基于混沌理论的股票分析及其神经网络预测
he Analysis of stock based on chaotic theory and the it’s forecast based on the Neural Networks
混沌动力学理论提供了证券市场中股价波动的一种分析方法。为了考察中国证券市场的价格是否存在混沌行为，本文以1990.12.19到2008.4.24的上海证券市场每天的收盘数据，分析了价格波动的非线性特征，通过重构相空间方法重构了1990年到2008年上证指数时间序列的奇怪吸引子，计算其关联维数， 并求出其Lyapunov 指数为正，从而确认了上证指数时间序列的混沌行为。神经网络，是一个非线性系统，通过学习，可以实现非线性函数逼近，从而能更好的实现股票的走向预测.
he chaotic dynamics theory has provided a analytic method to stock price volatility in the stock market. To find out whether the price of stock has the chaotic behavior ,this pager has analyzed nonlinear character of the stock price ,based on the close index of stock, from the 19th of Dec in 1990 to 24th of Apr in 2008,and we have reconstructed the strange attractor of the time sequence by the method of reconstructing phase space ,we have calculated correlated dimension, and have proved that the exponent of Lyapunov is positive, then we affirmed that the chaotic behavior does exit in the time sequence of stock . The neural network is a nonlinear system , it can approach the nonlinear function by learning, by using the neural network, we can forecast the stock’s direction of the next day.
张中华、丁华福
数学自动化基础理论财政、金融
混沌行为重构相空间关联维数Lyapunov指数神网络
chaotic behaviorreconstructed phase spacecorrelated dimensionthe Lyapunov exponentneural network.
张中华,丁华福.基于混沌理论的股票分析及其神经网络预测[EB/OL].(2008-07-16)[2025-08-19].http://www.paper.edu.cn/releasepaper/content/200807-309.点此复制
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