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基于改进一般失望模型的投资组合与资产定价研究
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摘要
经典投资组合和资产定价理论采用了源于新古典主义经济学的同质经济概念,假设投资者的经济决策是完全理性的。但理性并非人类行为的唯一驱动力,还会更多地受主观偏好等多重因素的影响。对资产的收益和风险采用不同的度量方法,会得到不同的投资组合方案,进一步也会得出不同的资产定价模型。投资者所持有的资产具有不同的类型和不同程度的风险,这些风险会给投资者带来相应的损失,因此投资者会对相应的资产进行必要的与风险相关的分析和评估,从而采取符合其投资目的和风险偏好的投资策略,减少其可能遭受的损失。而资产定价模型反应的则是整个市场处于均衡状态时资产的风险与其均衡价格之间的关系。因此深入研究并理解已有先进投资组合与资产定价理论的相关研究成果,在此基础上根据行为主体的真实心理感受及市场的实际运行状况对相关理论进行发展与完善,具有重要的理论与实际意义。
     本文首先对已有的风险偏好和风险度量以及投资组合优化和资产定价理论进行了总结与评价,指出已有理论存在的缺点与不足。在此基础上对已有理论进行改进与完善,提出了改进的一般失望模型,在这一改进的模型中,原有的行为主体目标收益参考点由固定的期望收益变为更为灵活的一般性收益参考点,同时采用适用性更强的线性分段效用函数替代了原有的效用函数,使得新的改进后的一般失望模型能够反映行为主体的多层次风险感受。
     其次,本文在改进的一般失望模型基础上构建了两类新的投资组合优化模型,其中一类以改进的一般失望模型作为目标函数,这类投资组合优化模型能够更为全面的反映行为主体或投资者的多重风险偏好,并为其提供相应的更为符合要求的投资组合方案,另一类投资组合优化模型以改进的一般失望模型对投资组合收益的偏度进行控制。与已有的偏度控制方法相比,以改进的一般失望模型进行偏度控制可以在满足相同投资目标的情形下为投资者提供更多的获取超额收益的机会。
     再次,本文在基于改进的一般失望模型的投资组合优化模型的基础上,推导出了单参考点情形下的资产定价模型,进而又给出了多参考点情形下的资产定价模型,并对这一模型进行了相关的实证研究,同时对模型中不同风险偏好对应的不同贝塔系数进行时变特征的研究,以系统的分析不同风险偏好对应的不同类型资产定价因子的时变特征。
     最后,本文对多参考点情形的基于改进一般失望模型的资产定价模型进行了进一步扩展,使其包括更多类型的资产定价风险因子,并以这个模型为基础,将流动性风险因子引入到资产定价模型中,同时本文对给出的包含流动性风险定价因子的定价模型进行相关实证研究,并进一步分析流动性风险贝塔的各种时变性特征,研究结果表明,本文对资产定价模型进行的扩展性研究是合理可行的。
Traditional portfolio and asset pricing theory adopt the concept ofhomogeneous economy which originated from neoclassical economics, assumingthe investors and their investment decisions are completely rational. However,rationality is not the only reason driving the human behavior but also other fact orsaffecting, such as subjective preferences and so on. With different measurement ofasset return and risk, there can exist differentiated portfolio for investors, and assetcan be priced differently with distinct pricing model. Investors holds assets ofvarious type and risk, and related risk bring losses to investors, for the reason ofwhich investors carry out necessary analysis and assessment of asset risk, and adoptrelative strategy consider with investors' objective and preference with less losses.Asset pricing model is the very formulation that reflects the relationship betweenasset risk and return in the situation of equilibrium market. Therefore going deepinto and comprehending current advanced theories of portfolio and asset pricing,based on which developing relative theories according the real feeling of investorsand real situation of market, have great significance both theoretically andpractically.
