Nonlinear complexity behaviors of agent-based 3D Potts financial dynamics with random environments

Yani Xing and Jun Wang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 492, issue C, 824-836

Abstract: A new microscopic 3D Potts interaction financial price model is established in this work, to investigate the nonlinear complexity behaviors of stock markets. 3D Potts model, which extends the 2D Potts model to three-dimensional, is a cubic lattice model to explain the interaction behavior among the agents. In order to explore the complexity of real financial markets and the 3D Potts financial model, a new random coarse-grained Lempel–Ziv complexity is proposed to certain series, such as the price returns, the price volatilities, and the random time d-returns. Then the composite multiscale entropy (CMSE) method is applied to the intrinsic mode functions (IMFs) and the corresponding shuffled data to study the complexity behaviors. The empirical results indicate that the 3D financial model is feasible.

Keywords: Microscopic financial price series dynamics; 3D Potts model; Shuffled time series; Random coarse-grained Lempel–Ziv complexity; Composite multiscale entropy; Empirical mode decomposition (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:492:y:2018:i:c:p:824-836

DOI: 10.1016/j.physa.2017.11.013

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