skip to main content

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

Lu, Yunfan ; Wang, Jun

Nonlinear Dynamics, 2016, Vol.86(3), pp.1823-1840 [Peer Reviewed Journal]

Full text available

Citations Cited by
  • Title:
    Nonlinear dynamical complexity of agent-based stochastic financial interacting epidemic system
  • Author: Lu, Yunfan ; Wang, Jun
  • Subjects: Nonlinear fluctuation complexity ; Financial time series model ; Stochastic interacting epidemic system ; Complexity analysis ; Zipf behavior
  • Is Part Of: Nonlinear Dynamics, 2016, Vol.86(3), pp.1823-1840
  • Description: 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.
  • Language: English
  • Identifier: ISSN: 0924-090X ; E-ISSN: 1573-269X ; DOI: 10.1007/s11071-016-2995-7

Searching Remote Databases, Please Wait