A Machine Learning Attack on Illegal Trading

50 Pages Posted: 21 Jan 2021 Last revised: 6 Dec 2022

See all articles by Robert James

Robert James

The University of Sydney

Henry Leung

University of Sydney Business School; Financial Research Network (FIRN)

Artem Prokhorov

University of Sydney Business School; Saint Petersburg State University - Center for Econometrics and Business Analytics (CEBA); University of Montreal - Centre interuniversitaire de recherche en économie quantitative (CIREQ)

Date Written: October 31, 2020

Abstract

We design an adaptive framework for the detection of illegal trading behavior. Its key
component is an extension of a pattern recognition tool, originating from the field of signal
processing and adapted to modern electronic systems of securities trading. The new method
combines the flexibility of dynamic time warping with contemporary approaches from extreme
value theory to explore large-scale transaction data and accurately identify illegal trading patterns.
Importantly, our method does not need access to any confirmed illegal transactions for
training. We use a high-frequency order book dataset provided by an international investment firm to show that the method achieves remarkable improvements over alternative approaches in
the identification of suspected illegal insider trading cases.

Keywords: Market Manipulation, Dynamic Time Warping, Market Microstructure, Machine Learning, Limit Order Books

JEL Classification: C02, C4, G14

Suggested Citation

James, Robert and Leung, Henry and Prokhorov, Artem, A Machine Learning Attack on Illegal Trading (October 31, 2020). Journal of Banking and Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3722391 or http://dx.doi.org/10.2139/ssrn.3722391

Robert James (Contact Author)

The University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

Henry Leung

University of Sydney Business School ( email )

402, H69
The University of Sydney
Sydney, NSW 2006
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Artem Prokhorov

University of Sydney Business School ( email )

Cnr. of Codrington and Rose Streets
Sydney, NSW 2006
Australia

Saint Petersburg State University - Center for Econometrics and Business Analytics (CEBA) ( email )

7-9, Universitetskaya nab.
Saint Petersburg, 199034
Russia

University of Montreal - Centre interuniversitaire de recherche en économie quantitative (CIREQ) ( email )

3150, rue Jean-Brillant
Montreal, QC H3T 1N8
Canada

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