     First, this paper make summative analysis of current theories of risk preference,risk measure, portfolio management and asset pricing, based on which this paperanalysis the shortcomings and insufficiency of the former theories. Then this paperput forward an improved generalized disappointment model, in the improved modeloriginal subject's target return reference point is changed from fixed expectedreturn to a generalized reference point, which is more flexible. In the meantimeimproved generalized disappointment model adopts linear piecewise utility functioninstead of traditional utility function, which makes the improved generalizeddisappointment model reflecting multiple risk feeling of investors.
     Second, based on the improved generalized disappointment model, this paperintroduces two kind of new portfolio models. One kind of the portfolio models setthe improved generalized disappointment model as target function, and can reflectinvestors' multiple risk attitude more comprehensively with more satifying portolio plan. The other kind of the portfolio models set improved generalizeddisappointment model as constraint which controls the skewness of portfolio return.Compared with current skewness controlling method in portfolio model, the methodadopt in this paper can offer more chances to get excess return with the sameinvestment target satisficed.
     Third, this paper deduces new asset pricing model with the portfolio modelbased on improved generalized disappointment model. Also this paper deduces anew pricing model with multiple reference points and analyzes the modelempirically. In the empirical research this paper focuses on the time varyingcharacteristics of beta in asset pricing model in order to analyze different assetpricing factors' time varying feature with multiple risk preference.
     Finally, this paper expands the asset pricing model based on improvedgeneralized diasppointment model. The expanded asset pricing model containsmore asset pricing factors. Also this paper introduce liquidity risk pricing factors into the expanded pricing model and analyzes the new pricing model empirically. Andthe liquidity risk pricing factors' time varying characteristics is analyzes, the resultsshows that the related improvement of asset pricing model in this paper is relevantand feasible.
引文
1Markowitz H M. Portfolio Selection[J]. Journal of Finance,1952,7(1):77-79.
    2Boyle P, Ding B. Numerical Methods in Finance, Chapter11: Portfolioselection with skewness. US: Springer,2006.
    3Fama E F, French K R. The Cross-Section Of Expected Stock Returns[J]. TheJournal of Finance,1992,2(47):427-465.
    4Jia J M, Dyer J S, Bulter J C. Generlized disappointment Models[J].Jounal ofrisk and uncertainty,2001,22(1):59-78.
    5Fielding D, Stracca L. Myopic loss aversion, aversion and the equitypremium[R], worlaing paper, European Central Bank,2003.
    6Markowitz H M. Portfolio Selection[J]. Journal of Finance,1952,7(1):77-79.
    7Konno H, Yamazaki H. Mean-Absolute Deviation Portfolio OptimizationModel And Its Application To Tokyo Stock Market[J]. Management Science,1991,(37):519-531.
    8Roy A D. Safety First And The Holding Of Assets[J]. Econometrica,1952,20(3):431-449.
    9Markowitz H M. Portfolio Selection: Efficient Diversification of Investments[M]. New York: Wiley,1959:89-102.
    10Bawa V S. Optimal Rules for Ordering Uncertain Prospects[J]. Journal OfFinancial Economics,1975,2(1):95-121.
    11Unser M. Lower Partial Moments As Measures Of Perceived Risk: AnExperimental Study[J]. Journal Of Economic Psychology,2000,21:253-280.
    12Ebert U. Measures Of Downside Risk[J]. Economics Bulletin,2005,4:1-9.
    13Morgan J P. Risk Metrics-Technical Document[R]. U.S.: J.P. Morgan Inc.,1994:32-56
    14Venkataraman S. Value At Risk For A Mixture Of Normal Distribution: TheUse Of Quasi-Bayesian Estimation Techniques[J]. Economic Perspectives(Federal Reserve Bank Of Chicago),1997,4:24-31.
    15Bulter J S, Schachter B. Estimating Value At Risk With A Precision MeasureBy Combining Kernel Estimation With Historical Simulation[J]. Review OfDerivatives Research,1998,1:371-390.
    16Danielsson J, Casper G, Vries D. Tail Index And Quantile Estimation WithVery High Finance Data[J]. Journal Of Empirical Finance,1997,4:241-257.
