中文版 | English
Title

基于时变隐马尔可夫机制转换模型的多资产配置研究

Alternative Title
RESEARCH ON MULTI-ASSET ALLOCATIONBASED ON TIME-VARYING HIDDEN MARKOVREGIME SWITCHING MODEL
Author
Name pinyin
HU Jiaqi
School number
12032832
Degree
硕士
Discipline
0701 数学
Subject category of dissertation
07 理学
Supervisor
周倜
Mentor unit
金融系
Publication Years
2022-05-07
Submission date
2022-06-29
University
南方科技大学
Place of Publication
深圳
Abstract

股票收益率预测和基于此的资产配置一直是金融研究的核心问题。过去许多 文献提出的方法在样本内有效,但在样本外往往表现不佳,甚至不如历史平均值 的预测表现。这是由金融市场状态变化引发的模型不确定、参数不稳定问题导致 的。金融市场不同状态之间的转换是突然的,但转换后的状态又具有持续性,这些 线性模型难以刻画的特征却可以被隐马尔可夫模型描述。本文在时变隐马尔可夫 机制转换模型的基础上加入经济变量,构成单因子和双因子预测模型,对美国市 场上的行业股票组合超额收益率进行样本外预测,并参考了组合预测的方法,结 合了各个预测因子的信息。基于隐马尔可夫机制转换模型的组合预测在日常消费 品、日常服务和其他行业 (诸如,矿业、娱乐、金融等) 股票组合上有很好的预测 表现,样本外𝑅 2显著为正。单因子和双因子时变模型在多数行业上的预测能力都 显著超越了历史平均值的预测。资产配置结果表明,基于隐马尔可夫机制转换模 型的组合配置有良好的表现,在样本外夏普率和确定性等价收益率上超过了基于 历史均值预测的 Markowitz 方法、普通单因子预测的组合配置。其中,双因子时变 模型得到的结果表现最佳,甚至在确定性等价收益率这一指标上显著优于1/N策 略。资产收益率和经济变量之间的关系会随经济周期发生变化。隐马尔可夫机制 转换模型可以识别经济周期的变化,从而可以更稳定地预测资产收益率,进而更 有效地进行资产配置。

Keywords
Language
Chinese
Training classes
独立培养
Enrollment Year
2020
Year of Degree Awarded
2022-07
References List

[1] CAMPBELL J, SHILLER R. The Dividend-Price Ratio and Expectation of Future Dividends and Discount Factors[J]. Review of Financial Studies, 1988, 1: 195-228.
[2] FISHER K, STATMAN M. Investor Sentiment and Stock Returns[J]. Financial Analysts Journal, 2000, 56: 16-23.
[3] HOMA K, JAFFEE D. The Supply of Money and Common Stock Prices[J]. Journal of Finance, 1971, 26: 1045-66.
[4] KUTTNER K, MOSSER P. The Monetary Transmission Mechanism: Some Answers and Further Questions[J]. Economic Policy Review, 2002, 8: 15-26.
[5] JANSEN D, TSAI C L. Monetary Policy and Stock Returns: Financing Constraints and Asymmetries in Bull and Bear Markets[J]. Journal of Empirical Finance, 2010, 17: 981-990.
[6] HSU K C, CHIANG H C. Nonlinear Effects of Monetary Policy on Stock Returns in a Smooth Transition Autoregressive Model[J]. The Quarterly Review of Economics and Finance, 2011, 51: 339-349.
[7] CHEN M H. Asymmetric Response of Hospitality Stock Prices to Fed Policy Actions[J]. International Journal of Hospitality Management, 2013, 33: 129–139.
[8] LIU H, MANZOOR A, WANG C, et al. The COVID-19 Outbreak and Affected Countries Stock Markets Response[J]. International Journal of Environmental Research and Public Health, 2020, 17: 2800.
[9] CULTER D, POTERBA J, SUMMERS L. Speculative Dynamics and the Role of Feedback Traders[J]. American Economic Review, 1990, 80: 63-68.
