依据运行趋势的中国股市量价关系研究
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摘要
建立在有效市场理论基础上的现代金融理论在实践上遇到了很多挑战,行为金融学为人们解释实践中的一些困惑提供了有效的手段。随着证券市场的加速国际化,经济、政治等影响因素都会改变人们对未来的预期和投资行为,进而通过股市最基本的变量——成交量和成交价表现出来,影响股市运行趋势;同时人们会根据股市运行趋势调整自己的行为,这也会通过成交量和成交价表现出来,从而影响量价关系。因此股市的运行趋势和量价关系通过人们的预期和投资行为相互影响,不可分割。而现有量价关系的研究虽然很多,所用的研究方法也很多,但是分割了运行趋势和量价关系的紧密联系,其研究的成果很难展现受复杂因素影响的量价间的真实关系。
本文紧紧抓住股市的趋势性,将趋势分析融于股市的量价分析之中,同时将股市的运动和能量的转化结合起来,将成交量能转化为维持当前股价势能的能量和促进股价向更高势能运动的能量。进而建立了运行趋势研究法,包括均衡价格的确定、运行趋势线的确定、依据运行趋势的股市运动能量转化分析和依据运行趋势的成交量分解。之后将运行趋势研究法和量价关系的研究结合起来,分析分解出的促进股价变化的成交量和均衡价格之间的关系,运行趋势研究法能很好的弱化机构人为操纵的影响,有利于展现量价之间的真正关系。
本文将运行趋势性研究法应用于量价研究的同时,还将最新金融理论Copula函数应用于量价相关性的研究之中,克服了以往研究中需对量价分布进行严格限定的局限。随后论文将运行趋势研究法分别与线性和非线性的方法相结合,应用于量价因果关系的研究中,既减少了机构人为操纵对因果关系研究结果的影响,也能便于分析比较不同市场环境中量价关系的不同,并将依据运行趋势的量价因果关系研究和常规量价因果关系研究做对比,通过分析和比较,揭示不同市场环境中投资者的行为差异对量价关系的影响,也从这个角度证实了依据运行趋势研究量价关系的重要意义。论文对量价相关性和因果关系的研究是依据运行趋势展开的,研究结果体现了运行趋势对量价关系的作用,并根据不同市场环境下的研究结果差异提出了证券市场管理的政策建议。最后,文章研究了量价关系对运行趋势的反作用,即量价背离关系的积累会导致运行趋势的改变。并借鉴经济学弹性的概念,建立量价弹性系数指标,使量价关系的异动通过量价弹性指标的异动体现出来,为预测趋势转变的关键区域准备了判断工具;论文从行为金融学的角度,分析得出量价背离的持续会导致运行趋势的变化,而且运行趋势转变前量价关系都会发生不同于原趋势的异动,因而运行趋势即将转变的关键区域就转变为发现和确定量价异动的区域,借助量价弹性系数这个工具,建立了依据运行趋势的关键区域预测法,解决了股市运行趋势预测的难题。
本文大量的理论分析和实证研究得到以下结果:第一,量价之间的相关性具有广泛性,总成交量及变化、分解的促进股价变化的成交量及变化都与均衡价格收益有正相关关系;第二,在牛市中,收益和成交量之间存在单向的Granger因果关系,而在熊市中,收益和成交量之间存在双向的Granger因果关系,不论熊市和牛市,上证和深证量价间均没有非线性因果关系;第三,不同市场环境的比较中还发现行为金融在股市中的作用明显,通过比较发现依据运行趋势的因果关系分析能反映量价间的稳定关系,而常规因果分析方法却反映不出来;第四,通过建立包含量价信息的量价弹性系数指标和依据运行趋势的关键区域研究法,可以实现对趋势转变关键区域的预测。
本文将建立的运行趋势研究法应用于量价研究中,以及将新的金融理论Copula函数应用于量价研究,包括非线性研究的应用,将有助于丰富量价研究的理论。对股市趋势运行不同阶段的投资者行为分析,以及不同市场环境中量价关系的比较,将推动行为金融学在股市分析中的发展。文章建立的依据运行趋势的关键区域预测法,包含了对量价关系、股市趋势性、投资者行为变化的综合应用,也必将丰富股市预测理论的发展。
Modern financial theories, which based on EMH are challenged by some practice puzzles; however, behavior finance can efficiently explain those puzzles. As the accelerated internationalization of stock market, economy, politics and other factors can change people’s investment behaviors and expectations of future, then influence moving tendency of stock market by the two most basic variables: volume and price. At the same time, people will change their behaviors by moving tendency of stock, and these actions will be exhibited by volume and price, so they can influence volume-price relation. Therefore, the moving tendency of stock and volume-price relation are influenced each other through people’s expectation and investment behaviors and become indivisible complex. Also there are many researches about volume-price relation following many research methods, but these researches divided the close relation between stock moving tendency and volume-price relation, so these researches were difficult in exhibiting true volume-price relation.
