Open AccessChaotic Dynamics Analysis Based on Financial Time Series
Author(s) -
Zheng Di Gu,
Yun Xu
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/2373423
Subject(s) - chaotic , bifurcation diagram , nonlinear system , computer science , series (stratigraphy) , time series , bifurcation , econometrics , wavelet , finance , mathematics , economics , artificial intelligence , physics , paleontology , quantum mechanics , machine learning , biology
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.