Co-evolutionary multi-agent-based modeling of artificial stock market by using the GP approach

Author

Chen, Xiaorong

Author_Institution

Graduate Sch. of Econ., Kyushu Univ., Fukuoka, Japan

fYear

2003

fDate

20-23 March 2003

Firstpage

159

Lastpage

165

Abstract

The paper deals with a multi-agent-based architecture for an artificial stock market. We attempt to add more heterogeneity to agents. Specifically, in this architecture rational agents prefer forecast equation models or simple trading rules to support their decision making, and own their own individual base or just learn from a public base. Besides these rational agents, a type of irrational agent is also defined. We focus on applying the GP approach to model cognitive behavior of adaptive agents. Time series generated from this multi-agent-based artificial stock market are demonstrated to replicate some features and compared with empirical studies.

Keywords

cognitive systems; forecasting theory; genetic algorithms; multi-agent systems; stock markets; time series; GP approach; adaptive agents; agent heterogeneity; artificial stock market; co-evolutionary multi-agent-based modeling; cognitive behavior modelling; decision making; forecast equation models; genetic programming; irrational agents; multi-agent-based architecture; multi-agent-based artificial stock market; multi-agent-based modeling; public base; rational agents; simple trading rules; time series; Artificial intelligence; Computational modeling; Decision making; Economic forecasting; Equations; Genetic programming; Power generation economics; Power system modeling; Predictive models; Stock markets;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Financial Engineering, 2003. Proceedings. 2003 IEEE International Conference on

Print_ISBN

0-7803-7654-4

Type

conf

DOI

10.1109/CIFER.2003.1196256

Filename

1196256