capital Budgets[J].Review of Economics and Statistics,1965,47(1):13-37.
    [38] Mossin,J.Equilibrium in a Capital Asset Market[J].Econometrica,1966,34(4):768-783.
    [39] Ross,S.The Arbitrage Theory of Capital Asset Pricing[J].Journal of Economic Theory, 1976,13(3):341-360.
    [40] Markowitz H. Portfolio Selection[J].Journal of Finance,1952,7(1):77-91.
    [41] Samuelson,P.A.Rational Proof that Properly Anticipated Prices Fluctuate Randomly[J]. Industrial Management Review,1965,6(2):41-49.
    [42] Fama,E.F.Efficient Capital Market:A Review of Theory and Empirical Work[J].Journal of Finance,1970,25(2):384-417.
    [43] Peters E.E.A Chaotic Attractor for the S&P500[J].Financial Analysts Journal,1991,47(2): 55-62.
    [44] Peters E.E.Fractal Market Analysis:Applying Chaos Theory to Investment and Econo- mics[M].New York:John Wiley&Sons,1994.
    [45] Mandelbrot B.B.Fractals:Form,Chance and Dimension[M].San Francisco:Freeman,1977.
    [46] Thaler,R.Advances of Behavioral Finance[M].New York:McGraw Hill Press,1993.
    [47] Shleifer,A.Inefficient Markets:An Introduction to Behavioral Finance[M].Oxford:Oxford University Press,2000.
    [48] Susan I.,Cohen L.&Starks T.Estimation Risk and Incentive Contracts for Portfolio Managers[J].Management Science,1988,34(9):1067-1079.
    [49] Bolton P.&Harris C.The Continuous-time Principal-agent Problem:Frequent-monitoring Contracts[R].Working Paper,Princeton University,2002.
    [50] Chan K,Chen H&Lakonishok J.On Mutual Fund Investment Styles[J].Review of Financial Studies,2002,15(5):1407-1437.
    [51] Laurens Swinkels&Liam Tjong-A-Tjoe.Can Mutual Funds Time Investment Styles?[J]. Journal of Asset Management,2007,8(2):123-132.
    [52]赵建明.基金投资风格与实证对照[N].金融时报,2001-09-19(B05).
    [53]杨朝军,蔡明超,徐慧泉.中国证券投资基金风格分类研究[J].上海交通大学学报, 2004,38(3):359-367.
    [54]赵宏宇.证券投资基金的投资风格分析和比较[J].证券市场导报,2005,(10):58-62.
    [55]欧阳敬东.浅谈我国开放式基金的投资风格[J].税务研究,2007,(7):49-51.
    [56]王敬,刘阳.证券投资基金投资风格:保持还是改变?[J]金融研究,2007,(8):120-130.
    [57] Lobosco,A&Dibartolomeo D.Approximating the Confidence Intervals for Sharpe Style Weight[J].Financial Analysts Journal,1997,53(4):80-85.
    [58] Gallo,J.G&Lockwood L.J.Benefits of Proper Style Classification of Equity Portfolio Managers[J].Journal of Portfolio Management,1997,23(3):47-55.
    [59]李玉刚.基金风格与选择能力研究[R].国泰君安证券研究所研究报告,2002.
    [60]曾晓洁,黄嵩,储国强.基金投资风格与基金分类的实证研究[J].金融研究,2004, (3):66-78.
    [61]赵坚毅,于泽,李颖俊.投资者参与和证券投资基金风格业绩的评估[J].经济研究,2005, (7):45-55.
    [62]张津,王卫华.我国证券投资基金投资风格实证研究[J].中央财经大学学报,2006,(1): 29-33.
    [63]李学峰,徐华.基金投资风格漂移及其对基金绩效的影响研究[J].证券市场导报,2007, (8):70-77.
    [64]宋威.风格漂移与基金绩效[J].商业研究,2009,(6):153-156.
    [65] Trzcinka,C.“Equity Style Classifications”:Comment[J].Journal of Portfolio Management, 1995,21(3):44-46.
