非线性协整建模研究及沪深股市实证分析

讨论了线性协整和非线性协整的涵义,指出在非线性系统中,非线性协整可以更好地刻画多个时间序列之间的均衡关系.提出了利用小波神经网络逼近非线性协整函数的方法,并给出了训练小波神经网络的变尺度算法.最后利用上海和深圳股指数据进行了实证研究,通过与BP神经网络的比较,证实了小波神经网络在非线性协整建模中的有效性,并说明沪深股市之间存在着非线性协整关系.

Study on modeling of nonlinear cointegration and empirical analysis of China''s stock markets

The paper discusses the significations of linear and nonlinear cointegration, and indicates that nonlinear cointegration theory can detect the equilibrium between time series more effectively in the nonlinear system. We use wavelet neural network to construct the nonlinear cointegration function, and give the DFP algorithm for network training. In the end, we give out the analysis of Shanghai and Shenzhen stock markets, and the results show the validity of wavelet neural network in nonlinear cointegra...