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Fuzzy entropy complexity and multifractal behavior of statistical physics financial dynamics

机译：统计物理金融动态的模糊熵复杂性和多分术行为

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摘要

The present paper introduces a novel stochastic statistical physics financial system by combining exclusion system with compound Poisson process. The financial system is a model concerning with price fluctuations derived from dissemination of trading attitudes of financial agents and random drastic jumps caused by exogenous economic factors, respectively. Multifractal detrended cross-correlation analysis and fuzzy entropy of simulation dataset are performed. Fractional fuzzy entropy based on fuzzy entropy method and fractional calculus, is also developed to explore nonlinear complexity of the proposed model in the paper. Empirical results display that there are significant multifractality and fractal asymmetry in the proposed model, and the complexity of return series increases when lambda or gamma increases, correspondingly. And same analyses for actual stock market dataset are comparatively investigated. The conclusions reveal that the novel compound dynamics can reproduce various nonlinear behaviors of actual stock markets to a certain extent. (C) 2018 Elsevier B.V. All rights reserved.
机译：本文通过将排斥系统与复合泊松过程结合，介绍了一种新型随机统计物理金融体系。金融体系是一个型号，它有关传播贸易态度的传播态度和随机经济因素造成的随机激烈跳跃的典范。进行了多法反转的跨相关分析和模糊数据集的模糊熵。基于模糊熵方法和分数微积分的分数模糊熵也被开发出探讨纸张中提出的模型的非线性复杂性。经验结果显示，在所提出的模型中存在显着的多重性和分形不对称性，并且当Lambda或伽玛相应地增加时，回报串的复杂性增加。对实际股票市场数据集的分析相对调查。结论表明，新型复合动态可以在一定程度上繁殖实际股票市场的各种非线性行为。 （c）2018年elestvier b.v.保留所有权利。

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