Detecting Financial Market Manipulation with Statistical Physics Tools

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

1 Citation (Scopus)

Abstract

We take inspiration from statistical physics to develop a novel conceptual framework for the analysis of financial markets. We model the order book dynamics as a motion of particles and define the momentum measure of the system as a way to summarise and assess the state of the market. Our approach proves useful in capturing salient financial market phenomena: in particular, it helps detect the market manipulation activities called spoofing and layering. We apply our method to identify pathological order book behaviours during the flash crash of the LUNA cryptocurrency, uncovering widespread instances of spoofing and layering in the market. Furthermore, we establish that our technique outperforms the conventional Z-score-based anomaly detection method in identifying market manipulations across both LUNA and Bitcoin cryptocurrency markets.

Original languageEnglish
Title of host publicationICAIF 2023 - 4th ACM International Conference on AI in Finance
Pages565-573
Number of pages9
ISBN (Electronic)9798400702402
DOIs
Publication statusPublished - 27 Nov 2023

Publication series

NameICAIF 2023 - 4th ACM International Conference on AI in Finance

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