    [66] Rekenthaler J,Gambera M,Charlson J.Estimating Portfolio Style: A Comparative Study of Portfolio-Based Fundamental Analysis and Returns-Based Style Analysis[R]. Morningstar Research Report,2002.
    [67] Kahn,V.A Question of Style:Must Consistency Equal Mediocrity in Mutual Funds?[J]. Financial World,1996,(2):70-75.
    [68] Jenke R.ter Horst,Theo E.Nijman,Frans A.de Roon.Evaluating Style Analysis[J].Journal of Empirical Finance,2004,11(1):29-53.
    [69]董铁牛,杨乃定,邵予工.中国开放式基金投资风格分析[J].管理评论,2008,20(7):3-9.
    [70] Wayne Ferson&Rudi Schadt.Measuring Fund Strategy and Performance in Changing Economic Conditions[J].Journal of Finance,1996,51(2):425-462.
    [71] Gallo,J.G&Lockwood L.J.Fund Management Changes and Equity Style Shifts[J]. Financial Analysts Journal,1999,55(11):44-52.
    [72] Chevalier,J. A&Ellison G.D.Career Concerns of Mutual Fund Managers[J].Quarterly Journal of Economics,1999,114(2):389-432.
    [73] Annaert J&Campenhout G.V.Style Breaks in Return-Based Style Analysis[R].WorkingPaper,University of Antwerp,2002.
    [74] Cooper M.J.,Gulen H&Rau P.R.Changing Names with Style:Mutual Fund Name Changes and Their Effects on Fund Flows[J].Journal of Finance,2005,60(6):2825-2858.
    [75]熊胜君,杨朝军.中国证券投资基金投资风格变化原因分析[J].哈尔滨商业大学学报(自然科学版),2005,21(6):801-805.
    [76]朱丹.我国基金投资风格及其成因[D].暨南大学硕士学位论文,2006.
    [77]郭文伟,宋光辉,许林.基金经理个人特征对基金风格漂移的影响研究[J].软科学,2010, 24(2):123-128.
    [78] Brown S.J&Goetzmann W.N.Hedge Funds with Style[J].Journal of Portfolio Manage- ment,2003,29(2):101-112.
    [79] Gibson,R&Gyger,S.The Style Consistency of Hedge Funds[J].European Financial Management,2007,13(2):287-308.
    [80] Kathryn A.H.,Robert W.F.Style Drift,Fund Flow and Fund Performance:New Cross- sectional Evidence[J].Financial Services Review,2007,16(1):55-71.
    [81] Andrew B.A.,Kingsley F,David R.G.Style Drift and Portfolio Management for Active Australian Equity Funds[J].Australian Journal of Management,2008,32(3):387-418.
    [82]付金花.投资风格变异对基金绩效的影响研究[D].湖南大学硕士学位论文,2006.
    [83]李学峰,徐华,李荣霞.基金投资风格一致性及其对基金绩效的影响[J].财贸研究, 2010,(2):89-97.
    [84] Lobosco A.Style/Risk-Adjusted Performance[J].Journal of Portfolio Management,1999, 26(4):65-68.
    [85] Modigliani,F.&Modigliani L.Risk-Adjusted Performance[J].Journal of Portfolio Manage- ment,1997,23(2):45-54.
    [86] Mandelbrot B.B.The Variation of Certain Speculative Prices[J].Journal of Business,1963, 36(4):394-419.
    [87] Mandelbrot B.B.The Fractal Geometry of Nature[M].San Francisco:Freeman,1982.
    [88] Mandelbrot,B.B,Fisher,A&Calvet,L.A Multifractal Model of Asset Returns[R].Cowles Foundation Discussion Paper,Yale University,1997.
    [89] Engle R.F.Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation[J].Econometrica,1982,50(4):987-1007.
    [90] Bollerslev T.Generalized Autoregressive Conditional Heteroskedasticity[J].Journal of Econometrics,1986,31(3):307-328.
    [91] Engle R.F,Lilien D.M,Robins R.P.Estimating Time Varying Risk Premia in the TermStructure:the ARCH-M Model[J].Econometrica,1987,55(2):391-407.
