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上证指数收益率、波动性与成交量动态关系研究——基于日数据的非线性动力学实证分析
引用本文:罗登跃,王春峰. 上证指数收益率、波动性与成交量动态关系研究——基于日数据的非线性动力学实证分析[J]. 系统工程理论与实践, 2005, 25(7): 41-48. DOI: 10.12011/1000-6788(2005)7-41
作者姓名:罗登跃  王春峰
作者单位:(1)天津大学管理学院;(2)山东大学管理学院
基金项目:国家杰出青年科学基金(70225002);教育部优秀教师教学科研奖励基金
摘    要:对上证指数的收益率、波动性与成交量的动态关系进行了实证分析.采用EGARCH(1,1) M模型和ARMA(4,3) ARCH(1)模型分别测度上证指数收益率的波动性以及成交量的波动性,使用逐步回归法建立了收益率与成交量(R-V),收益率的波动性与成交量(hR-V)以及收益率的波动性与成交量的波动性(hR-hV)等的二维动力学模型,并用动力学方法研究以上诸二维系统的动力学行为.研究结果表明,虽然大量研究结果表明股市收益率时间序列存在混沌现象,但由收益率与成交量、波动性与成交量等构成的二维动力系统并不存在混沌现象.

关 键 词:波动性  成交量  Lyapunov指数  逐步回归  EGARCHM模型  混沌   
文章编号:1000-6788(2005)07-0041-08
修稿时间:2004-07-09

Empirical Analysis of the Relation Between Daily Return Rate, Volatility and Trading Volume of Shanghai Stock Market Comprising Index Based on Nonlinar Dynamics
LUO Deng-yue,WANG Chun-feng. Empirical Analysis of the Relation Between Daily Return Rate, Volatility and Trading Volume of Shanghai Stock Market Comprising Index Based on Nonlinar Dynamics[J]. Systems Engineering —Theory & Practice, 2005, 25(7): 41-48. DOI: 10.12011/1000-6788(2005)7-41
Authors:LUO Deng-yue  WANG Chun-feng
Affiliation:(1)School of Management,Tianjin University(2)School of Management,Shandong University
Abstract:This paper investigates the relationships between return rate,return volatility and trading volume of Shanghai Stock Market Comprising Index.We measure return volatility by EGARCH(1,1)-M(exponential generalized autoregressive conditional heteroscedasticity) model and volatility of trading volume by ARMA(4,3)-ARCH(1) model.we build two-dimensional dynamic system of return rate and trading volume(R-V),return volatility and trading volume(h-R-V),return volatility and volume volatility(h-R-h-V) by using stepwise regression method,and investigate the dynamic behaviour of these systems.The results indicate that there does not exist chaos in these two-dimensional dynamic systems composed by return and trading volume,return volatility and trading volume ,although many empirical analysis indicate that the time series of stock market return rate is chaotic.
Keywords:return volatility  trading volume  Lyapunov exponent  stepwise regression  EGARCH-M model  chaos
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