This episode explores the technological transformations that have led to markets at the speed of light: algorithmic traders and flash crashes. Yet for all the images of terrifying AI we discover  that stock markets in the cloud are more rooted in material than ever before, pushing against the laws of physics in the pursuit of speed and profit. We see a culture war between hoodie and suit, techie and yuppie, but find – no surprise here – that whatever the uniform, the elites win out in the end.

Transcription

The Frankenstein story – the monster that bursts out of the laboratory and pursues its creator – is firmly embedded in our collective imagination. The novelist Robert Harris gives it a spin in the Fear Index, published in 2011. But the monster is not a thing of flesh and blood. It is an artificially intelligent trading algorithm launched by a Geneva-based hedge fund. It is fantastically, malevolently intelligent: able to penetrate secret files and to discover the worst imaginings of its creator, to conduct a reign of terror through purchase orders and sub-contracts. As its creator attempts to burn down the servers that house it, the algorithm uploads itself into the digital netherworld where it roams free, doing as its code instructs: feeding off fear for financial profit.

Harris has a keen ear for details in the news, and the financial cataclysm sparked off by this machine actually took place, just over ten years ago, in the afternoon of 6 May 2010. A wobble in the US markets, and then a spectacular collapse: the Dow Jones losing 998.5 points in 36 minutes, a trillion dollars of capital evaporating in five. Circuit-breakers – automatic cut outs designed to stop the market self-destructing – halted trading. When the market opened again, prices climbed quickly back to the morning’s levels. Although individual traders may have made or lost fortunes (we don’t know – and Harris deftly weaves fiction into the gap) very few ripples spread into the economy as a whole. This was the ‘Flash Crash’.

There may have been fear but there was no panic, no shrieking or shouting. The whole affair was conducted algorithmically, as high-speed trading machines did the electronic equivalent of yelling ‘sell, sell’, unloading stock to each other at ever-falling prices, and creating a self-fulfilling cyber-crash. Algorithms don’t panic, but they do form expectations, and they do so in thousandths of a second.

An initial investigation found that a large sell order had triggered the flash. There was a veiled reference to a problem with the timing of data feeds, a technical, structural problem. If you follow the news in the UK, though, you might have heard of the Hound of Hounslow, Navinder Singh Sarao, a solitary London trader with unusual personality traits who built an engine to ‘spoof’ the Chicago algorithms and made millions trading from his bedroom. American regulators became convinced that his activities had sparked off the crash, though this seems a lot less plausible than the fiction of malevolent artificial intelligence. Sarao may have made $70 million but most of his money seems to have ended up in the hands of fraudsters and questionable entrepreneurs. The only thing he purchased was a second-hand VW which he was too nervous to drive. He was extradited to the United States to face justice. The judge, expecting a criminal mastermind, saw instead a 41-year old man with autism who still lived with his parents and laid down a lenient sentence of a year of house arrest, even if Sarao had threatened to cut off the thumbs of a market administrator.

Hounslow, for those who don’t know London, is an unremarkable borough to the west of the city: suburbs, offices, few tourist attractions. Though the pun on Wolf of Wall Street may have been too tempting to avoid, it tells us something. In the place of the champagne and cocaine fuelled highlife of Jordan Belfort, we have a super-trader in an upstairs bedroom clad in hoodie and jeans, the global uniform of the techie. The Hound is just one manifestation of the culture war that has shaped financial markets over the last two decades: hoodie and baseball cap versus shirt and tie, techno wizard against Princeton-educated Master of the universe. That he was extradited to America and tried for market malfeasance shows, however, that market and state still walk hand in hand, whatever uniform the managers are wearing. That the only person of colour in this whole narrative so far is stood in a court of law says something else about financial markets, something that needs to be dealt with in a later episode.

Hello, and welcome to How to Build a Stock Exchange. My name is Philip Roscoe and I am a sociologist interested in the world of finance. I teach and research at the University of St Andrews in Scotland, and I want to build a stock exchange. Why? Because, when it comes to finance, what we have just isn’t good enough. It’s been a while since the last episode, my apologies, but there is some stuff going on. If you’ve been following this podcast, however, you’ll know that I’ve been talking about how financial markets really work, and how they became so important. I’ve been deconstructing markets: the wires, and screens, the buildings, the politics, the relationships, the historical entanglements that make them go, all in the hope of helping you understand how and why finance works as it does. As well as these, I’ve been looking at the stories we tell about the stock market. You might be surprised how much power stories have had on the shape and influence of financial markets, from Daniel Defoe to Ayn Rand. I’m trying to grasp the almost post-modern nature of finance, post-modern long before the term was invented, the fact that finance is, most of all, a story. Start-ups are stories, narratives of future possibility; shares and bonds are promises based on narratives of stability and growth. Even money is a story, circulating relations of trust written into banknotes, credit cards and accounts. Stories set the tone, make the rules, determine what counts and what does not. A good stock market needs a good story, so if we’re serious about rebuilding financial institutions then we need to take control of those stories.

Markets populated by algorithms scarcely understood by their creators raise all kinds of new and pressing problems. Fictional physicists living in Geneva and leveraging their experience of quantum mechanics into monstrous artificial intelligence; autistic coders living with their parents; transaction speeds that push up to the possibility of natural laws; there’s something different in contemporary finance…

This episode is all about the technological projects that transformed financial markets beyond recognition. I need to offer a caveat here. Ethnographies of high finance are not at all my domain, and I’ll be relying more than usual on the work of colleagues: Donald MacKenzie, Daniel Beunza, Juan-Pablo Pardo-Guerra, Christian Borch, Anna-Christina Lange, Marc Lenglet and others. You’ll find full references to my sources in the transcript on the podcast website.

We can think of changes that have swept through financial markets in two ways. First of all, they are a technological project driven by the endeavours of engineers. The result has been a wholesale transformation in the materiality of markets. To step into a trading pit now, and we can think of pit only in the most metaphorical sense, is to step into a warehouse of humming and chattering servers. Like the traders of old, they jostle for space around a central exchange, but space measured out in fibre-optic cable and milliseconds. We can also, though, think of these transformations in terms of a wholesale change in our understanding of how exchanges should work, as the metaphor that underpins them changes from one of the market as a fundamentally social entity to market as a computational device where efficiency becomes of paramount importance. The market ceases to be a concrete thing in a specific place and becomes a distributed network located nowhere, and everywhere: Wall Street, Chicago and Houndslow.[1] This change in our understanding of what the market actually is, what it is all about, reflects longer term moves in our understanding of the economy under neoliberalism. From von Mises and Hayek onwards we have grown accustomed to thinking of the economy – the market (in scare quotes) – as a vast dis-embedded computational device as opposed to a specific set of social and material situations.

Let’s start with a story of technological progress. We may recall from episode eight how automation had long been a dream of economists and policymakers who fastened on the possibilities for efficiency and surveillance that a mechanised market might offer: moving trades from the inaudible whispers of brokers to the easily supervised daylight of a centralised system. Pardo-Guerra’s study of the automation of the London stock exchange shows how the process began with the automation of tedious routine work of settlement and clearing, work previously conducted after hours in the rooms beneath the Exchange’s trading floor. Allowing the technologists in, even here, cracked open the closed world of the LSE. Treated at first like second-class citizens, the engineers built a series of systems that incrementally adv