    [92] Nelson D.B.Conditional Heteroskedasticity in Asset Returns:A New Approach[J].Econo- metrica,1991,59(2):347-370.
    [93] Glosten L.R,Jagannathan&Runkle D.On the Relation between the Expected Value and the Volatility of the Nominal Excess Returns on Stocks[J].Journal of Finance, 1993,48(5):1779-1801.
    [94] Ding Z.,Granger C.&Engle R.A Long Memory Property of Stock Market Returns. and a New Model[J].Journal of Empirical Finance,1993,1(1):83-106.
    [95] Zakoian J.M.Threshold Heteroskedastic Models[J].Journal of Economic Dynamics and Control,1994,18(5):931-955.
    [96] Baillie R.T.,Bollerslev T.,Mikkelsen H.O.Fractionally Integrated Generlized Autore- gressive Conditional Heteroskedasticity[J].Journal of Econometrics,1996,74(1):3-30.
    [97] Tse Y.K.The Conditional Heteroscedasticity of the Yen-Dollar Exchange Rate[J].Journal of Applied Econometrics,1998,13(1):49-55.
    [98] Davidson,J.Moment and Memory Properties of Linear Conditional Heteroscedasticity Models and a New Model[J].Journal of Business and Economic Statistics,2004,22(1): 16-29.
    [99] Andersen T.G,Bollerslev T,Diebold F.X&Ebens H.The Distribution of Realized Stock Return Volatility[J].Journal of Financial Economics,2001,61(1):43-76.
    [100] Giot P&Laurent S.Value-at-Risk for Long and Short Trading Positions[J].Journal of Applied Econometrics,2003,18(6):641–663.
    [101] Morgan J.P.RiskMetrics Technical Document[M].New York:Morgan Trust Company Global Research,1994.
    [102] Jorion P.Risk:Measuring the Risk in Value at Risk[J].Financial Analysts Journal,1996, 52(6):47-56.
    [103] Tang T.L.&Shieh S.J.Long-Memory in Stock Index Futures Markets:A Value-at-Risk Approach[J].Physica A,2006,366(1):437-448.
    [104] Kupiec P.H.Techniques for Verifying the Accuracy of Risk Measurement Models[J]. Journal of Derivatives,1995,3(2):73-84.
    [105] Engle&Manganelli.CAViaR:Conditional Autoregressive Value at Risk by Regression Quantiles[J].Journal of Business and Economic Statistics,2004,22(4):367-381.
    [106] Broocka W.A. Scheinkmanb J.A.Dechertc W.D.&LeBarona B. A Test for Independence Based on the Correlation Dimension Econometric Reviews[J].Econometric Reviews, 1996,15(3):197-235.
    [107] Box G.E.P.&Pierce D.A.Distribution of Residual Autocorrelations in Autoregressive- integrated Moving Average Time Series Models[J].Journal of the American Statistical Association,1970,65(332):1509-1526.
    [108] Ljung G.M.&Box G.E.P.On a Measure of Lack of Fit in Time Series Models[J]. Biometrika,1978,65(2):297-303.
    [109] Geweke J&Porter-Hudak S.The Estimation and Application of Long Memory Time Series Models[J].Journal of Time Series Analysis,1983,4(4):221-238.
    [110] Falconer Kenneth.分形几何——数学基础及其应用[M].曾文曲译,北京:人民邮电出版社,2007.
    [111] Mandelbrot B.B.Statistical Methodology for Non-periodic Cycles:From the Covariance to R/S Analysis[J].Annals of Economics and Social Measurement,1972,(1):257-288.
    [112] Wermers R.Mutual Fund Performance:An Empirical Decomposition into Stock-Picking Talent,Style,Transaction Costs and Expenses[J].Journal of Finance,2000,(4):1655-1703.
    [113] Hurst H.E.The Long-term Storage Capacity of Reservoirs[J].Transcactions of the American Society of Civil Engineers,1951,(116):770-799.
