Intelligent agent-assisted adaptive order simulation system in the artificial stock market

  • Authors:

  • Binge Cui;Huaiqing Wang;Kang Ye;Jiaqi Yan

  • Affiliations:

  • College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China;South University of Science and Technology of China, Shenzhen, Guangdong, China;Shanghai Stock Exchange, Shanghai, China;Department of Information Systems, City University of Hong Kong, Kowloon, Hong Kong, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

Quantified Score

Hi-index 12.05

Visualization

Abstract

Agent-based computational economics (ACE) has received increased attention and importance over recent years. Some researchers have attempted to develop an agent-based model of the stock market to investigate the behavior of investors and provide decision support for innovation of trading mechanisms. However, challenges remain regarding the design and implementation of such a model, due to the complexity of investors, financial information, policies, and so on. This paper will describe a novel architecture to model the stock market by utilizing stock agent, finance agent and investor agent. Each type of investor agent has a different investment strategy and learning method. A prototype system for supporting stock market simulation and evolution is also presented to demonstrate the practicality and feasibility of the proposed intelligent agent-based artificial stock market system architecture.