Regulation of Algorithmic Trading: Frameworks for Human Supervision and Direct Market Interventions

European Business Law Review

29 Pages Posted: 9 Feb 2021 Last revised: 18 Jan 2022

See all articles by Joseph Lee

Joseph Lee

School of Law, University of Manchester

Lukas Schu

affiliation not provided to SSRN

Date Written: January 14, 2021

Abstract

This paper identifies the regulatory gaps that currently exist in algorithmic trading and provides a framework for machine learning regulation in finance. It compares the regulation of algorithmic trading in the capital markets by both human supervision and direct market intervention in the UK, the EU and the US to identify techniques they have in common, as well as local differences. Section II sets out what algorithmic trading is, how it is defined, which of its functions have a positive effect and which are negative for risk and impact. Section III examines how trading risks can be managed by human supervision. Section IV looks at how direct market intervention can mitigate the risks of algorithmic trading, focusing on the circuit breaker requirement. Finally, the liability of the parties involved (traders, firms, and trading venues) are examined and the possible enforcement actions that regulators may take are set out.

Keywords: algorithms, high frequency trading, machine learning, financial regulation, MIFIDII, ESMA, FCA, SEC, circuit breaker, systemic risk

JEL Classification: K22

Suggested Citation

Lee, Joseph and Schu, Lukas, Regulation of Algorithmic Trading: Frameworks for Human Supervision and Direct Market Interventions (January 14, 2021). European Business Law Review , Available at SSRN: https://ssrn.com/abstract=3765882 or http://dx.doi.org/10.2139/ssrn.3765882

Joseph Lee (Contact Author)

School of Law, University of Manchester ( email )

Oxford Road
Manchester M13 9PL, M139PL
United Kingdom

Lukas Schu

affiliation not provided to SSRN

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