The paper grasps the stock tendency, places tendency analysis into volume-price analysis. At the same time, combines stock movement to stock energy transform, then transforms volume energy into a prat of potential energy which uses to sustain current price and the other energy which promotes higher potential energy in high price.The paper also builts up analysis methods by moving tendency, which includes computing equilibria price, looking for moving tendency line, disassembling volume. Next, the paper analyzes relation between disassembled volume promoting price movement and equilibria price, the methods can decrease influence of human manipulation in stock market and avail to exhibit true volume-price relation.
On the one hand, the paper places analysis methods of moving tendency into volume-price analysis; on the other hand, it places new financial theory Copula into volume-price relativity research. This avoids disadvantage of strict hypothesis of variable distribution in past researches. Later, the paper combines analysis methods of moving tendency with linear and nonlinear analysis respectively, applies to volume-price causality research. Thus it can decrease influence of human manipulation, and also analysis difference of volume-price relation in difference market condition expediently by contrast, and then contrasts moving tendency analysis in researching volume-price relation to ususl causality reseach. After the analysis and contrast, the paper reveals the influence of investors’behavior on volume-price relation in different market condition. The researchs embody effecting on volume-price relation by moving tendency, including volume-price relativity research and volume-price causality, the paper propose on securities management by the difference results in difference conditions. In the end, the paper researchs reaction on moving tendency by volume-price relativity, that is volume-price deviation leading to the change of moving tendency. Then builds up volume-price elasticity by conception of elasticity in economics, so the change of volume-price elasticity can exhibit the abnormal change of volume-price relation, it prepares tool in estimating key period of stock moving tendency. The paper concludes that the volume-price continuous deviation leads to the change of moving tendency by behaviour finance, and the volume-price relation would difference with that of current moving tendency before reversion. So the key period of tendency reversion is equal to the period of abnormal fluctuation in volume-price relation. Thus it buils analysis methods of moving tendency making use of the tool of volume-price elasticity coefficient, it resolve the difficulty in forecasting stock moving tendency.
The paper obtains some conclusions after many theories analysis and empirical tests: Firstly, Volume-price relativity is extensive: total volume or it’s change, disassembled volume promoting price movement or it’s change all has plus relativity to equilibria price. Secondly, there is unilateralisms Granger casuality in bullmarket, while there is bidirectional Granger casuality in bearmarket. There is not nonlinear Granger casuality in both markets. Third, Behavior finance has remarkable effects after contrasting to different investment conditions. Moreover, causality research by moving tendency can reflect the stable relation while usual causality research can’t do. Fourth, it can be ture forecasing key period of tendency reversion by building volume-price elasticity coefficient containing composite information of volume-price and analysis methods of moving tendency.
The paper avails to the abundance of volume-price theory by applying analysis methods of moving tendency, new financial theory Copula function and nonlinear research to volume-price research. It can also promote the application of behavior finance in stock analysis by analyzing investors’behaviors in different period of a tendency, and contrasing volume-price relation in different investment conditions. The methods forecast on key period by moving tendency, containing composite application of volume-price relation, stock tendency and investors’behaviors change, will improve the progress of stock forecast theory.
