READ ME File For Dataset in support of thesis 'The practical consequences of the transformation of the UK fixed income, currency, and commodity markets (“FICC”) into algorithmic realms for the management of conduct risk.'

Dataset DOI: 10.5258/SOTON/D3271

ReadMe Author: Alexander Conrad Culley, University of Southampton ORCID ID 000-0002-0560-9443

This dataset supports the thesis entitled 'The practical consequences of the transformation of the UK fixed income, currency, and commodity markets (“FICC”) into algorithmic realms for the management of conduct risk.'
AWARDED BY: Univeristy of Southampton
DATE OF AWARD: 2024

DESCRIPTION OF THE DATA
[This should include a detailed description of the data, how it was collected/created, any specialist software needed to view the data]

This dataset contains: Transcripts of semi-structured interviews conducted with practitioners in the financial services industry.

Date of data collection: Spring-Summer 2021

Information about geographic location of data collection: Data collected by from the United Kingdom using Microsoft Teams. Some participants were based overseas. 

Licence:
CC BY

Related projects/Funders:
NIL

Related publication:

CULLEY, A. 2024. The practical consequences of the transformation of the UK fixed income, currency, and commodity markets (“FICC”) into algorithmic realms for the management of conduct risk. Doctoral thesis. 

CULLEY, A. 2021. Identifying and mitigating ‘conduct risk’ in algorithmic FICC trading. Journal of Financial Compliance, 4(3), 267-281.

CULLEY, A. 2023b. Is employees' understanding of conduct risk aligned with values espoused in their employers' public statements? Journal of Financial Compliance, 7(1), 82-100.

CULLEY, A. C. 2022. Does the deployment of algorithms combined with direct electronic access increase conduct risk? Evidence from the LME. Journal of Financial Regulation and Compliance, 31(2), 220-236.

CULLEY, A. C. 2023c. Insights into UK investment firms’ efforts to comply with MiFID II RTS 6 that governs the conduct of algorithmic trading. Journal of Financial Regulation and Compliance, 31(5), 607-629.

Date that the file was created: October, 2024