Order book regulatory impact on stock market quality: a multi-agent reinforcement learning perspective
Johann Lussange and
Boris Gutkin
Additional contact information
Johann Lussange: LNC2 - Laboratoire de Neurosciences Cognitives & Computationnelles - DEC - Département d'Etudes Cognitives - ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INSERM - Institut National de la Santé et de la Recherche Médicale
Boris Gutkin: LNC2 - Laboratoire de Neurosciences Cognitives & Computationnelles - DEC - Département d'Etudes Cognitives - ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INSERM - Institut National de la Santé et de la Recherche Médicale
Working Papers from HAL
Abstract:
Recent technological developments have changed the fundamental ways stock markets function, bringing regulatory instances to assess the benefits of these developments. In parallel, the ongoing machine learning revolution and its multiple applications to trading can now be used to design a next generation of financial models, and thereby explore the systemic complexity of financial stock markets in new ways. We here follow on a previous groundwork, where we designed and calibrated a novel agent-based model stock market simulator, where each agent autonomously learns to trade by reinforcement learning. In this Paper, we now study the predictions of this model from a regulator's perspective. In particular, we focus on how the market quality is impacted by smaller order book tick sizes, increasingly larger metaorders, and higher trading frequencies, respectively. Under our model assumptions, we find that the market quality benefits from the latter, but not from the other two trends.
Keywords: Trading and Market Microstructure (q-fin.TR); Computational Finance (q-fin.CP); Pricing of Securities (q-fin.PR); FOS: Economics and business (search for similar items in EconPapers)
Date: 2023-02
Note: View the original document on HAL open archive server: https://hal.science/hal-04273903v1
References: Add references at CitEc
Citations:
Downloads: (external link)
https://hal.science/hal-04273903v1/document (application/pdf)
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:hal:wpaper:hal-04273903
DOI: 10.48550/arXiv.2302.04184
Access Statistics for this paper
More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().