股市联动与信息扩散－基于沪深股市日内数据的非线性动态研究

Market Linkage and Information Diffusions: Evidences from Nonlinear Intraday Dynamics

10.6338/JDA.201012_5(6).0002

石凱(Kai Shi)；王琨(Kun Wang)

Fourier函数 ； 非参数因果关系检验 ； 非线性协整 ； Fourier function ； Nonparametric Casualty Test ； Nonlinear Cointegratio

Journal of Data Analysis

5卷6期（2010 / 12 / 01）

39 - 49

簡體中文

不同于现有诸多文献对非线性形式的先验设定，本文尝试使用Fourier级数近似未知形式的非线性结构，以便获取沪深股市间更为稳健的非线性协整和误差修正机制。非参数检验表明，沪深两市存在复杂的短期非线性因果关系。本文的结论为股市联动和信息传导机制的研究提供了新的视角和研究思路，是对现有文献的有益扩展。

In contrast to the present literatures, this article considers an unknown form of nonlinear model using Fourier approximations. Without any priori information about specifications, our results of nonlinear cointegration and error correct mechanism are more robust. Furthermore, the nonparametric casualty test which developed by Hiemstra & Jones shows that there exit more complicated relations between different stock markets. More importantly, this article supposes a new perspective to the future researchers in the fields of market linkage and information diffusions, thus it is an useful extension to the present literatures.

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