Chaotic Dynamics Analysis Based on Financial Time Series

• Main Authors: Zheng Gu, Yuhua Xu
• Format: Article
• Language: English
• Published: Hindawi-Wiley 2021-01-01
• Series: Complexity
• Online Access: http://dx.doi.org/10.1155/2021/2373423

It is a common phenomenon in the field of financial research to study the dynamic of financial market and explore the complexity of financial system by using various complex scientific methods. In this paper, the chaotic dynamic properties of financial time series are analyzed. Firstly, the nonlinear characteristics of the data are discussed through the empirical analysis of agriculture index data; the daily agriculture index returns can be decomposed into the different scales based on wavelet analysis. Secondly, the dynamic system of some nonlinear characteristic data is established according to the Taylor series expansion form, and the corresponding dynamic characteristics are analyzed. Finally, the bifurcation diagram of the system shows complicated bifurcation phenomena, which provides a perspective for the analysis of chaotic phenomena of economic data.