Curating Independent Machines: How Machine Learning Reshapes Financial Markets

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Christian Borch

Titel

Professor

Institution

University of Copenhagen

Beløb

DKK 1,058,697

År

2022

Bevillingstype

Monograph Fellowships

Resumé

The financial markets have been widely automated during the past few decades, and most orders to buy or sell stocks and other securities are now placed by fully automated algorithms. These automated trading systems used to be “human-defined,” meaning that the strategies they pursued were conceived of by humans. Since the mid-2010s, however, a new type of algorithmic systems has become popular—automated trading systems based on so-called machine learning techniques. These systems are designed to generate their own strategies independently of human input. The aim of this project is (1) to examine this transformation toward machine-learning-based automated trading and its consequences for market risk as well as (2) to analyze its broader sociological implications.

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