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中国股市价格波动与信息流关系的实证分析
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摘要
股票市场中的量价关系是指股票价格的波动与交易量之间的关系,量价关系研究可推进证券市场微观结构研究,对解决我国证券市场中股价波动的一些难点问题,有着重要的理论价值和现实意义。Clark(1973),Epps(1976),Tauchen & Pitts(1983)等建立并发展了量价关系的混合分布假说(MDH)理论。该理论认为,价格波动与交易量是由潜在的不可观测的信息流共同决定的,信息流的冲击将同时产生交易量和价格波动,信息流即为混合变量,日交易次数和交易量均可以作为信息流的替代指标。可见,研究交易量对价格波动的影响,实质上是分析信息流对波动性的影响。通过信息流与股价波动性之间关系的研究,有助于了解资本市场的微观结构,揭示价格波动产生的根源。本文从信息与股价运行的基本理论出发,引出反映量价关系的混合分布假说,介绍其理论和相关研究,在混合分布假说(MDH)理论的分析框架下,对中国股票市场价格波动与信息流之间的关系进行实证分析。
     本文共分四个部分:
     第一部分,信息与股价运行的基本理论。简要介绍了股票价格的波动性,分析了信息与股价运行的关系:信息是股票价格运行的基础,是股票价格波动的最直接动因,股价运行同时反映信息。
     第二部分,混合分布假说。介绍了混合分布假说理论及其相关研究;在简要分析ARCH类模型并结合近年来研究的基础上,详细阐述了混合分布假说理论的分析框架。
     第三部分,混合分布假说在中国股票市场的实证检验。该部分以1993/1/11起到2002/12/31的上证综合指数与深证成份指数日收盘价为研究对象,采用非预期交易量作为信息流的替代指标,分析信息流与波动性之间的关系。
     第四部分,结论部分。本部分主要是第三部分研究结果的总结,并分析了实证研究过程中存在的缺陷。
Volume-price relation in stock market refers to the relationship between price volatility of shares and trading volume. Research on volume-price relation can promote study on the microstructure of stock market, for its important theoretical and practical value to resovle some problems of price volatility in Chinese stock market. Clark(1973), Epps(1976), Tauchen & Pitts(1983) established and developed the Mixture of Distributions Hypothesis (MDH). It believes that price volatility and trading volume are determined by potential and unobservable information flow whose impact creates both price volatility and trading volume at the same time. Information flow is a mixed variable, which can be substituted by two indexes-trading times per day and trading volume. Therefore, exploration into the trading volume impacts on price volatility is actually the analysis of the information flow impact on it. Research on the relationship between information flow and price volatility of shares helps to know the microstructure of captial market and unveil the cause of price volatility. This paper starts with the basic theories on information and the operation of stock price, introduces the MDH theory and its relative research, and makes case analysis within MDH theory on the relationship between price volatility and information flow in Chinese stock market.
    The paper has four parts:
    The first part introduces the basic theories on information and the operation of stock price. It brings in the volatility of stock price. Information is the base of stock price operation and actually is the direct reason of volatility, stock price operation reflects information on the same time.
    The second part presents the MDH, introducing its theory and relative exploration. After the brief analysis on ARCH model, it demonstrates the analysis frame of MDH in detail.
    The case test of MDH in Chinese stock market is found in the third part.
    
    
    