    17Fmhrechts P, Sidney R, Gennady S. Extreme Value Theory As A RiskManagement Tool[J]. North American Actuarial Journal,1999,3(1):30-41.
    18Frank I, David S. Translating Var Using Square Root Of T[J]. DerivativesWeek,1996,8(10):25-33.
    19Jamshidian F, Zhu Y. Scenario Simulation Model For Risk Management[J].Capital Market Strategy,1996,12:17-21.
    20Kupiec P. Techniques For Verifying The Accuracy Risk Of MeasurementModels[J]. Journal Of Derivatives,1995,3:86-99.
    21Pritsker M. Evaluating Value At Risk Methodologies: Accuracy VersusComputational Time[J]. Journal Of Financial Services Research,1996,12:44-73.
    22Fama E F, French K R. Common Risk Factors In The Returns On Stocks AndBonds[J]. Journal Of Financial Economics,1993,1(33):3-56.
    23Hendricks D, Beverly H. Bank Capital Requirements For Market Risk: TheInternal Models Approach[J]. Federal Reserve Rank Of New York EconomicPolicy Review,1997,3(12):58-83.
    24Consigli G. Tail Estimation And Mean-Var Portfolio Selection In MarketSubject To Financial Instability[J]. Journal Of Banking&Finance,2002,26:1355-1382.
    25Cherny A S. Weighted VaR And Its Properties[J]. Finance Stoch,2006,10:367-393.
    26Yamai Y, Yoshiba T. Value-At-Risk Versus Expected Shortfall: A PracticalPerspective[J]. Journal Of Banking&Finance,2005,4(29):997-1015.
    27Acerbi C, Tasche D. On The Coherence Of Expected Shortfall[J]. Journal OfBanking&Finance,2002,26(7):1487-1503.
    28Grechuk B, Molyboha A, Zabarankin M. Chebyshev’S Inequalities With LawInvariant Deviation Measures, Engineering And Informational Sciences,2010,24:145-170.
    29Coombs C, Bowen J. A Test Of Ve-Theories Of Risk And The Effect Of TheCentral Limit Theorem[J]. Acta Psychologica,1971,35:15-28.
    30Jia J, Dyer J S. Standard Measure Of Risk And Risk-Value Models[J].Management Science,1996,(42):1691-1705.
    31Balzer L. Managing Downside Risk In Financial Markets: Theory, PracticeAnd Implementation[M]. Oxford: Butterworth-Heinemann,2001:103-105.
    32Farinelli S, Rossello D, Tibiletti L. Computational Asset Allocation UsingOne-Sided And Two-Sided Variability Measures[J]. Lecture Notes InComputer Science,2006,3994:324-331.
    33Thierry P, Pim V V. Downside risk and asset pricing[J]. Journal of Banking&Finance.2006,6(30):823-849.
    34Imre K, Szilard P, Gabor N. Noise sensitivity of portfolio selection undervarious risk measures[J]. Journal of Banking&Finance,2007,5(31):1545-1573.
    35Calafore G C. Ambiguous risk measures and optimal robust portfolios[J].SIAM Journal on Optimization,2007,18(3):853-877.
    36Daniel R S. Conditional coskewness and asset pricing[J]. Journal of EmpiricalFinance.2007,4(14):91-119.
    37Rachev R, Ortobelli S, Stoyanov S, Fabozzi F, Biglova A. Desirable PropertiesOf An Ideal Risk Measure In Portfolio Theory[J]. International Journal OfTheoretical And Applied Finance,2008,1(11):19-54.
    38Ekaterina N S, Efim M B, Svetozar T R, Frank J F, Wei S, Stoyan V S.Handbook Of Portfolio Construction2010[M]. U.S.: Springer,2010:649-673.
    39Naomi M, Andrzej. Risk-adjusted probability measures in portfoliooptimization with coherent measures of risk[J]. European Journal ofOperational Research,2008,6(191):193-206.
