The Stack Inversion: On Algo-Centrism and the Complex Architecture of Automated Financial Securities Trading Systems

Abstract

In this article, I argue that devoting analytical attention to the natively technical concept of “the stack” can help re-sensitize studies of algorithms in Science and Technology Studies (STS) and adjacent fields to the depths of interdependence between different layers and elements of computational systems. Inspired by Bowker and Star's three-decades old methodological gestalt-switch concept of “infrastructural inversion,” I propose a “stack inversion” that seeks to mitigate “algo-centrism”—an overemphasis on algorithms and algorithmic action—by shifting focus to the relational practices and material politics of “stacking.” To demonstrate the analytical value of this stack inversion, I examine and discuss how software developers, data scientists, computer engineers, and other so-called “quants” working in the financial industry talk about and reflect on their own practices of devising and operating automated trading systems. The empirical material I analyze consists of 182 interviews conducted in the US and Europe with people occupying a range of different roles in financial securities trading and investment management. The article contributes to the burgeoning STS-informed literature on algorithms by proposing a conceptual-analytic move that allows for reflexive engagement with the material politics, opacities, and dependencies created in and around automated computational systems.