中国物理B ›› 2023, Vol. 32 ›› Issue (8): 88901-088901.doi: 10.1088/1674-1056/accb4a

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A kinetic description of the impact of agent competence and psychological factors on investment decision-making

Chunhua Hu(胡春华)1,† and Hongjing Chen(陈弘婧)2   

  1. 1. School of Economics, Southwest Minzu University, Chengdu 610041, China;
    2. School of Statistics, Chengdu University of Information Technology, Chengdu 610103, China
  • 收稿日期:2023-02-17 修回日期:2023-04-03 接受日期:2023-04-07 发布日期:2023-07-26
  • 通讯作者: Chunhua Hu E-mail:chunhuahu@swun.edu.cn
  • 基金资助:
    Project supported by the Fundamental Research Funds for the Central Universities and Southwest Minzu University (Grant No.2022SJQ002).

A kinetic description of the impact of agent competence and psychological factors on investment decision-making

Chunhua Hu(胡春华)1,† and Hongjing Chen(陈弘婧)2   

  1. 1. School of Economics, Southwest Minzu University, Chengdu 610041, China;
    2. School of Statistics, Chengdu University of Information Technology, Chengdu 610103, China
  • Received:2023-02-17 Revised:2023-04-03 Accepted:2023-04-07 Published:2023-07-26
  • Contact: Chunhua Hu E-mail:chunhuahu@swun.edu.cn
  • Supported by:
    Project supported by the Fundamental Research Funds for the Central Universities and Southwest Minzu University (Grant No.2022SJQ002).

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摘要： The kinetic theory is employed to analyze influence of agent competence and psychological factors on investment decision-making. We assume that the wealth held by agents in the financial market is non-negative, and agents set their own investment strategies. The herding behavior is considered when analyzing the impact of an agent's psychological factors on investment decision-making. A nonlinear Boltzmann model containing herding behavior, agent competence and irrational behavior is employed to investigate investment decision-making. To characterize the agent's irrational behavior, we utilize a value function which includes current and ideal-investment decisions to describe the agent's irrational behavior. Employing the asymptotic procedure, we obtain the Fokker-Planck equation from the Boltzmann equation. Numerical results and the stationary solution of the obtained Fokker-Planck equation illustrate how herding behavior, agent competence, psychological factors, and irrational behavior affect investment decision-making, i.e., herding behavior has both advantages and disadvantages for investment decision-making, and the agent's competence to invest helps the agent to increase income and to reduce loss.

关键词: kinetic theory, investment decisions, Fokker-Planck equation, value function

Abstract: The kinetic theory is employed to analyze influence of agent competence and psychological factors on investment decision-making. We assume that the wealth held by agents in the financial market is non-negative, and agents set their own investment strategies. The herding behavior is considered when analyzing the impact of an agent's psychological factors on investment decision-making. A nonlinear Boltzmann model containing herding behavior, agent competence and irrational behavior is employed to investigate investment decision-making. To characterize the agent's irrational behavior, we utilize a value function which includes current and ideal-investment decisions to describe the agent's irrational behavior. Employing the asymptotic procedure, we obtain the Fokker-Planck equation from the Boltzmann equation. Numerical results and the stationary solution of the obtained Fokker-Planck equation illustrate how herding behavior, agent competence, psychological factors, and irrational behavior affect investment decision-making, i.e., herding behavior has both advantages and disadvantages for investment decision-making, and the agent's competence to invest helps the agent to increase income and to reduce loss.

Key words: kinetic theory, investment decisions, Fokker-Planck equation, value function

中图分类号:  (Economics; econophysics, financial markets, business and management)

  • 89.65.Gh
47.45.Ab (Kinetic theory of gases) 05.20.Dd (Kinetic theory) 05.10.Gg (Stochastic analysis methods)