[10] DELONG J, SHLEIFER A, SUMMERS L, et al. Noise Trader Risk in Financial Markets[J]. Journal of Political Economy, 1990, 98: 703-738.
[11] 任泽平, 陈昌盛. 经济周期波动与行业景气变动: 因果联系、传导机制与政策含义[J]. 经 济学动态, 2012(1): 19-27.
[12] 尚煜, 许文浩. 基于经济周期的股票市场行业资产配置研究[J]. 经济问题, 2020(3): 25-34.
[13] COCHRANE J. Presidential Address: Discount Rates[J]. Journal of Finance, 2011, 66: 1047- 1108.
[14] MARKOWITZ H M. Portfolio Selection[J]. The Journal of Finance, 1952, 7: 77-91.
[15] BARRY C. Portfolio Analysis under Uncertain Means, Variances, and Covariances[J]. Journal of Finance, 1974, 29: 515-22.
[16] BAWA V S, BROWN S J, KLEIN R W. Estimation Risk and Optimal Portfolio Choice[J]. Journal of Finance, 1979, 36: 89-111.
[17] JOBSON D, KORKIE B, RATTI V. Improved Estimation for Markowitz Portfolios Using James-Stein Type Estimators[J]. Proceedings of the American Statistical Association, 1979, 41: 279-92.
[18] JOBSON D, KORKIE R B. Estimation of Markowitz Efficient Portfolios[J]. Journal of the American Statistical Association, 1980, 75: 544-54.
[19] JORION P. International Portfolio Diversification with Estimation Risk[J]. The Journal of Business, 1985, 58: 259-78.
[20] JORION P. Bayes-Stein Estimation For Portfolio Analysis[J]. Journal of Financial and Quantitative Analysis, 1986, 21: 279-292.
[21] PáSTOR L. Portfolio Selection and Asset Pricing Model[J]. The Journal of Finance, 2000, 55: 179 - 223.
[22] PáSTOR L, STAMBAUGH R. Comparing Asset Pricing Models: An Investment Perspective [J]. Journal of Financial Economics, 2000, 56: 335-381.
[23] ROZEFF M. Dividend Yields Are Equity Risk Premiums[J]. Journal of Portfolio Management, 1984, 11: 68-75.
[24] FAMA E, FRENCH K. Dividend Yields and Expected Stock Return[J]. Journal of Financial Economics, 1988, 22: 3–25.
[25] FAMA E, FRENCH K. Business Conditions and Expected Returns on Stock and Bonds[J]. Journal of Financial Economics, 1989, 25: 23-49.
[26] WELCH I, GOYAL A. A Comprehensive Look at the Empirical Performance of Equity Premium Prediction[J]. Review of Financial Studies, 2008, 21: 1455-1508.
[27] BOSSAERTS P, HILLION P. Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?[J]. Review of Financial Studies, 1999, 12: 405-28.
[28] LETTAU M, NIEUWERBURGH S. Reconciling the Return Predictability Evidence[J]. Review of Financial Studies, 2008, 21: 1607-1652.
[29] MAHEU J, MCCURDY T. How Useful Are Historical Data for Forecasting the Long-Run Equity Return Distribution?[J]. Journal of Business and Economic Statistics, 2009, 27: 95-112.
[30] CAMPBELL J, THOMPSON S. Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?[J]. Review of Financial Studies, 2008, 21: 1509-1531.
[31] LUDVIGSON S, NG S. The Empirical Risk-Return Relation: A Factor Analysis Approach[J]. Journal of Financial Economics, 2007, 83: 171-222.
[32] STOCK J, WATSON M. Combination Forecasts of Output Growth in a Seven-Country Data Set[J]. Journal of Forecasting, 2004, 23: 405-430.
[33] RAPACH D, STRAUSS J, ZHOU G. Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy[J]. Review of Financial Studies, 2009, 23: 821-862.
[34] DANGL T, HALLING M. Predictive Regressions with Time-Varying Coefficients[J]. Journal of Financial Economics, 2012, 106: 157–181.
[35] GU S, KELLY B, XIU D. Empirical Asset Pricing via Machine Learning[J]. The Review of Financial Studies, 2020, 33: 2223-2273.