    [114] Mandelbrot B.B&Wallis J.R.Robustness of the Rescaled Range R/S in the Measurement of Noncyclic Long-run Statistical Dependence[J].Water Resource Research,1969, (5):967-988.
    [115] Lo A.W.Long-term Memory in Stock Prices[J].Econometrica,1991,59(5):1279-1313.
    [116] Seong-Min Yoon&Sang Hoon Kang.Non-periodic Cycles and Long-memory Property in the Korean Stock Market[J].The Journal of the Korean Economy,2008,9(3):403-424.
    [117] Triki Mohamed Bilel&Selmi Nadhem.Long Memory in Stock Returns:Evidence of G7 Stocks Markets[J].Research Journal of International Studies,2009,(9):36-46.
    [118] Siow-Hooi Tan,Lee-Lee Chong,Peik-Foong Yeap.Long Memory Properties in Stock Prices:Evidence from the Malaysian Stock Market[J].European Journal of Economics, 2010,(18):77-84.
    [119]史永东.中国证券市场股票收益持久性的经验分析[J].世界经济,2000,(11):29-33.
    [120]徐迪,吴世农.上海股票市场的分形结构分析[J].中国经济问题,2002,(1):27-33.
    [121]范英,魏一鸣.基于R/S分析的中国股票市场分形特征研究[J].系统工程,2004,22(11): 46-51.
    [122]郝清民.中国股市收益率长记忆性R/S非线性分析[J].管理科学学报,2007,(2): 115-117.
    [123]谢朝华,李忠,郑咏梅,文凤华.中国股票市场分形与混沌特征:1994-2008[J].系统工程,2010,28(6):30-35.
    [124]胡雪明,宋学峰.沪深股票市场的多重分形分析[J].数量经济技术经济研究,2003,(8): 124-127.
    [125]施锡铨,艾克凤.股票市场风险的多重分形分析[J].统计研究,2004,(9):33-36.
    [126]苑莹,庄新田.股指时间序列的多重分形Hurst分析[J].管理学报,2007,4(4):449-452.
    [127]黄诒蓉,罗奕.基于经典R/S分析方法的H指数估计有效性评价[J].统计与信息论坛, 2009,24(8):59-64.
    [128]王翼,王歆明.MATLAB基础及在经济学与管理科学中的应用[M].北京:机械工业出版社,2009.
    [129]王春峰,张庆翠,李刚.中国股票市场收益的长期记忆性研究[J].系统工程,2003,21(1): 22-28.
    [130]陈梦根.中国股市长期记忆效应的实证研究[J].经济研究,2003,(3):70-78.
    [131]张卫国,胡彦梅,陈建忠.中国股市收益及波动的ARFIMA–FIGARCH模型研究[J].南方经济,2006,(3):108-112.
    [132]李海奇,屠新曙,段琳琳.中国股票市场波动长记忆建模研究[J].统计与决策,2006,(8): 17-20.
    [133] Fernandez C.&Steel M.F.J.On Bayesian Modeling of Fat Tails and Skewness[J].Journal of the American Statistical Association,1998,93(441):359-371.
    [134] Wilson Kwana,Wai Keung Lib&Guodong Lib.On the Estimation and Diagnostic Checking of the ARFIMA–HYGARCH Model[J].Computational Statistics&Data Analysis,2010,(7):1-13.
    [135] Palm F.C.&Vlaar P.J.G.,Simple Diagnostic Procedures for Modeling Financial Time Series[J].Allgemeines Statistisches Archiv,1997,(81):85-101.
    [136] Kantelhardt J.W,Zschiegner S.A,Koscielny B.E,Havlin S,Bunde A,Stanley H.E. Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series[J].Physica A,2002,316(1-4):87-114.
    [137] Matia K&Ashkenazy Y.Multifractal Properties of Price Fluctuations of Stocks and Commodities[J].Europhys Letters,2003,61(3):422-428.
    [138] Ramirez J.A,Paredes G.E&Vazquez A.Detrended Fluctuation Analysis of the Neutronic Power from A Nuclear Reactor[J].Physica A,2005,351(2-4):227-240.
