The AlgoFinance research project has led to the following publications:
Christian Borch and Bo Hee Min (forthcoming) 'Toward a sociology of machine-learning explainability: Human-machine interaction in deep-neural-network-based automated trading', Big Data & Society.
Christian Borch and Bo Hee Min (2022) 'Machine learning and social action in markets: Analyzing the shift from first- to second-generation automated trading', Economy and Society https://doi.org/10.1080/03085147.2022.2050088.
Hansen, Kristian Bondo and Christian Borch (2022) 'Alternative data and sentiment analysis: prospecting non-standard data in machine learning-driven finance', Big Data & Society https://doi.org/10.1177/20539517211070701.
Souleles, Daniel (2021) 'Why would you buy an electric car on Jetski Friday? Or, a critique of financial markets from an options trading room', Finance and Society 7(2): 113–129: https://doi.org/10.2218/finsoc.v7i2.6628.
Min, Bo Hee and Christian Borch (2021) 'Systemic Failures and Organizational Risk Management in Algorithmic Trading: Normal Accidents and High Reliability in Financial Markets', Social Studies of Science, https://doi.org/10.1177/03063127211048515.
Borch, Christian (forthcoming) 'Algorithmic Mimicry and Mimicry in Nature', The Manipulator.
Borch, Christian (2020) 'Corona, markedssmitte og sociale laviner', pp. 41–53 in Ole B. Jensen and Nikolaj Schultz (eds) Det epidemiske samfund. Copenhagen: Hans Reitzels Forlag.
Hansen, Kristian Bondo and Christian Borch (2022) 'Alternative data and sentiment analysis: prospecting non-standard data in machine learning-driven finance', Big Data & Society blog, January 21, 2022: https://bigdatasoc.blogspot.com/.