    40Alejandro B, Raquel B, José G. Extending pricing rules with general riskfunctions[J]. European Journal of Operational Research,2010,2(201):23-33.
    41Zinoviy L. On the Tail Mean-Variance optimal portfolio selection[J]. Insurance:Mathematics and Economics,2010,2(46):547-553.
    42Mao J C T. Models of capital budgeting, E-V versus E-S [J]. Journal ofFinancial and Quantitative Analysis,1970,5:657-675.
    43Hogan W W, Warren J M. Computation of The Efficient Boundary in The E-SPortfolio Selection Model [J]. Journal of Financial Quantitative Analysis.1972,8:1881-1896.
    44Bawa, Vijay S, Eric B. Lindenberg. Capital Market Equilibrium in aMean-Lower Partial Moment Framework [J]. Journal of Financial Economics,1977,5:189-200
    45Nantell T J, Price B. An Analytical Comparison of Variance and SemivarianceCapital Market Theories [J]. Journal of Financial and Quantitative Analysis.1979,14,221-242.
    46Harlow W V, Rao R K S. Asset Pricing In A Generalized Mean-Lower PartialMoment Framework: Theory And Evidence[J]. Journal Of Financial AndQuantitative Analysis,1989,24:285-312.
    47Harlow W V. Asset Allocation In A Downside-Risk Framework[J]. FinancialAnalysts Journal,1991,47:28-40.
    48Lee Y F, Kuo Y M, Bollinger E K. Effects of feeding heights and distancefrom protective cover on the foraging behavior of wintering birds. CanadianJournal of Zoolog [J].2005,83:880-890
    49Jarrow R, Zhao F. Downside Loss Aversion And Portfolio Management[J].Management Science,2006,52:558-566.
    50Brennan M, Schwartz E. Portfolio insurance and financial market equilibrium[J]. Journal of Business,1989,16:403-426.
    51Cox J, Huang C. Optimum consumption and portfolio policies when assetprices follow a diffusion process [J]. Journal of Economic Theory,(1989),49:33-83.
    52Basak S. A General Equilibrium Model of Portfolio Insurance[J]. Rev.Financial Stud.1995,8:1059-1090.
    53Grossman S, Zhou Z. Equilibrium analysis of portfolio insurance[J]. Journal ofFinance,1996,11:1379-1403.
    54Nguyen P, Portait R. Dynamic asset allocation with mean variance preferenceand solvency constraint [J]. J. Econ. Dynamics Control,2002,26:11-3
    55Hansen L P, Jagannathan R.Implications of Security Market Data for Modelsof Dynamic Economies[J]. Journal of Political Economy,1991,99:225-262.
    56Deng, X.T. Li, Z.F., Wang, S.Y, A Minimax Portfolio Selection Strategy withEquilibrium [J].European Journal of Operational Research,2005,166:278-292.
    57Wu Z W, Song X F, Xu Y Y, Liu K. A note on a minimax rule for portfolioselection and equilibrium price system [J]. Applied Mathematics andComputation,2009,208(1):49-57.
    58Li, X., Zhou, X. Y Continuous-time mean-variance efficiency: The80%rule[J]. Annals of Applied Probability,2006,16:1751-1763.
    59Yan, J.A. Zhou, X.Y Markowitz strategies revised [J]. Acta MathematicaScientia,2009,29B(4):817-828.
    60Chen, P. Yang, H.L. Yin, G. Markowitz's mean-variance asset-liabilitymanagement with regime switching: A continuous-time model[J]. Mathematicsand Economics,2008,43:456-465.
    61吴祝武,朱开永,胡建华,许盈盈.证券数减少情形下M-V证券组合特征灵敏度研究[J].中国矿业大学学报,2006,35(3):122-128.
    62吴祝武,朱开永,许盈盈.证券数目变化时受到扰动的M-V有效前沿分析[J].运筹学学报,2007,11(2):122-128.