    [139] Kantelhardt J.W,Rybski D,Zschiegner S.A,Braun P,Koscielny-Bunde E,Livina V,Havlin S&Bunde A.Multifractality of River Runoff and Precipitation:Comparison of FluctuationAnalysis and Wavelet Methods[J].Journal of Hydrology,2003,330(8):240-245.
    [140] Koscielny-Bunde E,Kantelhardt J.W,Braun P,Bunde A.&Havlin S.Long-term Persistence and Multifractal of River Runoff Records:Detrended Fluctuatio Studies[J]. Journal of Hydrology,2006,322(1-4):120-137.
    [141] Gomez J.D.&Poveda G.Estimacion Del Espectro Multifractal Para Series De Precipitacion Horaria en Los Andes Tropicales de Colombia[J].Rev.Acad.Colomb. Cienc,2008,32(125):483-502.
    [142]卢方元.中国股市收益率的多重分形分析[J].系统工程理论与实践,2004,24(6):50-54.
    [143]曹广喜,史安娜.沪深股市波动的多重分形结构分析[J].经济经纬,2006,(6):136-139.
    [144]曹广喜.基于分形分析的我国股市波动性研究[M].北京:经济科学出版社,2008.
    [145]都国雄,宁宣熙.上海证券市场的多重分形特性分析[J].系统工程理论与实践,2007, 27(10):40-47.
    [146]刘维奇,牛奉高.沪深两市多重分形特征的成因及其变化[J].经济管理,2009,31(12): 138-143.
    [147] Jiang Zhiqiang&Zhou Weixing.Multifractal Analysis of Chinese Stock Volatilities based on the Partition Function Approach[J].PhysicaA,2008,387(19-20):4881-4888.
    [148]周炜星.上证指数高频数据的多重分形错觉[J].管理科学学报,2010,13(3):81-86.
    [149]苑莹,庄新田.国际汇率多重分形消除趋势波动分析[J].管理科学,2007,20(4):80-85.
    [150]苑莹,庄新田.股票市场多重分形性的统计描述[J].管理评论,2007,19(12):3-8.
    [151]苑莹,庄新田,金秀.基于MF-DFA的中国股票市场多标度特性及成因分析[J].管理工程学报,2009,23(4):96-99.
    [152]苑莹,庄新田,金秀.期货价格收益序列的多重分形统计描述及成因分析[J].东北大学学报(自然科学版),2010,31(4):605-608.
    [153]宋加旺.基于分形市场理论和Copula函数理论的中国资本市场实证研究[D].天津大学硕士学位论文,2005.
    [154]胡彦梅,张卫国,陈建忠.中国股市长记忆的修正R/S分析[J].数理统计与管理,2006, 25(1):73-77.
    [155]黄诒蓉,罗奕.资本市场分形结构的理论与方法[J].当代财经,2006,(3):54-59.
    [156]李宇海.我国证券市场多时间跨度的分形特征研究[J].经济经纬,2009,(1):150-153.
    [157]王鹏,魏宇,张蕾.中国交易所债券市场分形特征的实证研究[J].数理统计与管理, 2009,28(2):324-330.
    [158]陈丽.基于分形维的经济均衡理论研究[J].经济经纬,2010,(2):1-4.
    [159]樊智,张世英.金融市场的效率与分形市场理论[J].系统工程理论与实践,2002,22(3): 13-19.
    [160] Mcleod A.I&Hipel K.W.Simulation Procedures for Box-Jenkins Models[J].Water Resources Research,1978,14(5):969-975.
    [161]袁境.中国开放式基金投资风格趋同化的因子分析[J].经济体制改革,2005,(5): 126-130.
    [162]黄诒蓉.中国股市分形结构:理论与实证[M].广州:中山大学出版社,2006.
    [163]司马则茜,蔡晨,李建平.我国银行操作风险的分形特征[J].中国管理科学,2008,16(1): 42-47.
