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

Authored by Binge Cui, Huaiqing Wang, Kang Ye, Jiaqi Yan

Date Published: 2012-08

DOI: 10.1016/j.eswa.2012.02.018

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Pseudocode

Model Code URLs: Model code not found

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. (C) 2012 Elsevier Ltd. All rights reserved.

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Intelligent agent Short selling Stock simulation Trading strategy