    63吴祝武,朱开永.证券数目变化时M-V有效前沿的旋移分析[[J].大学数学,2009,139(2):56-59.
    64Xie, S.X., Li, Z.F., Wang,.S.Y Continuous-time portfolio selection withliability: model and stochastic LQapproach [J]. Insurance: Mathematics andEconomic, Mean-variance,2008,42:943-953.
    65Ji, S.L., Peng, S.G. Terminal perturbation method for the backward approachto continuous time mean-variance portfolio selection [J]. Stochastic Processesand their Applications,2008(118):952-967.
    66Krokhmal P, Soberanis P. Risk Optimization With P-Order Conic Constraints:A Linear Programming Approach[J]. European Journal Of OperationalResearch,2010,4(201):653-671.
    67Markowitz H M. Portfolio Selection[J]. Journal of Finance,1952,7(1):77-79.
    68Cochrane, J. H. Asset Pricing. Princeton University Press[M].2001.
    69Rennart, M. J. Taxes, Market Valuation and Corporate Financial Policy[J].National Tax Journal,1970,23:417-427. Rennart, M. J. Taxes, MarketValuation and Corporate Financial Policy[J]. National Tax Journal,1970,23:417-427.
    70Brennan,M. J. Capital Market Equilibrium With Divergent Borrowing andLending Rates[J]. Journal ofFinancial and Quantitative Analysis,1971,6:1197-1205.
    71Black, E Capital Market Equilibrium with Restricted Borrowing[J]. Journal ofBusiness,1972,45:444-456.
    72Levy, H. Equilibrium in an Imperfect Market: AConstraint on the Number ofSecurities in the Portfolio[J]. American Economic Review,1978,68:643-658.
    73Sharp, W. E Capital Asset Prices with andwithout Negative Holdings[J].Journal of Finance,1991,46:489-509.
    74Harvey,C., and G Zhou. International Asset Pricing with AlternativeDistribution Assumptions[J]. Journal ofEmpirical Finance,1993,1:107-131.
    75Bollerslev,T., R. E Engle, and J. M. Wooldridge. A Capital Asset PricingModel with Time-Varying Covariances[J]. The Journal of PoliticalEconomy,1988,96:116-150.
    76Jagannathan, R., and Z. Wang. The Conditional CAPM and the Cross-sectionof Expected Returns[J]. Journal of Finance,1996,51:3-53.
    77Ross, S. A. The Arbitrage Pricing Theory of Capital Asset Pricing[J]. Journalof Economic Theory,1976,13:341-360.
    78Fama, E. E, and K. R. French. Multifactor Explanations of Asset PricingAnomalies[J]. Journal of Finance,1996,51:55-84.
    79Merton, R. C. An Intertemporal Capital Asset Pricing Model[J]. Econometrics1973,41:867-887.
    80kunev, J. An Alternative Measure of Mutual Fund Performance[J]. Journal ofBusiness Finance&Accounting,1990,17:247-264.
    81Price, K., B. Price, and T. J. Nantell. Varianceand Lower Partial MomentMeasures of Systematic Risk: Some Analytical and Empirical Results[J].Journal of Finance,1982,37:843-855.
    82Bansal R, Hsieh D A, Viswanathan S. A New Approach to InternationalArbitrage Pricing[J]. Journal ofFinance,1993,48:1719-1747.
    83Bansal R, Viswanathan S. No Arbitrage and Arbitrage Pricing[J]. Journal ofFinance,1993,48:1231-1262.
    84Chapman D A. Approximating The Asset Pricing Kernel[J]. Journal of Finance,1997,52:1383-1410.
    85Kraus A, LitzenbergerR H. Skewness Preference and the Valuation of RiskAssets[J]. Journal ofFinance,1976,31:1085-1100.
    86Friend I, Westerfield R. Co-skewness and Capital Asset Pricing[J]. Journal ofFinance,1980,35:897-913.
    87Kimball M S. Precautionary Saving in The Large and in The Small[J].Econometrica,1990,58:53-73.
