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Nonlinear Fluctuation Behavior of Financial Time Series Model by Statistical Physics System

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  • Wuyang Cheng
  • Jun Wang

Abstract

We develop a random financial time series model of stock market by one of statistical physics systems, the stochastic contact interacting system. Contact process is a continuous time Markov process; one interpretation of this model is as a model for the spread of an infection, where the epidemic spreading mimics the interplay of local infections and recovery of individuals. From this financial model, we study the statistical behaviors of return time series, and the corresponding behaviors of returns for Shanghai Stock Exchange Composite Index (SSECI) and Hang Seng Index (HSI) are also comparatively studied. Further, we investigate the Zipf distribution and multifractal phenomenon of returns and price changes. Zipf analysis and MF-DFA analysis are applied to investigate the natures of fluctuations for the stock market.

Suggested Citation

  • Wuyang Cheng & Jun Wang, 2014. "Nonlinear Fluctuation Behavior of Financial Time Series Model by Statistical Physics System," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-11, May.
    • Handle: RePEc:hin:jnlaaa:806271
    DOI: 10.1155/2014/806271
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    Cited by:

    1. Jujie Wang & Yinan Liao & Zhenzhen Zhuang & Dongming Gao, 2021. "An Optimal Weighted Combined Model Coupled with Feature Reconstruction and Deep Learning for Multivariate Stock Index Forecasting," Mathematics, MDPI, vol. 9(21), pages 1-20, October.
    2. Adriano Zanin Zambom & Seonjin Kim & Nancy Lopes Garcia, 2022. "Variable length Markov chain with exogenous covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 312-328, March.
    3. Xing, Yani & Wang, Jun, 2019. "Statistical volatility duration and complexity of financial dynamics on Sierpinski gasket lattice percolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 234-247.

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