粒子群算法在非线性金融风险模型中的应用

doi:10.3969/j.issn.1000-1565.2018.03.001

河北大学学报(自然科学版) ›› 2018, Vol. 38 ›› Issue (3): 225-231.DOI: 10.3969/j.issn.1000-1565.2018.03.001

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粒子群算法在非线性金融风险模型中的应用

李博^1,2,田瑞兰³,张炜华 ³,刘国欣^1,3

收稿日期:2017-10-15 出版日期:2018-05-25 发布日期:2018-05-25
通讯作者: 刘国欣(1960—),男,河北任丘人,河北工业大学教授,博士生导师,主要从事风险理论、概论极限定理等方向的研究.E-mail:ssq-124@163.com
作者简介:李博(1987—),男,湖北英山人,河北工业大学在读博士研究生,主要从事金融风险管理研究. E-mail:159985271@qq.com
基金资助:
国家自然科学基金资助项目(11471218);河北省高等学校科学技术研究项目(ZD20131017)

Application of particle swarm optimization in a class of nonlinear financial risk system

LI Bo^1,2,TIAN Ruilan³,ZHANG Weihua³, LIU Guoxin^1,3

1. School of Economics and Management, Hebei University of Technology, Tianjin 300000, China; 2. Investment Banking and Asset Management Department, Bank of China, Hebei Branch, Shijiazhuang 050000, China; 3. School of Economics and Management, Shijiazhuang TiedaoUniversity, Shijiazhuang 050043, China

Received:2017-10-15 Online:2018-05-25 Published:2018-05-25

摘要/Abstract

摘要： 在非线性动力学混沌与分岔理论的基础上引入粒子群算法,对如何选择最优参数配比以保证金融系统的平稳运行及最大程度的降低系统总风险值进行探讨.结果表明,所选取的理论与研究方法能够有效寻找最优参数配比,并对相关机构进行调控具有一定的理论指导意义.

关键词: 金融风险系统, 非线性动力学, 混沌与分岔, 粒子群算法

Abstract: Maintaining stable operation of financial system and reducing financial risk is a focus studied by economical researchers. Based on the nonlinear chaos and bifurcation theory, this paper introduces the particle swarm optimization and discuss how to choose the optimal parameter ratio to ensure the smooth operation of the financial system and the maximum reduction of the total risk value of the system. The results show that the theory and methods selected in this paper can effectively find the optimal parameter ratio and have certain theoretical significance for the regulation of related institutions.

Key words: financial risk system, nonlinear dynamics, chaos and bifurcation, particle swarm optimization(PSO)

中图分类号:

F830

李博,田瑞兰,张炜华 ,刘国欣. 粒子群算法在非线性金融风险模型中的应用[J]. 河北大学学报(自然科学版), 2018, 38(3): 225-231.

LI Bo,TIAN Ruilan,ZHANG Weihua, LIU Guoxin. Application of particle swarm optimization in a class of nonlinear financial risk system[J]. Journal of Hebei University (Natural Science Edition), 2018, 38(3): 225-231.

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粒子群算法在非线性金融风险模型中的应用

Application of particle swarm optimization in a class of nonlinear financial risk system

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