NDLI: Nonlinear dynamical complexity of agent-based stochastic financial interacting epidemic system

Content Provider	Springer Nature Link
Author	Lu, Yunfan Wang, Jun
Copyright Year	2016
Abstract	In an attempt to investigate the nonlinear dynamic mechanism of financial market microstructure, a stochastic interacting epidemic system is applied to establish an agent-based financial price dynamics, in which the spread of viruses and the physical condition of humans in the interacting epidemic system are, respectively, utilized to imitate the dispersal of the information and the investment attitude of the investors in a stock market. Combined with the ensemble empirical mode decomposition, the composite multiscale entropy analysis is applied to analyze the fluctuation complexity of financial time series, including the proposed model data and seven real stock indices. Further, the Zipf fluctuation behaviors of these time series are also investigated. The comparatively empirical results of the real indices and the simulation data show the similar fluctuation behaviors, indicating that this agent-based financial model can imitate some important properties of stock markets.
Starting Page	1823
Ending Page	1840
Page Count	18
File Format	PDF
ISSN	0924090X
Journal	Nonlinear Dynamics
Volume Number	86
Issue Number	3
e-ISSN	1573269X
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-08-04
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Nonlinear fluctuation complexity Financial time series model Stochastic interacting epidemic system Complexity analysis Zipf behavior Vibration, Dynamical Systems, Control Classical Mechanics Mechanical Engineering Automotive Engineering
Content Type	Text
Resource Type	Article
Subject	Ocean Engineering Applied Mathematics Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Aerospace Engineering

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