股票市场与国际商品市场联动性实证研究
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摘要
随着金融自由化、全球化,商品市场与股票市场之间、国内股市与外围市场之间的信息传递与联动机制均随之增强。2008年全球金融危机的爆发,一方面促使世界金融体系出现一定程度调整,另一方面对投资者预期和交易策略产生深刻影响,从而使得危机期间以及危机后时代全球不同资本市场的联系可能发生结构性变化。与此同时,在经历数次大规模的金融市场动荡后,风险分散和资产多样化需求的日益旺盛使得不同资本市场之间的相关性成为人们关注焦点。本文旨在分析国际商品市场与国内外股票市场的互动机制和相关关系的动态变化特征,具有重要理论和现实意义。
     本文首先分析了股票市场与商品市场的理论联动机理,说明在有效市场条件下两类市场存在确定性的信息传递机制,而现实市场的不完善导致市场联动的不确定性与时变特征。此外商品市场的金融属性导致使得商品成为股票的投资替代品,资金的跨市流转对两类市场联动性可能产生影响。
     为量化联动机制及刻画动态特征,本文结合VAR、diag-TGARCH、AG-DCC模型对国际商品市场和国内外股票市场联系进行了系统性实证分析。文中选择中国、香港、美国三地股市,国际石油、金属、黄金市场三类商品市场及其标价货币美元的总共7类代表性指数作为样本,首先使用VAR模型考察不同市场的均值溢出效应,使用diag-TGARCH模型考察各市场波动的不对称效应。在此基础上运用AG-DCC模型得到各市场动态相关性的估计方程,以考察相关性的不对称特征和时变特征,并分析金融危机前后市场间相关性是否发生结构变化。
     均值溢出效应的实证结果表明:香港股市是内地股市影响外围股市的重要桥梁;美国和香港股市能对部分国际商品市场提供较好的价格预测功能,而我国内地股市的预测功能相对较差;国际商品市场对美股和港股存在一定价格预测功能,但对我国内地股市的引导作用较弱。
     动态相关性的实证结果表明:金融危机爆发促使我国股市与外围股市联动性迅速上升;香港、美国股市与美元在金融危机爆发后出现较明显的负相关性,而内地股市与美元的相关性长期均较微弱;三地股市与黄金的相关性在金融危机后迅速下降,与石油的相关性在金融危机后经济复苏初期开始迅速上升,而与铜的相关性长期比较微弱;美国、香港、内地股市与各国际商品市场的相关性整体水平依次降低。这些结论说明金融危机的爆发对于商品市场与股票市场联动性产生了结构性影响;三地股市与国际商品市场相关性的整体趋势类似,但存在明显的深度和广度的区别。
With the trends of financial liberalization and financial globalization, information transmission and interaction mechanim between commodity markets and stock markets, and between domestic stock market and foreign markets might be further strengthened. 2008 global financial crisis caused financial system have some adjustment, and changed the investers’expectations and trading strategies, so the linkages of global capital markets between in-crisis era and post-crisis era might have some structural changes. At the same time, after several large-scale finance crises, the correlations among different capital markets became the focus of attention, because of the demands of risk prevention and asset diversification. This thesis tends to analyze dynamic characteristics of interaction mechanim and correlations among international commodity markets and domestic、foreign stock markets, which has important theoretical and practical significance.
     This thesis first analyzed theoretical mechanism of linkages between stock markets and commodity markets. In the condition of EMH, information transmission mechanism between the two markets is determined. But real markets are imperfect, which cause the linkage mechanism uncertainty and dynamic. Commodity became stock’s alternative investment because of its financial properties, and capital cross-market flow may have influence to the linkage mechanism of the two markets.
     To quantify the linkage mechanism and depict these characteristics, this thesis combine VAR, diag-TGARCH, AG-DCC model to make systematic empirical analyses on international commodity markets and domestic、foreign stock markets. We selected representative indices of China、Hong Kong、the U.S. stock markets, international oil、metal、gold markets and the dollar market as samples. First we used VAR model to analyze mean spillover effects in different markets, then we used diag-TGARCH model to analyze the market asymmetric volatility effect. Based on the results we used AG-DCC model to estimate equations of dynamic correlations among different markets, in order to study the asymmetry and time-varying characteristics, and test the structural change of correlations before and after the 2008 financial crisis.
