Noise traders in an agent-based artificial stock market

Abstract

This paper investigates whether noise traders can survive in the long run and how they influence financial markets by proposing an agent-based artificial stock market, as one simulation model of computational economics. This market contains noise traders, informed and uninformed traders. Informed and uninformed traders can learn from information by using Genetic Programming, while noise traders cannot. The system is first calibrated to real financial markets by replicating several stylized facts. We find that noise traders cannot survive or they just transform to other kind of traders in the long run, and they increase market volatility, price distortion, noise trader risk, and trading volume in the market. However, regulation intervention, e.g., price limits, transaction tax and longer settlement cycle, can affect noise trader’s surviving period and their influence on markets.

Publication DOI: https://doi.org/10.1007/s10479-023-05528-7
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Funding Information: The authors would like to thank Professor Victor Chang for the research support from VC Research (VCR 0000146) and acknowledge the support of Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Republic of China [award n
Additional Information: Funding The authors would like to thank Professor Victor Chang for the research support from VC Research (VCR 0000146) and acknowledge the support of Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Republic of China [award number: 22YJC790161]. Copyright © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Uncontrolled Keywords: Agent-based modeling,Computational economics,Noise traders,Price limits,Risk and volatility dynamics,Simulation models,The settlement cycle,Transaction tax,General Decision Sciences,Management Science and Operations Research
Publication ISSN: 1572-9338
Last Modified: 07 Oct 2024 07:51
Date Deposited: 31 Aug 2023 15:57
Full Text Link:
Related URLs: https://link.sp ... 479-023-05528-7 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-08-07
Published Online Date: 2023-08-07
Accepted Date: 2023-07-09
Authors: Dai, Xiaoting
Zhang, Jie
Chang, Victor (ORCID Profile 0000-0002-8012-5852)

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record