Fundamentals of Algorithmic Markets: Liquidity, Contingency, and the Incomputability of Exchange

Since the mid-2000s, financial markets have been subjected to an unprecedented critical scrutiny, particularly in light of ‘black swan events’ such as the supposedly unpredictable Global Financial Crisis, and algorithmic ‘accidents’ such as the Flash Crash of May 2010. Yet while the complexity of derivatives instruments and the rise of high-frequency trading have received a lot of academic interest (Bryan and Rafferty 2006; MacKenzie 2014), less attention has been given to the measures implemented by central banks in recent years to revive trading. These measures are exemplified by practices such as quantitative easing, by which central banks introduce new money in the monetary supply of a country in order to promote lending and boost economic activity (see Holmes 2014). While the efficacy of such maneuvers remains questionable, my goal in this article is to focus on the deeper issue that they expose – that is, the centrality of market liquidity to financial activity and, by extension, to the dynamism of the socio-political sphere.
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