A Material Political Economy: The High-Frequency Trading of US Shares
Ultrafast, automated ‘high-frequency trading’ or HFT now makes up around half of all US share trading. Drawing upon interviews with 54 high-frequency traders, MacKenzie’s talk will examine the ‘signals’ (patterns of data) that shape how HFT algorithms interact. He will argue that despite the high-technology glamour of autonomous, algorithmic economic agents, their behaviour is shaped by ‘political economy’ struggles — some with their origins in the 1970s — about how shares and other financial instruments should be traded.
The underlying theoretical goal is to integrate the materialism of actor-network theory with the emphasis on meso-level conflict in field-theoretic economic sociology. The talk, however, will be quite concrete. MacKenzie will, for example, explain the effect of rain on patterns of US stock prices, and reveal the mundane feature of the US political system that underpins the HFT signal (‘futures lead’) on which he will focus.
Donald MacKenzie is a professor of sociology at the University of Edinburgh. His books include An Engine, Not a Camera: How Financial Models Shape Markets (MIT Press, 2006) and the co-authored Chains of Finance: How Investment Management is Shaped (Oxford University Press, 2017). He writes regularly about financial markets in the London Review of Books.