股票市场混沌吸引子的特征量——基于G-P算法与小数据量算法

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (6): 229-232.

股票市场混沌吸引子的特征量——基于G-P算法与小数据量算法

李红权邹琳

湖南师范大学商学院

收稿日期:2006-06-16 修回日期:1900-01-01 出版日期:2007-02-21 发布日期:2007-02-21
通讯作者: 李红权

Empirical study on Chaotic attractor in stock market based on G-P arithmetic and the small data arithmetic

Received:2006-06-16 Revised:1900-01-01 Online:2007-02-21 Published:2007-02-21

摘要/Abstract

摘要： 针对金融时间序列的特点，论文分析已有混沌特征量算法的基础上，采用特殊的对数线性趋势消除法（简记为LLD）处理数据、引入Rosenstein提出的小数据量算法等计算最大李雅普诺夫指数以及其它混沌系统的特征量，对我国证券市场的混沌动力学结构做出了稳健的分析。结果表明中国股市具有显著的非线性混沌特征，这一结论将为金融理论的研究提供新的方向。

关键词: 证券市场　　混沌动力学　　小数据量算法

Abstract: This paper firstly discussed traditional arithmetic on the detection of chaos and the characteristics of financial time series. And then using log-linear detrending method , small data set arithmetic proposed by Rosenstein to calculate largest Lyapunov exponents and other detecting techniques, this study examined chaotic structure in China stock market. The results show that the stock market has significantly chaotic dynamics. Our conclusion would provide new approaches for research on financial market theory.

Key words: Stock market Chaotic attractor Small data arithmetic

李红权邹琳. 股票市场混沌吸引子的特征量——基于G-P算法与小数据量算法[J]. 计算机工程与应用, 2007, 43(6): 229-232.