Curating Independent Machines: How Machine Learning Reshapes Financial Markets
Navn på bevillingshaver
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.