A guest post from Nathan Coombs who is an incoming Leverhulme Early Career Research Fellow at the University of Edinburgh. He edits the Journal of Critical Globalisation Studies, and is the author of the forthcoming book, Politics of the Event: From Marxism to Contemporary French Theory (Edinburgh University Press, 2015). His current research interests are in financial algorithms and financial regulation. He can be contacted at n.coombs (at) fastmail.co.uk
Over the last decade, scholars have become increasingly interested in what we do when we make use of models and simulations. An emerging consensus – often legitimated through reference to Bruno Latour’s Actor-Network Theory – is that mathematical models and computer simulations are not passive tools but rather a material force in their own right. Agents may employ such technologies in order to achieve pre-determined ends, but the technologies themselves have an effectivity that exceeds their users’ intentions, and set in place path-dependencies that serve to proscribe the range of political and economic possibility.
This concern with the politics of technology cuts across multiple disciplines including Sociology, Communication Studies, International Relations, International Political Economy, and Management Studies. However, the Social Studies of Finance (SSF) has perhaps gone furthest in exploring the practical implications of modelling and simulation technologies. Applying Austinian and Barnesian notions of performativity, researchers in this field have sought to grasp the way in which economic models shape markets, and to dig into the mathematical and technical details that underpin this process.
Donald MacKenzie’s book An Engine, Not a Camera (2008) is exemplary of this approach, and a common point of reference for scholars in SSF and all the aforementioned disciplines. In his analysis of the development and uptake of the Black-Scholes option-pricing model in the 1970s, MacKenzie aims to show how the model’s employment of the efficient market hypothesis – where stock prices are considered to accurately reflect their risk – led to a period in which the pricing of options came to reflect that predicted by the model. The point of MacKenzie’s analysis is not to endorse the neoclassical economic assumptions codified in the model. Rather, it is to point out how models serve to socially facilitate evaluation practices in the face of complexity, uncertainty, and epistemological opacity. On this basis a model can also contribute to financial instability when it is both widely employed and based on assumptions that are confounded by ‘real world’ contingencies.