本文紧紧抓住股市的趋势性,将趋势分析融于股市的量价分析之中,同时将股市的运动和能量的转化结合起来,将成交量能转化为维持当前股价势能的能量和促进股价向更高势能运动的能量。进而建立了运行趋势研究法,包括均衡价格的确定、运行趋势线的确定、依据运行趋势的股市运动能量转化分析和依据运行趋势的成交量分解。之后将运行趋势研究法和量价关系的研究结合起来,分析分解出的促进股价变化的成交量和均衡价格之间的关系,运行趋势研究法能很好的弱化机构人为操纵的影响,有利于展现量价之间的真正关系。
本文将运行趋势性研究法应用于量价研究的同时,还将最新金融理论Copula函数应用于量价相关性的研究之中,克服了以往研究中需对量价分布进行严格限定的局限。随后论文将运行趋势研究法分别与线性和非线性的方法相结合,应用于量价因果关系的研究中,既减少了机构人为操纵对因果关系研究结果的影响,也能便于分析比较不同市场环境中量价关系的不同,并将依据运行趋势的量价因果关系研究和常规量价因果关系研究做对比,通过分析和比较,揭示不同市场环境中投资者的行为差异对量价关系的影响,也从这个角度证实了依据运行趋势研究量价关系的重要意义。论文对量价相关性和因果关系的研究是依据运行趋势展开的,研究结果体现了运行趋势对量价关系的作用,并根据不同市场环境下的研究结果差异提出了证券市场管理的政策建议。最后,文章研究了量价关系对运行趋势的反作用,即量价背离关系的积累会导致运行趋势的改变。并借鉴经济学弹性的概念,建立量价弹性系数指标,使量价关系的异动通过量价弹性指标的异动体现出来,为预测趋势转变的关键区域准备了判断工具;论文从行为金融学的角度,分析得出量价背离的持续会导致运行趋势的变化,而且运行趋势转变前量价关系都会发生不同于原趋势的异动,因而运行趋势即将转变的关键区域就转变为发现和确定量价异动的区域,借助量价弹性系数这个工具,建立了依据运行趋势的关键区域预测法,解决了股市运行趋势预测的难题。
本文大量的理论分析和实证研究得到以下结果:第一,量价之间的相关性具有广泛性,总成交量及变化、分解的促进股价变化的成交量及变化都与均衡价格收益有正相关关系;第二,在牛市中,收益和成交量之间存在单向的Granger因果关系,而在熊市中,收益和成交量之间存在双向的Granger因果关系,不论熊市和牛市,上证和深证量价间均没有非线性因果关系;第三,不同市场环境的比较中还发现行为金融在股市中的作用明显,通过比较发现依据运行趋势的因果关系分析能反映量价间的稳定关系,而常规因果分析方法却反映不出来;第四,通过建立包含量价信息的量价弹性系数指标和依据运行趋势的关键区域研究法,可以实现对趋势转变关键区域的预测。
本文将建立的运行趋势研究法应用于量价研究中,以及将新的金融理论Copula函数应用于量价研究,包括非线性研究的应用,将有助于丰富量价研究的理论。对股市趋势运行不同阶段的投资者行为分析,以及不同市场环境中量价关系的比较,将推动行为金融学在股市分析中的发展。文章建立的依据运行趋势的关键区域预测法,包含了对量价关系、股市趋势性、投资者行为变化的综合应用,也必将丰富股市预测理论的发展。
Modern financial theories, which based on EMH are challenged by some practice puzzles; however, behavior finance can efficiently explain those puzzles. As the accelerated internationalization of stock market, economy, politics and other factors can change people’s investment behaviors and expectations of future, then influence moving tendency of stock market by the two most basic variables: volume and price. At the same time, people will change their behaviors by moving tendency of stock, and these actions will be exhibited by volume and price, so they can influence volume-price relation. Therefore, the moving tendency of stock and volume-price relation are influenced each other through people’s expectation and investment behaviors and become indivisible complex. Also there are many researches about volume-price relation following many research methods, but these researches divided the close relation between stock moving tendency and volume-price relation, so these researches were difficult in exhibiting true volume-price relation.
