A Platform for Stock Market Simulation with Distributed Agent-Based Modeling

Author(s):  
Chunyu Wang ◽  
Ce Yu ◽  
Hutong Wu ◽  
Xiang Chen ◽  
Yuelei Li ◽  
...  
2000 ◽  
Vol 03 (01n04) ◽  
pp. 451-461 ◽  
Author(s):  
Eric Bonabeau

Agent-based simulation is a powerful simulation modeling technique that has seen a number of applications in the last five years, including applications to real-world business problems. In this chapter I introduce agent-based simulation and review three applications to business problems: a theme park simulation, a stock market simulation, and a bankwide simulation.


2015 ◽  
Vol 5 (4) ◽  
pp. 257-270 ◽  
Author(s):  
Guocheng Wang ◽  
Shiguo Zhang

Abstract One of the most important advantage of ABM (Agent-Based Modeling) used in social and economic calculation simulation is that the critical behavioral characteristics of the micro agents can be deeply depicted by the approach. Why, what and how real behavior(s) should be incorporated into ABM and is it appropriate and effective to use ABM with HSCA collaboration and micro-macro link features for complex economy/finance analysis? Through deepening behavioral analysis and using computational experimental methods incorporating HS (Human Subject) into CA (Computational Agent), which is extended ABM, based on the theory of behavioral finance and complexity science as well, we constructed a micro-macro integrated model with the key behavioral characteristics of investors as an experimental platform to cognize the conduction mechanism of complex capital market and typical phenomena in this paper, and illustrated briefly applied cases including the internal relations between impulsive behavior and the fluctuation of stock’s, the asymmetric cognitive bias and volatility cluster, deflective peak and fat-tail of China stock market.


2015 ◽  
Vol E98.D (10) ◽  
pp. 1727-1735 ◽  
Author(s):  
Ce YU ◽  
Xiang CHEN ◽  
Chunyu WANG ◽  
Hutong WU ◽  
Jizhou SUN ◽  
...  

Author(s):  
Thomas Plieger ◽  
Thomas Grünhage ◽  
Éilish Duke ◽  
Martin Reuter

Abstract. Gender and personality traits influence risk proneness in the context of financial decisions. However, most studies on this topic have relied on either self-report data or on artificial measures of financial risk-taking behavior. Our study aimed to identify relevant trading behaviors and personal characteristics related to trading success. N = 108 Caucasians took part in a three-week stock market simulation paradigm, in which they traded shares of eight fictional companies that differed in issue price, volatility, and outcome. Participants also completed questionnaires measuring personality, risk-taking behavior, and life stress. Our model showed that being male and scoring high on self-directedness led to more risky financial behavior, which in turn positively predicted success in the stock market simulation. The total model explained 39% of the variance in trading success, indicating a role for other factors in influencing trading behavior. Future studies should try to enrich our model to get a more accurate impression of the associations between individual characteristics and financially successful behavior in context of stock trading.


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