    Analyzing the closing prices of composite index in Shanghai Stock Market and component index in Shenzheng Stock Market between January 11th 1993 and December 31th 2002 and using unexpected trading volume as the substitute for information flow, it illustrates the relationship between information flow and price volatility.
    The fourth part is the conclusion of this paper. It concludes the research result of the third part and presents the defects in the analysis.
引文
1. Dow and Gorton, 1997, Stork Market Efficiency and Economic Efficiency:Is There a Connection?,Journal of Finance52, 1087-1129
    2. Peter K. Clark, 1973, A Subordinated Stochastic Process Model with Finite Variance For Speulative Prices,Econometrica Vol. 41,No. 1.
    3. Epps, W. and M. Epps , 1976, The stochastic dependence of security price changes and transaction volumes: implications for the mixture of distributions hypothesis, Econometrica 44, 305-321
    4. Karpoff.J.M, 1987, The relation between price changes and trading volume, Journal of Finacial and Quantitative Analysis 22, 279-292
    5. Tauchen G. E. and M.Pitts, 1983, The price variability-volume relationship on speculative markets, Econometrica 51, 485-506
    6. Lamoureux C.G.,W.D.Lastrapes, 1990, Heteroskedasticity in stock return data:volume versus GARCH effects,Journal of Finance, XLV, No. 1, 221-229
    7. Patelis A.D. 1997, Stock Return Predictability and The Role of Monetary Policy, Journal of Finance 52, 1951-1972
    8. ChenN.F.,RollR. RossS.A. 1986, Economic Force and the Stock Market, Journal of Business59, 383-403
    9. BittingmayerG. 1998, Output, StockVolatility, and Political Uncertainty in a Natural Experiment:Germany,1880-1940", Journal of Finance53, 2243-2257
    10. Culter D.M.,James M.P.,and Summers L.H. 1989, What Moves Stock Prices? Journal of Portfolio Management 15, 4-12
    11. MitchellM.L. and MulherinJ.H. 1994, The Impact of Information on the Stock Market, Journal of Finance 49, 923-950
    
    
    12. Andersen, T.G., 1996, Return volatility and trading volume: an informa tion flow interpretation of stochastic volatility. Journal of Finance 51, 169-204
    13. Liesenfeld R. 2001, A generalized bivariate mixture model for stock price volatility and trading volume. Journal of Econometrics 104, 141-178
    14. Kim, D. and S. Kon, 1994, Alternative models for the conditional heteroskedasticity of stock returns, Journal of Business 67, 563-588
    15. Lamoureux, C.G., & Lastrapes, W.D., 1994, Endogenous trading volume and momentum in stock-return volatility. Journal of Business and Economic Statistics 12, 253-260
    16. Gallo, G. M., and B. Pacini, 2000, The effects of trading activity on market volatility, The European Journal of Finance 6, 163-175
    17. Omran, M. F., and E. McKenzie, 2000,Heteroskedasticity in stock returns data revisited: volume versus GARCH effects, Applied Financial Economics 10, 553-560
    18. Bwo-Nung Huang and Chin-Wei Yang,2001,An empirical investigationof trading volume and return volatility of the Taiwan Stock Market, Global Finance Journal 12, 55-77
    19. Martin T.Bohl and Harald Henke, 2001, Trading Volume and Stock Market Volatility: The Polish Case, http://viadrina. EuvFrankfurto.de/gk-wiwi
    20. Terry A.Marsh,Niklas Wagner, 2000, Return-volume dependence and Extremes in International Equity markets.Working paper RPF-293,Haas School of Business,UC Berkeley.
    21. Brailsford,T.J.,1996, The empirical relationship between trading volume, returns, and volatility.Accounting and Finance 35,
    
    89-111
    22. RagunathanV., Peker,A., 1997, Price volatility, trading volume, and mark- et depth:evidence from the Australia futures markets, Applied Financial Economics 7, 447-454
    23. Bollerslev, T., and D. Jubinski, 1999, Equity trading volume and volatility: Latent information arrivals and common long-run dependencies, Journal of Business and Economic Statistics 17, 9-21
    24. Hodrick, R.J., Prescott, E.C., 1993, Postwar U.S. Business Cycles" An Empirical Investigation, Quarterly Journal of Economics 108, 905-939
    25.[英]凯恩斯(1936),就业、利息与货币通论[M],商务印书馆,1993年版第133-134页。
    26.靳云汇、于存高,中国股票市场与国民经济关系的实证研究(上、下)[J],金融研究,1998年第3期。
    27.包建祥,对股票市场信息定价制度的重新诠释[J],投资研究,1999年第5期,37-40。
    28.李双成、王春峰,中国股票市场量价关系的实证研[J],山西财经大学学报,2003年第4期,82-85。
    29.姚尔强,股价波动的理论研究与实证分析[M],经济科学出版社,2002.9。
    30.汪同三、张守一,21世纪数量经济学[M],中国统计出版社,2001。
    31.陈怡玲、宋逢明,中国股市价格变动与交易量关系的实证研究[M],管理科学学报,2000年第6期,62-68。

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