[36] HAMILTON J D. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle[J]. Econometrica, 1989, 57: 357-384.
[37] GOLDFELD S M, QUANDT R E. A Markov Model for Switching Regressions[J]. Journal of Econometrics, 1973, 1: 3-15.
[38] COSSLETT S R, LEE L F. Serial Correlation in Latent Discrete Variable Models[J]. Journal of Econometrics, 1985, 27: 79-97.
[39] SIMS C, ZHA T. Were there Regime Switches in U.S. Monetary Policy?[J]. American Economic Review, 2006, 96: 54-81.
[40] SOSSOUNOV K, PAGAN A. A Simple Framework for Analyzing Bull and Bear Markets[J]. Journal of Applied Econometrics, 2003, 18: 23-46.
[41] CAMPBELL J, LO A, MACKINLAY A. The Econometrics of Financial Markets[M]. Princeton University Press: Princeton, NJ, 1997.
[42] TIMMERMANN A. Moments of Markov Switching Models[J]. Journal of Econometrics, 2000, 96: 75-111.
[43] LONGIN F, SOLNIK B. Extreme Value Correlation of International Equity Markets[J]. The Journal of Finance, 2001, 56: 649 - 676.
[44] ANG A, CHEN J. Asymmetric Correlations of Equity Portfolios[J]. Journal of Financial Economics, 2001, 63: 443-494.
[45] HENKEL S, MARTIN J, NARDARI F. Time-Varying Short-Horizon Return Predictability[J]. Journal of Financial Economics, 2011, 99: 560-580.
[46] TIMMERMANN A, PEREZ-QUIROS G. Firm Size and Cyclical Variations in Stock Returns [J]. The Journal of Finance, 2000, 55: 1229–62.
[47] GUIDOLIN M, TIMMERMANN A. Size and Value Anomalies under Regime Shifts[J]. Journal of Financial Econometrics, 2007, 6: 1-48.
[48] ZHU X, ZHU J. Predicting Stock Returns: A Regime-Switching Combination Approach and Economic Links[J]. Journal of Banking and Finance, 2013, 37: 4120-4133.
[49] ZAGST R, HAUPTMANN J, HOPPENKAMPS A, et al. Forecasting market turbulence using regime-switching models[J]. Financial Markets and Portfolio Management, 2014, 28: 139-164.
[50] FINK H, KLIMOVA Y, CZADO C, et al. Regime Switching Vine Copula Models for Global Equity and Volatility Indices[J]. Econometrics, 2017, 5: 1-38.
[51] ZHENG K, LI Y, XU W. Regime switching model estimation: spectral clustering hidden Markov model[J]. Annals of Operations Research, 2019, 303: 297-319.
[52] BEKAERT G, ANG A. International Asset Allocation with Regime Shifts[J]. Review of Financial Studies, 2002, 15: 1137-1187.
[53] ANG A, BEKAERT G. How Do Regimes Affect Asset Allocation[J]. Financial Analysts Journal, 2004, 60: 86-99.
[54] TU J. Is Regime Switching in Stock Returns Important in Portfolio Decisions?[J]. Management Science, 2010, 56: 1198-1215.
[55] DEMIGUEL V, GARLAPPI L, UPPAL R. Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?[J]. Review of Financial Studies, 2009, 22: 1915–1953.
[56] 易纲, 王召. 货币政策与金融资产价格[J]. 经济研究, 2002(3): 13-20.
[57] 王晓明. 银行信贷与资产价格的顺周期关系研究[J]. 金融研究, 2010(3): 45-55.
[58] 郑方镳, 吴超鹏, 吴世农. 股票成交量与收益率序列相关性研究——来自中国股市的实证 证据[J]. 金融研究, 2007(3): 140-150.
[59] 陈国进, 张贻军. 异质信念, 卖空限制与我国股市的暴跌现象研究[J]. 金融研究, 2009(4): 80-91.
[60] MILLER E. Risk, Uncertainty, and Divergence of Opinion[J]. Journal of Finance, 1977, 32: 1151-68.
