EconPapers    
Economics at your fingertips  
 

Agent-based artificial financial market with evolutionary algorithm

Yan Chen, Zezhou Xu and Wenqiang Yu

Economic Research-Ekonomska Istraživanja, 2022, vol. 35, issue 1, 5037-5057

Abstract: In traditional financial studies, existing approaches are unable to address increasingly complex problems. In this paper, an artificial financial market is proposed, in accordance with the adaptation market hypothesis, using artificial intelligence algorithms. This market includes three types of agents with different investments and risk preferences, representing the heterogeneity of traders. Genetic network programming is combined with a state-action-reward-state-action (SARSA)(λ) algorithm for designing the market to reflect the adaptation of technical agents. A pricing mechanism is taken into consideration, based on the auction mechanism of the Chinese securities market. The characteristics of price time series are analyzed to determine whether excessive volatility exists in four different markets. Explanations are provided for the corresponding financial phenomena considering the hypotheses under the proposed novel artificial financial market.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/1331677X.2021.2021098 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:reroxx:v:35:y:2022:i:1:p:5037-5057

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rero20

DOI: 10.1080/1331677X.2021.2021098

Access Statistics for this article

Economic Research-Ekonomska Istraživanja is currently edited by Marinko Skare

More articles in Economic Research-Ekonomska Istraživanja from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:reroxx:v:35:y:2022:i:1:p:5037-5057