The paper grasps the stock tendency, places tendency analysis into volume-price analysis. At the same time, combines stock movement to stock energy transform, then transforms volume energy into a prat of potential energy which uses to sustain current price and the other energy which promotes higher potential energy in high price.The paper also builts up analysis methods by moving tendency, which includes computing equilibria price, looking for moving tendency line, disassembling volume. Next, the paper analyzes relation between disassembled volume promoting price movement and equilibria price, the methods can decrease influence of human manipulation in stock market and avail to exhibit true volume-price relation.
On the one hand, the paper places analysis methods of moving tendency into volume-price analysis; on the other hand, it places new financial theory Copula into volume-price relativity research. This avoids disadvantage of strict hypothesis of variable distribution in past researches. Later, the paper combines analysis methods of moving tendency with linear and nonlinear analysis respectively, applies to volume-price causality research. Thus it can decrease influence of human manipulation, and also analysis difference of volume-price relation in difference market condition expediently by contrast, and then contrasts moving tendency analysis in researching volume-price relation to ususl causality reseach. After the analysis and contrast, the paper reveals the influence of investors’behavior on volume-price relation in different market condition. The researchs embody effecting on volume-price relation by moving tendency, including volume-price relativity research and volume-price causality, the paper propose on securities management by the difference results in difference conditions. In the end, the paper researchs reaction on moving tendency by volume-price relativity, that is volume-price deviation leading to the change of moving tendency. Then builds up volume-price elasticity by conception of elasticity in economics, so the change of volume-price elasticity can exhibit the abnormal change of volume-price relation, it prepares tool in estimating key period of stock moving tendency. The paper concludes that the volume-price continuous deviation leads to the change of moving tendency by behaviour finance, and the volume-price relation would difference with that of current moving tendency before reversion. So the key period of tendency reversion is equal to the period of abnormal fluctuation in volume-price relation. Thus it buils analysis methods of moving tendency making use of the tool of volume-price elasticity coefficient, it resolve the difficulty in forecasting stock moving tendency.
The paper obtains some conclusions after many theories analysis and empirical tests: Firstly, Volume-price relativity is extensive: total volume or it’s change, disassembled volume promoting price movement or it’s change all has plus relativity to equilibria price. Secondly, there is unilateralisms Granger casuality in bullmarket, while there is bidirectional Granger casuality in bearmarket. There is not nonlinear Granger casuality in both markets. Third, Behavior finance has remarkable effects after contrasting to different investment conditions. Moreover, causality research by moving tendency can reflect the stable relation while usual causality research can’t do. Fourth, it can be ture forecasing key period of tendency reversion by building volume-price elasticity coefficient containing composite information of volume-price and analysis methods of moving tendency.
The paper avails to the abundance of volume-price theory by applying analysis methods of moving tendency, new financial theory Copula function and nonlinear research to volume-price research. It can also promote the application of behavior finance in stock analysis by analyzing investors’behaviors in different period of a tendency, and contrasing volume-price relation in different investment conditions. The methods forecast on key period by moving tendency, containing composite application of volume-price relation, stock tendency and investors’behaviors change, will improve the progress of stock forecast theory.
