The Use and Promises of Machine Learning in Financial Markets: From Mundane Practices to Complex Automated Systems

Taylor Spears, Kristian Bondo Hansen

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Abstract

This chapter examines the use of machine learning (ML) in financial markets and argues that the adoption of ML into finance is bringing to light new issues that have traditionally fallen outside the purview of the sociology of finance and financial modeling. Furthermore, the chapter argues that the use of ML methods may be facilitating a cultural and infrastructural alignment between big tech and financial services through both the adoption of open source software within finance and the dependence of ML on large-scale cloud infrastructures. Accordingly, the chapter identifies two potential directions for future work on the sociology of financial machine learning: a “horizontal” expansion to account for the ways machine learning is being used across financial institutions, and a “vertical” deepening that investigates the infrastructures upon which ML systems are developed and deployed, and how they are shaping financial institutions and markets.
Original languageEnglish
Title of host publication The Oxford Handbook of the Sociology of Machine Learning
EditorsChristian Borch, Juan Pablo Pardo-Guerra
Number of pages18
Place of PublicationOxford
PublisherOxford University Press
Publication date2023
ISBN (Print)9780197653609
ISBN (Electronic)9780197653630
DOIs
Publication statusPublished - 2023
SeriesOxford Handbooks

Keywords

  • Financial markets
  • Machine learning
  • Modeling culture
  • Sociology of finance
  • Automated system
  • Infrastructure studies

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