Understanding intra-day price formation process by agent-based financial market simulation: calibrating the extended chiarella model
Author(s)
Gao, Kang
Vytelingum, Perukrishnen
Weston, Stephen
Luk, Wayne
Guo, Ce
Type
Journal Article
Abstract
This article presents XGB-Chiarella, a powerful new approach for deploying agent-based models to generate realistic intra-day artificial financial price data. This approach is based on agent-based models, calibrated by XGBoost machine learning surrogate. Following the Extended Chiarella model, three types of trading agents are introduced in this agent-based model: fundamental traders, momentum traders, and noise traders. In particular, XGB-Chiarella focuses on configuring the simulation to accurately reflect real market behaviours. Instead of using the original Expectation-Maximisation algorithm for parameter estimation, the agent-based Extended Chiarella model is calibrated using XGBoost machine learning surrogate. It is shown that the machine learning surrogate learned in the proposed method is an accurate proxy of the true agent-based market simulation. The proposed calibration method is superior to the original Expectation-Maximisation parameter estimation in terms of the distance between historical and simulated stylised facts. With the same underlying model, the proposed methodology is capable of generating realistic price time series in various stocks listed at three different exchanges, which indicates the universality of intra-day price formation process. For the time scale (minutes) chosen in this paper, one agent per category is shown to be sufficient to capture the intra-day price formation process. The proposed XGB-Chiarella approach provides insights that the price formation process is comprised of the interactions between momentum traders, fundamental traders, and noise traders. It can also be used to enhance risk management by practitioners.
Date Issued
2022-05-01
Date Acceptance
2022-01-12
Citation
Wilmott Magazine, 2022, 2022 (119), pp.22-38
ISSN
1541-8286
Publisher
Wilmott Electronic Media Ltd
Start Page
22
End Page
38
Journal / Book Title
Wilmott Magazine
Volume
2022
Issue
119
Copyright Statement
© 2022 Wilmott Magazine. This is the peer reviewed version of the following article, which has been published in final form at https://wilmott.com/wilmott-magazine-may-2022-issue/. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Identifier
https://wilmott.com/
Publication Status
Published
Date Publish Online
2022-04-12