    [164] Yuan Y,Zhuang X.T,Jin X.Measuring Multifractality of Stock Price Fluctuation Using Multifractal Detrended Fluctuation Analysis[J].Physica A,2009,388(11):2189-2197.
    [165] Bocker K&Klüppelberg C.Operational VAR:A Closed-form Approximation[J].Risk, 2005,18(12):90-93.
    [166]郑文通.金融风险管理的VaR方法及其应用[J].国际金融研究,1997,13(9):58-62.
    [167]邵欣炜,张屹山.基于VaR的证券投资组合风险评估及管理体系[J].数量经济技术经济研究,2003,(12):66-70.
    [168]余素红,张世英,宋军.基于GARCH模型和SV模型的VaR比较[J].管理科学学报, 2004,7(5):61-66.
    [169]肖智,傅肖肖,钟波.基于EVT-BM-FIGARCH的动态VaR风险测度[J].中国管理科学, 2008,16(4):18-23.
    [170]林宇,卫贵武,魏宇,谭斌.基于Skew-t-FIAPARCH的金融市场动态风险VaR测度研究[J].中国管理科学,2009,17(6):17-24.
    [171] Ping-Tsung Wu,Shwu-Jane Shieh.Value-at-Risk Analysis for Long Term Interest Rate Futures:Fat-tail and Long Memory in Return Innovations[J].Journal of Empirical Finance,2007,14(1):248-259.
    [172] Ming-Chih Lee,Chien-Liang Chiu&Wan-Hsiu Cheng.Modeling Value-at-Risk for Oil Prices Using a Bootstrapping Approach[J].International Research Journal of Finance and Economics,2010,(40):7-19.
    [173] Laurent S.&Peters J.–P. G@RCH 2.2:An Ox Package for Estimating and Forecasting Various ARCH Models[J].Journal of Economic Surveys,2002,16(3):447-484.
    [174] Hansen P.R&Lunde A.A Forecast Comparison of Volatility Models:Does Anything Beata GARCH(1,1)?[J].Journal of Applied Econometrics,2005,20(7):873-889.
    [175] Nolan J.P.Numerical Computation of Stable Densities and Distribution Functions[J]. Comm.in Stat.Stochastic Models,1997,13(3):759-774.
    [176]魏宇,黄登仕.基于多标度分形理论的金融风险测度指标研究[J].管理科学学报,2005, 8(4):50-59.
    [177]魏宇.金融市场的收益分布与EVT风险测度[J].数量经济技术经济研究,2006,(4): 101-110.
    [178]魏宇,余怒涛.中国股票市场的波动率预测模型及其SPA检验[J].金融研究,2007,(7): 138-150.
    [179]王鹏,王建琼.中国股票市场的多分形波动率测度及其有效性研究[J].中国管理科学, 2008,16(6):9-15.
    [180]王鹏,魏宇,王建琼.基于多分形波动率测度的权证定价方法研究[J].管理科学,2009, 22(2):106-113.
    [181] Wei Y&Wang P.Forecasting Volatility of SSEC in Chinese Stock Market Using Multifractal Analysis[J].Physica A,2008,387(7):1585-1592.
    [182] Hansen&Lunde.Consistent Ranking of Volatility Models[J].Journal of Econometrics, 2006,131(1-2):97–121.
    [183] Andersen T.G.&Bollerslev T.Answering the Skeptics:Yes,Standard Volatility Models Do Provide Accurate Forecasts[J].International Economic Review,1998,39(4):885-905.
    [184] Andersen T.G.,Bollerslev T.&Meddahi N.Correcting the Errors:Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities[J].Econometrica, 2005,73(1):279-296.
    [185] Andersen T.G.,Bollerslev T.,Frederiksen P.&Nielsen M.Continuous-time Models, Realized Volatilities and Testable Distributional Implications for Daily Stock Returns [J].Journal of Applied Econometrics,2010,25(2):233-261.
    [186]齐晓楠,赵秀娟,王一鸣,汪寿阳.开放式基金信息披露制度的国际比较[J].管理评论, 2009,21(8):3-12.

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