[61] 姜富伟, 徐俊, RAPACH D E, 等. 中国股票市场可预测性的实证研究[J]. 金融研究, 2011 (9): 15.
[62] HONG H, TOROUS W, VALKANOV R. Do Industries Lead Stock Markets?[J]. Journal of Financial Economics, 2007, 83: 367-396.
[63] 魏巍贤, 陈智文, 王建军. 三状态马尔柯夫机制转换模型研究——在世界油价波动分析中的应用[J]. 财经研究, 2006, 32(6): 120-131.
[64] 高金余, 陈翔. 马尔可夫切换模型及其在中国股市中的应用[J]. 中国管理科学, 2007, 15 (6): 33-38.
[65] 严太华, 陈明玉. 基于马尔科夫切换模型的上证指数周收益率时间序列分析[J]. 中国管理科学, 2009, 17(6): 33-38.
[66] 张冬青, 韩玉兵, 宁宣熙, 等. 基于小波域隐马尔可夫模型的时间序列分析-平滑, 插值和预测[J]. 中国管理科学, 2008, 16(2): 122-127.
[67] 吴吉林, 张二华. 次贷危机, 市场风险与股市间相依性[J]. 世界经济, 2010(3): 95-108.
[68] 姜婷, 周孝华, 董耀武. 基于 Markov 机制转换模型的我国股市周期波动状态研究[J]. 系统工程理论与实践, 2013, 33: 1934-1939.
[69] 张同斌, 高铁梅. 中国经济周期波动的阶段特征及驱动机制研究——基于时变概率马尔科夫区制转移 (MS-TVTP) 模型的实证分析[J]. 财贸经济, 2015(1): 27-39.
[70] 吴世农, 陈斌. 风险度量方法与金融资产配置模型的理论和实证研究[J]. 经济研究, 1999 (9): 30-38.
[71] 蒋晓全, 丁秀英. 我国证券投资基金资产配置效率研究[J]. 金融研究, 2007(2): 89-97.
[72] 李仲飞, 袁子甲. 参数不确定性下资产配置的动态均值-方差模型[J]. 管理科学学报, 2010, 13(12): 1-9.
[73] 张冀, 谢远涛, 杨娟. 风险依赖、一致性风险度量与投资组合——基于 Mean-Copula-CVaR的投资组合研究[J]. 金融研究, 2016(10): 159-173.
[74] 潘志远, 毛金龙, 周彬蕊. 高维的相关性建模及其在资产组合中的应用[J]. 金融研究, 2018 (2): 190-206.
[75] 周亮, 李红权. 基于马尔科夫区制转换及 Black-Litterman 模型的大类资产组合模型研究[J]. 数理统计与管理, 2020, 39: 617-632.
[76] 王犇. 隐马尔可夫模型、马尔可夫状态转换模型在量化投资中的应用[M]. 清华大学出版 社, 2017.
[77] DIEBOLD F, LEE J H, WEINBACH G. Regime Switching with Time-Varying Transition Probabilities. In Nonstationary Time Series Analysis and Cointegration[M]. Oxford University Press, 1994: 283-302. 67 参考文献
[78] PETERSEN K, PEDERSEN M. The Matrix Cookbook[M]. 2012.
[79] QU Z, ZHUO F. Likelihood Ratio-Based Tests for Markov Regime Switching[J]. The Review of Economic Studies, 2020, 88: 937-968.
[80] JAGANNATHAN R, MA T. Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraint Helps[J]. Journal of Finance, 2003, 58: 1651-1684.
[81] DOAN T, FILARDO A. Business-Cycle Phases and Their Transitional Dynamics[J]. Journal of Business and Economic Statistics, 1994, 12: 299-308.
[82] GRAY S. Modelling the Conditional Distribution of Interest Rates as A Regime-Switching Process[J]. Journal of Financial Economics, 1996, 42: 27-62.
[83] HAMILTON J. Analysis of Time Series Subject to Change[J]. Journal of Econometrics, 1990, 45: 39-70.
