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.
- Borch, Christian (2022) 'Financial Contagion in an Age of COVID-19: On Biological, Human, and Algorithmic Mimesis', CounterText 8(1): 206–226: https://www.euppublishing.com/doi/abs/10.3366/count.2022.0263.
- 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.
- Christian Borch (2022) 'Machine learning, knowledge risk, and principal-agent problems in automated trading', Technology in Society 68: https://doi.org/10.1016/j.techsoc.2021.101852.
- 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.
- Borch, Christian (2021) 'Machine learning and social theory: Collective machine behaviour in algorithmic trading', European Journal of Social Theory, https://doi.org/10.1177/13684310211056010.
- 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.
- Souleles, Daniel (2021) 'How to think about people who don’t want to be studied: Further reflections on studying up', Critique of Anthropology 41(3): 206–226. https://doi.org/10.1177/0308275X211038045.
- Hansen, Kristian Bondo and Christian Borch (2021) 'The absorption and multiplication of uncertainty in machine-learning-driven finance', British Journal of Sociology 72(4): 1015–1029.https://onlinelibrary.wiley.com/doi/full/10.1111/1468-4446.12880.
- Hansen, Kristian Bondo (2021) 'Financial Contagion: Problems of proximity and connectivity in financial markets', Journal of Cultural Economy 14(4): 388–402. https://www.tandfonline.com/doi/full/10.1080/17530350.2021.1879211.
- Hansen, Kristian Bondo (2021) 'Model Talk: Calculative Cultures in Quantitative Finance', Science, Technology & Human Values 46(3): 600–627.https://doi.org/10.1177/0162243920944225.
- Hansen, Kristian Bondo (2020) 'The Virtue of Simplicity: On machine learning models in algorithmic trading', Big Data & Society 7(1) https://doi.org/10.1177/2053951720926558.
- Souleles, Daniel (2020) 'Trading Options and the Unattainable Dream: Some Reflections on Semiotic Ideologies', Signs and Society 8(2) Spring: 243-261. https://doi.org/10.1086/707315.
- Souleles, Daniel (2019) 'The distribution of ignorance on financial markets', Economy and Society 48(4): 510–531. https://doi.org/10.1080/03085147.2019.1678263.
- Borch, Christian (2020) Social Avalanche: Crowds, Cities and Financial Markets. Cambridge: Cambridge University Press. https://www.cambridge.org/dk/academic/subjects/sociology/social-theory/social-avalanche-crowds-cities-and-financial-markets?format=PB
- 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/.
- Hansen, Kristian Bondo (2020) 'The virtue of simplicity: On machine learning models in algorithmic trading', Big Data & Society, 21 May, 2020: http://bigdatasoc.blogspot.com/2020/05/the-virtue-of-simplicity-on-machine.html.
- Borch, Christian (2020) 'Ten Years after the Flash Crash, We Still Need to Make Algorithmic Trading Less Risky. Can Culture Save The Day?', socializing finance, May 6, 2020: https://socfinance.wordpress.com/2020/05/06/ten-years-after-the-flash-crash-we-still-need-to-make-algorithmic-trading-less-risky-can-culture-save-the-day/.
- Borch, Christian (2020) 'Financial trading bots have fascinating similarities to people – we need to learn from them', The Conversation, January 16, 2020: https://theconversation.com/financial-trading-bots-have-fascinating-similarities-to-people-we-need-to-learn-from-them-130015.
- Borch, Christian (2020) 'Crowd Behaviour in Financial Markets, from the Hong Kong Protests to Algorithmic Trading', FifteenEigthyFour, January 9, 2020: http://www.cambridgeblog.org/2020/01/crowd-behaviour-in-financial-markets-from-the-hong-kong-protests-to-algorithmic-trading/.
Last updated by: Caitlin Welch 13/06/2022
News
Articles in Big Data & Society, Technology in Society, and European Journal of Social Theory
Kristian and Christian publish new paper on machine learning