引文
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58 Starks M., Smirlock L..An Experical Analysis of the Stock Price-volume Relationship. Journal of Banking and Finance.1998, 12(1): 31-42
59 H.Gurgul, P.Majdosz, R.Mestel. Joint Dynamics of Prices and Trading Volume on the Polish Stock Market. Managing Global Transitions.2003, 3(2): 139-156
60 Gunduz L.,Hatemi J. A. Stock Price and Volume Relation in Emerging Markets. 6th ERC/METU International Conference on Economics Ankara,Turkey, 2002.Ankara,Middle East Technical University,2002:107-111
61 Hinich M., Patterson D.M. Evidence of Nonlinearity in Daily Stock Returns. Journal of Business and Economic Statistics. 1985, 3:47-73
62 Gallant A. R., Rossi P. E., Tauchen G. Stock Price and Volume. The Review of Financial Studies. 1992,5:199-242
63 Brock, Lakonishok, LeBaron. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance. 1992,7:1731-1764
64 Duffee, G.. Trading Volume and Return Reversals. Finance and Economics Discussion Paper Series.1992, (192): 45-56
65 Engle, R.F.. Autoregrressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation.Econometrica. 1982, (50): 987-1006
66 Bollerslev T. Generalized Autoregressive Conditional Heteroscedastic. Journal of Econnometrics.1986, (31): 307-327
67 Hendrik Bessembinder, Paul J., Seguin. Futures-trading Activity and Stock Price Volatility. Journal of Finance. 1992, (5): 2015-2034
68 Terry A., Marsh, Niklas, Wagner. Return-volume Dependence and Extremes in International Equity markets. Working paper RPF-293,Haas School of Business, UC Berkeley.2000, 5-10
69 Richard Gerlach, Cathy W.S., Chen. Asymmetric Responses of International Stock Markets to Trading Volume. Physical A-statistical Mechanics Applications. 2006, 360 (2): 422-444
70 Sklar A. Functions De Repartition a’n Dimensions et Leurs Marges. Publications del’Institut de l’Universite’de Paris.1959, 8:229-231
71 Genest.C, Rivest.L. Statistical Inference Procedures for Bivariate Archimedean Copulas. Journal of American Statistical Association.1993, 88:1034-1043
72 Davision R, Mackinnon.J. Estimation and Inference in Econometrics. New York:Oxford University Press, 1993:56-78
73 Joe H. Parametric Families of Multivariate Distributions with Given Margins. Journal of Maltivarite Analisis.1993, 46(2): 262-282
74 Embrechts P, Mcneil A, Straumann D. Correlation: Pitfalls and Alternatives.Risk. 1999,25(5): 11-21
75 Bouye E, Durrleman V, Nikeghbal A, et al. Copulas for Finance: A Reading Guide and some Applications. Londres: City University Business School Financial Econometrics Research Center, Working Paper. 2000
76 Claudio Romano. Calibrating and Simulating Copula Functions:an Aplication to Italian Stock Market.Rome:Working Paper of CIDEM.2002
77 Beatriz V.M., Rafael.M. Measuring Financial Risks with Copulas. International Review of Financial Analysis.2004, 13:27-45
78樊智,张世英.金融市场的效率与分形市场理论.系统工程理论与实践.2002,22(3):13-19
79曹宏铎,李昊.经济系统分形机制与股票市场R/S分析.系统工程理论与实践,2003,(3):25-28
80李亚静、何跃、朱宏泉.中国股市收益率与波动性长记忆性的实证研究[J].系统工程理论与实践.2003,(1):9-15
81陈梦根.股票价格分析特征的实证研究:修正R/S分析.统计研究,2003,(4):57-61
82叶行,林水山.基于分形理论下的股票市场有效性研究.中南大学学报(社会科学版).2005,(2):222-226
83张晓莉,严广乐.中国股票市场长记忆特征的实证研究.系统工程学报.2007,2:80-84.