[84] ALBERT J, CHIB S. Bayes Inference Via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts[J]. Journal of Business and Economic Statistics, 1993, 11: 1-15.
[85] KIM C J, NELSON C. State-Space Models with Regime Switching: Classical and Gibbs Sampling Approaches with Applications[M]. The MIT Press, 2017.
[86] KIM C J. Dynamic Linear Model with Markov Switching[J]. Journal of Econometrics, 1991, 60: 1-22.
[87] KIM C J, NELSON C. Business Cycle Turning Points, A New Coincident Index, and Tests of Duration Dependence Based on A Dynamic Factor Model with Regime Switching[J]. The Review of Economics and Statistics, 1998, 80: 188-201.
[88] CLARK T, WEST K. Approximately Normal Tests for Equal Predictive Accuracy in Nested Models[J]. Journal of Econometrics, 2007, 138: 291-311.
[89] DIEBOLD F, MARIANO R. Comparing Predictive Accuracy[J]. Journal of Business and Economic Statistics, 1995, 13: 253-63.
[90] WEST K. Asymptotic Inference about Predictive Ability[J]. Econometrica, 1996, 64: 1067-84.
[91] WEST K, NEWEY W. A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix[J]. Econometrica, 1987, 55: 703-08.
[92] HUANG D, JIANG F, TU J, et al. Investor Sentiment Aligned: A Powerful Predictor of Stock Returns[J]. The Review of Financial Studies, 2014, 28: 791-837.
[93] MEMMEL C. Performance Hypothesis Testing with the Sharpe Ratio[J]. Finance Letters, 2003, 1: 21-23.
[94] JOBSON D, KORKIE R B. Performance Hypothesis Testing with the Sharpe and Treynor Measures[J]. Journal of Finance, 1981, 36: 889-908.
[95] GOETZMANN W, INGERSOLL J, SPIEGEL M, et al. Portfolio Performance Manipulation and Manipulation-Proof Performance Measures[J]. Review of Financial Studies, 2007, 20: 1503-1546.
[96] FAMA E. Two Pillars of Asset Pricing[J]. The American Economic Review, 2014, 104: 1467– 1485. 68 参考文献
[97] RAPACH D, RINGGENBERG M, ZHOU G. Short Interest and Aggregate Stock Returns[J]. Journal of Financial Economics, 2016, 121: 46-65.
[98] MELE A. Asymmetric Stock Market Volatility and the Cyclical Behavior of Expected Returns [J]. Journal of Financial Economics, 2007, 86: 446-478.
[99] CAMPBELL J. A Variance Decomposition Model for Stock Returns[J]. Economic Journal, 1991, 101: 157-79.
[100] CUJEAN J, HASLER M. Why Does Return Predictability Concentrate in Bad Times?[J]. The Journal of Finance, 2017, 72: 2717-2757.
[101] MERTON R C. An Intertemporal Capital Asset Pricing Model[J]. Econometrica, 1973, 41: 867-887.
[102] GUO H, WHITELAW R. Uncovering the Risk-Return Relation in the Stock Market[J]. The Journal of Finance, 2006, 61: 1433-1463.
[103] FAMA E, SCHWERT G, Willian. Asset Returns and Inflation[J]. Journal of Financial Eco nomics, 1977, 5: 115-146.
[104] LI E X, ZHA T, ZHANG J, et al. Does Fiscal Policy Matter for Stock-Bond Return Correlation? [J]. Journal of Monetary Economics, 2022.
[105] 张春玲, 姜富伟, 唐国豪. 资本市场收益可预测性研究进展[J]. 经济学动态, 2019(2): 133- 148.
[106] ANG A, TIMMERMANN A. Regime Changes and Financial Markets[J]. Annual Review of Financial Economics, 2012, 4: 313-337

Academic Degree Assessment Sub committee
金融系
Domestic book classification number
F830.91
Data Source
人工提交
Document TypeThesis
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/343170
DepartmentDepartment of Finance
Recommended Citation
GB/T 7714
胡家啟. 基于时变隐马尔可夫机制转换模型的多资产配置研究[D]. 深圳. 南方科技大学,2022.
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