基于相空间重构的同业拆借利率混沌特性研究

中国管理科学 ›› 2006, Vol. ›› Issue (6): 140-143.

基于相空间重构的同业拆借利率混沌特性研究

李玉锁, 齐中英

哈尔滨工业大学管理学院, 黑龙江, 哈尔滨, 150001

收稿日期:2005-11-14 修回日期:2006-11-16 出版日期:2006-12-28 发布日期:2012-03-07

A Study on the Chaotic Characteristics for Interbank Rate Based on Phrase Space Reconstruction

LI Yu-suo, QI Zhong-ying

School of Management, Harbin Institute of Technology, Harbin 150001, China

Received:2005-11-14 Revised:2006-11-16 Online:2006-12-28 Published:2012-03-07

摘要/Abstract

摘要： 同业拆借利率在整个金融市场的利率结构中具有导向作用,因此对同业拆借利率波动的研究具有重要意义.本文基于相空间重构技术对我国银行间同业拆借利率进行了实证研究,通过关联维数和Kolmogorov熵这两个指数来研究我国银行间同业拆借利率的混沌特征.计算结果表明,银行间同业拆借利率具有混沌特性,这使得对同业拆借利率的长期预测成为不可能.

关键词: 同业拆借利率, 混沌, 关联维数, 相空间重构

Abstract: Interbank rates have important effects on other interest rates in the financial market,and therefore it is very important to research the fluctuation of interbank rate.Based on phrase space reconstruction,the paper gives empirical analysis on chaos in China interbank offered rate.The paper analyzes chaotic characteristics of China interbank offered rate by correlation dimension and Kolmogorov entropy.The results demonstrate that interbank rate has chaotic properties,which make the long term forecast impossible.

Key words: interbank rate, chaos, correlation dimension, phrase space reconstruction

中图分类号:

F713.50

李玉锁, 齐中英. 基于相空间重构的同业拆借利率混沌特性研究[J]. 中国管理科学, 2006, (6): 140-143.

LI Yu-suo, QI Zhong-ying. A Study on the Chaotic Characteristics for Interbank Rate Based on Phrase Space Reconstruction[J]. Chinese Journal of Management Science, 2006, (6): 140-143.

参考文献

[1] Richard D.H..The emergence of chaos from classical economic growth[J].Quarterly Journal of Economics,1983,54:201-213.
[2] Doyne F.J.,Sidorowich John J..Predicting chaotic time series[J].Physical Review Letters,1987,59:845-848.
[3] Henry A.D.I..Prdiction on chaotic nonlinear systems:Methods for time series with broadband fourier spectra[J].Physica,1990,41:1782-1807.
[4] Judd K.,Mees A..Modeling chaotic motions of a string from experimental data[J].Physica D,1996,92:221 -236.
[5] 叶中行,杨利平.上证指数的混沌特性分析[J].上海交通大学学报,1998,32(3):129-132.
[6] 段虎,沈菲.证券市场的混沌研究及相空间预测[J].数量经济技术经济研究,2002,(7):111-114.
[7] 郁俊莉,王其文,韩文秀.经济时间序列相空间重构与混沌特性判定研究[J].武汉大学学报(理学版),2004,50(1):33-37.
[8] 谢赤,杨妮.汇率行为的混沌性及其分形维描述[J].湖南大学学报(社会科学版),2005,19(5):50-56.
[9] 谢赤.利率行为描述与风险管理--利率期限结构及其应用研究[M].湖南人民出版社,2004:7l-73.
[10] Packard N.H.,Crutchifield J.P.,Farmer J.D.,Shaw R.S..Geometry from a time series[J].Physical Review Letters,1980,45:712-716.
[11] Takens F.Mane,et al.Detecting strange attractors in fluid turbulence.Rand D A,Young L S.Dynamical systems and turbulence[M].Vol.898 of Lecture Notes in Mathematics.Berlin:Springer,1986:366-381.
[12] Grassberger and Procaccia.Dimcnsions and entropies of strange attractors from a fluctuating dynamics approach[J].Physics,1984,13:34-54.
[13] Theiler J.,Eubank S.Testing for nonlinearity in time series:the mthod of surrogate data[J].Physica D,1992,58:77-94.
[14] Kugiumtzis D.,Lillelqendlie B..State space reconstruction parameters in the analysis of chaotic time series the role of the time window length[J].Physica D.1996,95:13 -28.
[15] Cao Liang-yue,Alistair Mees.Practical method for determining the minimum embedding dimension of a scalar time series[J].Physica D,1997,110:43-50.