Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market

Qixuan Luo (), Shijia Song () and Handong Li ()
Additional contact information
Qixuan Luo: Beijing Normal University
Shijia Song: Beijing Normal University
Handong Li: Beijing Normal University

Computational Economics, 2023, vol. 62, issue 4, No 13, 1750 pages

Abstract: Abstract The widespread application of algorithmic trading (AT) will have a lasting and profound effect on the financial market. This paper uses the multi-agent model to construct a multi-asset artificial stock market that can trade multiple assets simultaneously. The simulation results show that the multi-asset market can reproduce the stylized facts of the actual stock market. Then, the effects of an institutional trader using the four different AT strategies on the market containing the three risky assets are studied. The results are as follows: (1) The two types of implementation shortfall (IS) strategies can help the institutional trader achieve the smaller total liquidation costs; (2) the liquidation behavior of the institutional trader using the different strategies has significant negative impacts on the most market indicators of the liquidity, the volatility, the price discovery efficiency and the long memory of absolute returns on the whole, while the individual market indicators are improved in a few cases; (3) compared with the other three strategies, the portfolio IS strategy considering both the optimal liquidation time and the correlation of the stocks is better in terms of the execution effects and the impacts on the market.

Keywords: Artificial stock market; Multi-agent model; Algorithmic trading; Portfolio (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-022-10316-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:62:y:2023:i:4:d:10.1007_s10614-022-10316-9

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-022-10316-9

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().