Agent-based modeling simulation analysis on the regulation of institutional investor's encroachment behavior in stock market

Artikel

Purpose: This study explores the effective regulation of institutional investor's encroachment behavior in stock market. Given the theoretical and practical importance, the present study examines the effect of the self-adaptive regulation strategy (adjusting the regulation factors such as punishment and the probability of investigating successfully in time) for the sake of the small & medium-sized investor protection. Design/methodology/approach: This study was carried out through game theory and agent-based modeling simulation. Firstly, a dynamic game model was built to search the core factors of regulation and the equilibrium paths. Secondly, an agent-based modeling simulation model was built in Swarm to extend the game model. Finally, a simulation experiment (using virtual parameter values) was performed to examine the effect of regulation strategy obtained form game model. Findings: The results of this study showed that the core factors of avoiding the institutional investor's encroachment behavior are the punishment and the probability of investigating successfully of the regulator. The core factors embody as the self-adaptability and the capability of regulator. If the regulator can adjust the regulation factors in time, the illegal behaviors will be avoided effectively. Research limitations/implications: The simulation experiment in this paper was performed with virtual parameter values. Although the results of experiment showed the effect of self-adaptive regulation, there are still some differences between simulation experiment and real market situation. Originality/value: The purpose of this study is to investigate an effective regulation strategy of institutional investor's encroachment behavior in stock market in order to maintain market order and protect the benefits of investors. Base on the game model and simulation model, a simulation experiment was preformed and the result showed that the self-adaptive regulation would be effective. This study applied game theory and agent-based modeling simulation to the research of financial regulation, and extended the application field of these two methods.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 7 ; Year: 2014 ; Issue: 2 ; Pages: 434-447 ; Barcelona: OmniaScience

Classification and Topics

• Classification: Management
• Subject: institutional investor ; agent-based modeling ; simulation ; regulation ; self-adaptability

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Li Yang ; Liu, Shuo
• Event: Veröffentlichung
• (who): OmniaScience
• (where): Barcelona
• (when): 2014

Further information

• DOI: doi:10.3926/jiem.1024
• Handle: http://hdl.handle.net/10419/188610
• Last update: 10.03.2025, 11:44 AM CET