84章融,金雪军.证券市场中投资者短期行为分析.数量经济技术经济研究.2003,1:68-71
85孙建军,王美今.股市政策对个体证券投资者交易行为的影响.数量经济技术经济研究.2004,6:141-146
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58 Starks M., Smirlock L..An Experical Analysis of the Stock Price-volume Relationship. Journal of Banking and Finance.1998, 12(1): 31-42
59 H.Gurgul, P.Majdosz, R.Mestel. Joint Dynamics of Prices and Trading Volume on the Polish Stock Market. Managing Global Transitions.2003, 3(2): 139-156
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61 Hinich M., Patterson D.M. Evidence of Nonlinearity in Daily Stock Returns. Journal of Business and Economic Statistics. 1985, 3:47-73
62 Gallant A. R., Rossi P. E., Tauchen G. Stock Price and Volume. The Review of Financial Studies. 1992,5:199-242
63 Brock, Lakonishok, LeBaron. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance. 1992,7:1731-1764
64 Duffee, G.. Trading Volume and Return Reversals. Finance and Economics Discussion Paper Series.1992, (192): 45-56
65 Engle, R.F.. Autoregrressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation.Econometrica. 1982, (50): 987-1006
66 Bollerslev T. Generalized Autoregressive Conditional Heteroscedastic. Journal of Econnometrics.1986, (31): 307-327
67 Hendrik Bessembinder, Paul J., Seguin. Futures-trading Activity and Stock Price Volatility. Journal of Finance. 1992, (5): 2015-2034
68 Terry A., Marsh, Niklas, Wagner. Return-volume Dependence and Extremes in International Equity markets. Working paper RPF-293,Haas School of Business, UC Berkeley.2000, 5-10
69 Richard Gerlach, Cathy W.S., Chen. Asymmetric Responses of International Stock Markets to Trading Volume. Physical A-statistical Mechanics Applications. 2006, 360 (2): 422-444
70 Sklar A. Functions De Repartition a’n Dimensions et Leurs Marges. Publications del’Institut de l’Universite’de Paris.1959, 8:229-231
71 Genest.C, Rivest.L. Statistical Inference Procedures for Bivariate Archimedean Copulas. Journal of American Statistical Association.1993, 88:1034-1043
72 Davision R, Mackinnon.J. Estimation and Inference in Econometrics. New York:Oxford University Press, 1993:56-78
73 Joe H. Parametric Families of Multivariate Distributions with Given Margins. Journal of Maltivarite Analisis.1993, 46(2): 262-282
74 Embrechts P, Mcneil A, Straumann D. Correlation: Pitfalls and Alternatives.Risk. 1999,25(5): 11-21
75 Bouye E, Durrleman V, Nikeghbal A, et al. Copulas for Finance: A Reading Guide and some Applications. Londres: City University Business School Financial Econometrics Research Center, Working Paper. 2000
76 Claudio Romano. Calibrating and Simulating Copula Functions:an Aplication to Italian Stock Market.Rome:Working Paper of CIDEM.2002
77 Beatriz V.M., Rafael.M. Measuring Financial Risks with Copulas. International Review of Financial Analysis.2004, 13:27-45
78樊智,张世英.金融市场的效率与分形市场理论.系统工程理论与实践.2002,22(3):13-19
79曹宏铎,李昊.经济系统分形机制与股票市场R/S分析.系统工程理论与实践,2003,(3):25-28
80李亚静、何跃、朱宏泉.中国股市收益率与波动性长记忆性的实证研究[J].系统工程理论与实践.2003,(1):9-15
81陈梦根.股票价格分析特征的实证研究:修正R/S分析.统计研究,2003,(4):57-61
82叶行,林水山.基于分形理论下的股票市场有效性研究.中南大学学报(社会科学版).2005,(2):222-226
83张晓莉,严广乐.中国股票市场长记忆特征的实证研究.系统工程学报.2007,2:80-84.
84章融,金雪军.证券市场中投资者短期行为分析.数量经济技术经济研究.2003,1:68-71
85孙建军,王美今.股市政策对个体证券投资者交易行为的影响.数量经济技术经济研究.2004,6:141-146
86杨炘,王小征,滕召学.中国股市个人与机构投资者的羊群效应清华大学学报(自然科学版).2004,12(44):1610-1614
87郭磊,吴冲锋,凌传荣.股票市场羊群行为的中美比较.上海交通大学学报.2006,40(4):705-708
88赵龙凯,岳衡.关于我国股指心理关口的实证研究.金融研究.2006,(2):61-69
89黄建兵,唐国兴.股票价格波动与成交量的天内效应和周内效应.数量经济技术经济研究.2003,(4):157-161
90肖峻,陈伟忠,王宇喜.中国股市基于成交量的价格动量策略.同济大学学报(自然科学板).2006 34(8): 1126-1130
91王杉,宋毓明.中国股票市场的简单量价关系模型.管理科学学报,2006,8(4):65-72
92张博,殷仲民.上海证券价格与交易量关系实证分析.大连理工大学学报(社会科学版).2007,28(3):18-24
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