Identifying and mitigating ‘conduct risk’ in algorithmic FICC trading

Alexander Culley
Additional contact information
Alexander Culley: Chartered Fellow of the Chartered Institute of Securities and Investments, UK

Journal of Financial Compliance, 2021, vol. 4, issue 3, 267-281

Abstract: From 31st March, 2021, pursuant to the Senior Managers and Certification Regime (SMCR), British investment firms are required to have performed their first fitness and propriety assessments of persons overseeing the deployment of trading algorithms. Inherent in this requirement is an assumption that natural persons will continue to play the leading role in algorithmic design and calibration for the foreseeable future. Popular non-fiction works), however, are evocative of a future dominated by artificial intelligence with significant levels of autonomy. Building on his recent review of the extant literature concerning conduct risks and their mitigation in algorithmic trading (AT) firms (Culley, 2020), the author proposes a research agenda to assess if initiatives such as the SMCR are considerate of new conduct risks that could emerge in the machine age. Favouring a pragmatic epistemology that the author asserts is consistent with the Financial Conduct Authority’s (FCA) own approach to regulation, the author suggests three possible research strategies (case studies, mixed methods and action research) that could be employed by researchers interested in this topic, before settling on what the author considers to be the most suitable strategy for his own study. In addition, the author provides details on the primary data (elite interviews, focus groups) and secondary data collection techniques that will be utilised, together with an insight into appropriate sampling and data analysis methods. While the author plans to use this research agenda in the context of AT in the fixed income, currencies and commodities markets because of the dearth of studies in this area, it is hoped that it will inspire other scholars to conduct examinations into the conduct risks posed by the automation so that both policymakers and firms can make informed decisions regarding their mitigation in the future.

Keywords: conduct risk; algorithmic trading; high-frequency trading; FICC markets; artificial intelligence; FCA; SMCR (search for similar items in EconPapers)
JEL-codes: E5 G2 K2 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/6274/download/ (application/pdf)
https://hstalks.com/article/6274/ (text/html)
Requires a paid subscription for full access.

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:aza:jfc000:y:2021:v:4:i:3:p:267-281

Access Statistics for this article

More articles in Journal of Financial Compliance from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().