    88Acharya V V, Pedersen L H. Asset Pricing With Liquidity Risk[J]. Journal OfFinancial Economics,2005,77(2):375-410.
    89姚京,袁子甲,李仲飞.基于相对var的资产配置和资本资产定价模型[J].数量经济技术经济研究,2005,12:133-142.
    90姚京,袁子甲,李仲飞,李瑞. Var风险度量下的系数:估计方法和实证研究[J].系统工程理论与实践,2009,7:27-29.
    91Walter R. Principles of Mathematical Analysis[M]. US: McGraw-Hill,2008.
    92Kimball M S. Standard Risk Aversion[J]. Econometrica,1993,61:589-611.
    93黄峰,杨朝军.流动性风险与股票定价:来自我国股市的经验证据[J].管理世界,2007,5:30-39.
    94Alexander GordonJ, Chervany N L. On the estimation and stability ofbeta[J].Journal of Financial and Quantitative Analys,1980,15(1):123-128.
    95Hrvey C A, Siddique. Autoregressive Conditional Skewness[J]. Journal ofFinancial and Quantitative Analysis,1999,34:465-487.
    96Jurczenko E, Mmllet B. The3-CAPM: Theoretical Foundations and An AssetPricing Model Comparison in a Unified Framework[J]. Developments inForecast Combination and Portfolio Choice, John Wiley&Sons,2001,239-1273.
    97Chabi Y F, Leisen D, Renau R. Implications of Asymmetry Risk for PortfolioAnalysis and Asset Pricing[R]. Discussion paper, UNC,2006,1-34.
    98Vanden J M. Option Coskewness and Capital Asset Pricing[J]. Review ofFinancial Studies,2006,19:1279-1320.
    99Blume M E, Betas and their regression tendeneies: some further evidence[J].Journalof Finanee,1979,34(1):265-267.
    100Longstaff F A. How Much Can Marketability Affect Security Values? TheJournal of Finance,1995,(5):1767-1774.
    101Roll R. A Simple Implicit Measure of the Effective Bid-Ask Spread in anEfficient Market[J]. Journal of Finance,1984,(39):1127-1139.
    102Hasbrouck J. Measuring the information content of stock trades[J]. Journal ofFinance,1991,(46):179-207.
    103Javier E. Mean-semivariance behavior: Downside risk and capital assetpricing[J]. International Review of Economics and Finance,2007,3(16):169-185.
    104王燕鸣,王宜峰.投资机会变动与风险收益关系实证研究[J].管理科学,2012,8:100-110.
    105Smith, D R. Conditional Coskewness and Asset Pricing[J]. Journal ofEmpirical Finance,2007,14:91-119.
    106Chen, L D, Lesmond, Wei J. Corporate Yield Spreads and Bond Liquidity[J].Journal of Finance,2007,4(23):56-75.
    107Covitz D, Downing C. Liquidity or Credit Risk? The De terminants of VeryShort-Term Corporate Yield Spreads[J]. Journal of Finance,2007(5):24-37.
    108王金安,陈浪南.考虑流动性的三阶矩资本资产定价的理论模型与实证研究[J].会计研究,2008,8:50-58.
    109蒋玉梅,王明照.投资者情绪与股票收益:总体效应与横截面效应的实证研究[J].南开管理评论.2010,(3):150-160.
    110曹崇延,姜丹君,瞿安民.基于行业考虑的β和B/M与股票收益率关系研究[J].电子科技大学学报.2012,(6):54-59.
    111Acharya V, Amihud, Bharath S. Liquidity Risk of Corporate Bond Returns [R].NBER Working Paper,2010:1-25.
    112Lin H, J. Wang, Wu C. Liquidity risk and the cross-section of expectedcorporate bond return[sJ]. Journal of Financial Economics,2010,3(4):56-87.
    113Boyle P, Ding B. Numerical Methods in Finance, Chapter11: Portfolioselection with skewness. US: Springer,2006.

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