     Empirical results of mean spillover effects show that: Hong Kong stock market is an important bridge of China stock market to affect foreign stock markets; Hong Kong and the U.S. stock markets have better price forecast function to some international commodity markets than China stock market; International commodity markets have price farecast function to Hong Kong and the U.S. stock markets, but don’t have much influence on China stock market.
     Empirical results of dynamic correlations show that: the correlaion between China stock market and foreign stock markets is higher after the financal crisis; Hong Kong and the U.S. stock markets have Significant negative correlations with the the U.S. dollar, but the correlation between China stock market and the U.S. dollar is weak in long run; the correlation between the U.S.、Hong Kong、China stock markets and gold is lower after the financal crisis, the correlation between the three stock markets and oil is higher after the financal crisis, the correlation between the three stock markets and copper is weak in long term; the correlation between the U.S.、Hong Kong、China stock markets and international commodity markets successive decrease. These results demonstrate that 2008 financial crisis certainly have structural effects on the linkage between commodity markets and stock markets; correlations between three stock markets and commodity markets have similar trends, but there are some distinction on depth and breadth of various countries’capital markets.
引文
[1]吉姆·罗杰斯.热门商品投资[M].北京:中信出版社,2005: 16-17.
    [2] Gary Gorton, K.Geert Rouwenhorst. Facts and fantasies about commodity futures[R].Yale ICF Working Paper. 2005,01: 04-20.
    [3] Chang Eric C, Cheng Joseph W, Pinegar J Michael. Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets[J]. Journal of Banking&Finance. 1999, (5): 727-753.
    [4] Van der Voet, Ester Kleijn, Rene Huele, Ruben Ishikawa, Masanobu Verkuijlen. Evert predicting future emissions based on characteristics of stocks[J]. Ecological Economics. 2002, (2): 223-35.
    [5] Gannon Gerard. Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets[J]. International Review of Financial Analysis. 2005, (3): 326-336.
    [6]寇玲.金融危机下国际金融市场间波动溢出效应研究——基于中英美的实证比较[D].大连理工大学硕士学位论文, 200912.
    [7]吴照银.全球股市、汇市、商品市场联动性研究[J].中国证券期货. 2009,1: 56-61.
    [8] Eun C, S. Shim. International transmission of stock market movement[J]. Journal of financial and quantitative analysis, 1989(24): 241-256.
    [9] Janakiramanan, S., and S.L.Asjeet. An empirical examination of linkages between Pacific—Basin Stock Markets.[J]. Journal of International Financial Markets. Institutions and Money, 1998, 8:155-173.
    [10] Gerrits, R.J. and Yuce.A Short and Long term Links among European and U.S. Stock markets[J]. Applied Financial Economics, 1999, 9:1-9.
    [11]张福,赵华,赵嫒嫒.中美股市协整关系的实证分析[J].财经论坛, 2004, 2: 32-41.
    [12]张碧琼.中国股票市场信息国际化:基于EGARCH模型的检验[J].国际金融研究, 2005, 5: 56-67.
    [13]崔准焕.中国股市与美国股市之间联动性研究[D],浙江大学博士学位论文,200708.
    [14]卓桂秋.中美股市联动性的实证研究[D],厦门大学硕士学位论文,2009.
    [15] Huang, Roger D., Ronald W. Masulis, and Hans R. Stoll, Energy Shocks andFinancial Markets[J], Journal of Futures Markets, 1996, 16:1-27.
    [16] Basher, Syed A., and Perry Sadorsky, Oil Price Risk and Emerging Stock Markets[J], Global Finance Journal, 2006, 17,224-251.
    [17]金洪飞,金荦.石油价格和股票市场的溢出效应[J].金融研究, 2008, 2: 83-97
    [18]金洪飞,金荦.国际石油价格对中国股票市场的影响——基于行业数据的经验分析[J].金融研究, 2010, 2: 173-187.
    [19]陈俊芳,刘凤元,王志明.铝业上市公司股票收益率模型及投资价值分析[J].技术经济与管理研究,2003, (6): 62-64.
