Biased trader model and analysis of financial market dynamics

Article type: Research Article

Authors: Kilicay-Ergin, Nil^{a; *} | Enke, David^b | Dagli, Cihan^b

Affiliations: [a] Penn State University, Great Valley School of Graduate Professional Studies, Malvern, PA, USA | [b] Missouri University of Science and Technology, Department of Engineering Management and Systems Engineering, Rolla, MO, USA

Correspondence: [*] Corresponding author. E-mail: nhe2@psu.edu

Abstract: This study focuses on various trader behaviors that affect market dynamics. In particular, the effects of a covering mechanism, learning mechanism and bias mechanism are analyzed through agent-based financial market model. An XCS classifier system is used to model trader learning mechanism. A trader model is proposed to formulate a trader decision model that combines bias mechanisms with learning mechanisms. The results reveal that biased traders survive under evolving markets and affect price dynamics. The model contributes to understanding the market behavior and potential sources of deviation from efficient market equilibrium.

Keywords: Agent based modeling, biased decision making, financial markets, learning classifier systems

DOI: 10.3233/KES-2011-0235

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 16, no. 2, pp. 99-116, 2012