An agent-based model and detect price manipulation based on intraday transaction data with simulation
Mohammad Zare,
Omid Naghshineh A.,
Erfan Salavati and
Adel Mohammadpour
Applied Economics, 2021, vol. 53, issue 43, 4931-4949
Abstract:
In this article, we propose an agent-based model for LOB markets, and by simulation, we estimate the model’s parameters. This model has two interesting points. First, we divide the data transaction of 1 day into six parts. Second, we detect price manipulation by using intraday transaction data. To detect price manipulation, we simulate the model once without the price manipulator and once with the price manipulator, and then by using some statistical properties such as skewness we find relations to detect price manipulation.
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2021.1912282 (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:applec:v:53:y:2021:i:43:p:4931-4949
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2021.1912282
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().