    [20]戎燕.铝期货价格与锅业上市公司股价的内在关系研究[D].浙江工业大学硕士学位论文,2008,12,30-58.
    [21]徐东贤.有色金属期货价格走势规律及投资风险控制[D].河海大学商学院硕士学位论文,2007,64-68.
    [22]唐英,温涛.我国铜业上市公司股票价格与铜期货价格关系的实证研究[J].证券与保险,2008, (2):57-59.
    [23]胡恩同,黄金不同于其他资产的原因——一个实证分析[J].源复黄金研究, 2004, 6(14): 68-90.
    [24]胡恩同,黄金与股票收益的长期相关性分析——以美国与英国为例[J].黄金、外汇投资超宏观揭秘,人民出版社, 2006,8: 48-56.
    [25]胡恩同,黄金价格走势影响因素与分析方法[J].源复黄金研究, 2004, 10(18): 100-109.
    [26] Grubel. Internationally Diversified Portfolios : Welfare Gains and Capital Flows[J]. American Economic Review, 1968, 12: 1299-1314.
    [27] JF Jaffe. Gold and gold stocks as investments for institutional portfolios[J]. Financial Analysts Journal, 1989,2,(45): 53-59.
    [28] Robert Faff, Howard Chan. A multifactor model of gold industry stock returns: evidence from the Australian equity market[J]. Applied Financial Economics, 1998, 8,(1): 21-28.
    [29]沈家诤,肖春英,肖云辉.黄金与美元[J].黄金, 2005,9,(26):5-9.
    [30]陈旭敏.中国的“美元”命运[J].海外经济评论, 2007, 16: 15-16.
    [31]于军. A股的美元坐标.财经, 2010,2:7-7.
    [32] Bollerslev, Engle, and Wooldridge. A Capital Asset Pricing Model with Time Varying Covariances. Journal of Political Economy. 1988, 96, 116-131.
    [33] Engle R, Kroner K. Multivariate simultaneous GARCH[J]. Econometric Theory, 1995,1l:122-150.
    [34] Bollerslev, T. Modeling the Coherence in Short-run Nominal Exchange Rate:A Multivariate Generalized ARCH Model[J]. Review of Economics and Statistics, 1990,(72):498-505.
    [35] Engle, R.F. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroscedasticity Models[J]. Journal of Business and Economic statistics, 2002,(20):339-350.
    [36] Chiang, T.C., Jeon, B.N., Li. Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Markets[J]. Journal of International Money and Finance, 2007,(26):1206-1228.
    [37] Vargas, G.A. What Drives the Dynamic Conditional Correlation of Foreign Exchange and Equity Retums?[R]. Singapore Management University, Working Paper, 2008.
    [38] Billio, Caporin, Gobbo. Block Dynamic Conditional Correlation Multivariate GARCH Models[R]. Gruppi di Ricerca Economica Teorica e Applicata, Working Paper, 2003.
    [39] Cappiello L, Engle R, Sheppard K. Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns[J]. Journal of Financial Econometrics, 2006, (4): 537-572.
    [40] Stuart Hyde, Don Bredin, Nghia Nguyen. Correlation dynamics between Asia-Pacific, EC and US stocks returns[J]. International Finance Review, 2007, 8: 39-61.
    [41] Jian Yang, Yinggang zhou, Wai-kin Leung. Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Stock, Bond, and Securitized Real Estate Markets[J]. Working paper.
    [42] Eugene F. Fama. Efficient Capital Markets: A Review of Theory and Empirical Work[J]. The Journal of Finance, 1970, 3(25): 383-417.
    [43]丘晓坚,孟卫东,王榆.信息机制在有效市场与分形市场的比较[J].重庆交通学院学报. 2006,2(25): 134-137.
    [44] Lin, W.R. Engle and K.Ito. Do Bulls and Bear Move Across Borders? Intemational Transmission ofstock returns and volatility[J].Review offinancial studies,1994, 01.7: 507-538.
    [45]李承元.有色金属的性质和用途[J].江西有色金属,1998,02: 22-24.
    [46]杨洁.国际石油价格与深圳行业分类股价指数之间的关联性研究[D].西南交通大学硕士学位论文,2007:34-40.
