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作出了稳健的分析。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。
This paper firstly discusses 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 Lya punov exponents and other detecting techniques,this study examines chaotic structure in China stock market.The results show that the stock market has significantly chaotic dynamics.Our conclusion can provide new approaches for research on financial market theory.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第6期229-232,共4页
Computer Engineering and Applications
基金
国家自然科学基金( the National Natural Science Foundation of China under Grant No.70471030)
湖南省教育厅资助科研课题( the research Project of Department of Education of Hunan Province
China under Grant No.06B063) 。
