Two new AlgoFinance publications

We are happy to announce the publication of two new AlgoFinance papers.   One is Daniel Souleles’s new article ”Trading Options and the Unattainable Dream: Some Reflections on Semiotic Ideologies” which is published in Signs and Society. Abstract: Over the last few decades there has been a miniature industrial revolution in the buying and selling of securities on capital and derivatives markets. Whereas most trading once happened in open outcry pits or over the phone, trading now occurs primarly via electronic limit order books. Whereas once traders could have little education and find work as a consequence of membership in a local insular network, new financial hires are now the most talented graduates of PhD and master’s programs in the hard sciences and mathematics. Even though these circumstances are well attested, knowing is not enough for some to become this new kind of trader. I suggest that the theory of semiotic ideologies—that is, what grounding assumptions people bring to the process of interpreting signs—can be used to illustrate boundary cases of social change in which people are simply unable to learn enough to adapt to new circumstances in their lives. I will show that even though traders can adopt the appropriate semiotic ideology of markets that their times demand, some of them will never be skilled enough to fully participate. This, in turn, has to do with the nature of change in a capitalist economic system. The article is freely available here.   The other article is by Kristian Bondo Hansen. It is titled ”Model Talk: Calculative Cultures in Quantitative Finance” and is published in Science, Technology & Human Values. Abstract: This paper explores how calculative cultures shape perceptions of models and practices of model use in the financial industry. A calculative culture comprises a specific set of practices and norms concerning data and model use in an organizational setting. Drawing on interviews with model users (data scientists, software developers, traders, and portfolio managers) working in algorithmic securities trading, I argue that the introduction of complex machine-learning models changes the dynamics in calculative cultures, which leads to a displacement of human judgment in quantitative finance. In this paper, I distinguish between three calculative cultures: (1) an idealistic culture of undivided trust in models, (2) a pragmatic culture of skepticism toward model accuracy, and (3) a pragmatic idealist culture of early stage skepticism and implementation and production-phase idealism. Based on the empirical material, the analysis engages with examples of each of the three calculative cultures. The study contributes to the social studies of finance and science and technology studies more broadly by showing how perceptions of models shape and are shaped through model work in data-intensive, computerized finance. The article is freely available here.

Last updated by: Caitlin Welch 05/08/2020