    [47]马克思.H.布瓦索.信息空间——认识组织、制度和文化的一种框架[M].上海:上海译文出版社, 2000: 85-92.
    [48]程希明.中国股市板块羊群效应的实证研究[J].系统工程理论与实践, 2004,12: 45-50
    [49] Barberis, Shleifer. A Survey of Behavioral Finance(M). Handbook of Financial Economics, Elsevier Science, 2003: 1053-1121.
    [50] H.M.马柯维茨.资产选择[M].考利斯基金专著,1952年16号.
    [51]沛巾杰.中国内地、相关和美国三地股市联动性的实证分析[M].中山大学,2008,5: 34-52.
    [52]宋芙蓉.人民币期货与现货市场的动态关联性研究[D].厦门大学硕士学位论文,200905.
    [53] Bollerslev,Tim. Generalized Autoregressive Conditional Heteroscedasticity[J]. Journal of Econometrics, 1986,31:307-327.
    [54] Engle, Robert F, and Victor K. Ng. Measuring and Testing the Impact of News on Volatility[J]. Journal of Finance, 1993,48:1022-1082.
    [55] Zakoian, J. M. Threshold Heteroskedastic Models[J]. Journal of Economic Dynamics and Control, 1994,18:931-944.
    [56] Andrew A. Christie. The stochastic behavior of common stock variances:Value, leverage and interest rate effects[J]. Journal of Financial Economics. 1982,10(4): 407-432.
    [57] Campbell, J.Y., and Henstschel,L. No news is good news: an asymmetric model of changing volatility in stock returns[J]. Journal of financial economics, 1992, 31: 281-318.
    [58] Peter Carr, Liuren Wu. Leverage Effect, Volatility Feedback, and Self-Exciting Market Disruptions: Disentangling the Multi-Dimensional Variations in S&P 500 Index Options[M]. Bloomberg Portfolio Research Paper No. 2009,03.
    [59] Michael McKenzie. The economics of exchange rate volatility asymmetry[J]. International Journal of Finance&Economics. 2002,7(3): 247–260.
    [60]董秀良,吴仁水.基于DCC-MGARCH模型的中国A、B股市场相关性及其解释[J].中国软科学, 2008,7: 125-133.
    [61] Bollerslev, Engle, and Wooldridge. A Capital Asset Pricing Model with Time Varying Covariances. Journal of Political Economy. 1988, 96, 116-131.
    [62] Bollerslev, T. Modeling the Coherence in Short-run Nominal Exchange Rate:A Multivariate Generalized ARCH Model[J]. Review of Economics and Statistics, 1990,(72):498-505.
    [63] Tsui, A.K. and Q.Yu. Constant Conditional Correlation in a Bivariate GARCHModel: Evidence from the Stock Market in China[J]. Mathematics and Computers in Simulation, 1999,(48): 503-509.
    [64] Engle, R.F. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroscedasticity Models[J]. Journal of Business and Economic statistics, 2002,(20):339-350.
    [65] Tse, Y K. and A.K.Tsui. A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-varying Correlations[J]. Journal of Business and Economic Statistics, 2002,(20): 351-362.
    [66] Vargas, G.A. What Drives the Dynamic Conditional Correlation of Foreign Exchange and Equity Retums?[R]. Singapore Management University, Working Paper, 2008.
    [67] Kroner, K.F. and V.K.Ng. Modeling Asymmetric Comovements of Asset Returns[J]. Review of Financial Studies, 1998, (11): 817-844.
    [68] Longin, F., and B.Solnik. Extreme Correlation of International Equity Markets[J]. Forthcoming in The Journal of Finance, 2002,5: 72-84.
    [69] Ang, A. and J.Chen. Asymmetric Correlations of Equity Portfolios[J]. Journal of Financial Economics, 2002,(63):443-494.
    [70] Machayluk, D., Wilson, P.J. and Zubruegg, R. Asymmetric Volatility, Correlation and Returns Dynamics Between the U.S. and U.K. Securitized Real Estate Markets[J]. Real Estate Economics. 2006,(34):109-131.
    [71] Cappiello L, Engle R, Sheppard K. Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns[J]. Journal of Financial Econometrics, 2006, (4): 537-572.

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