Monthly Archives: June 2020

Episode 17. White markets, black markets

This episode examines the racialized structures of finance. It sets off from the infamous Zong massacre and legal case of 1781 to explore the patterns of exploitation that underpin finance, and to show that contemporary finance is built on structures and practices established by eighteenth century slavery. It finds modern parallels in the speculative credit of the financial crisis and its legacy of austerity. There’s a personal narrative, as well, a family genealogy that circles the slave trade, winding up in the sometimes contradictory figure of the critical management academic.


A picture, a poem, a legal text. Three representations of the same unspeakable truth.

The picture: Turner’s greatest masterpiece – at least in the eyes of the art critic John Ruskin – the Slave Ship, or ‘Slavers throwing overboard the dead and dying, typhoon coming on’. A swirling mass of violence, colour, and anger, held together by a lowering sun, red, ochre, orange; the sea smashing in from the left, foaming, boiling, the whole picture askance. In the background the stricken ship, sails secured, ploughing through the spume. But the foreground, oh, the foreground: a severed black leg, manacle attached; hands reaching, the ironwork of that abhorrent trade somehow floating; hideous fishes descending ravenous, gulls circling, the water carmine to match the sunset. It’s hard to look at. I’ve never seen it in the flesh, this painting, but by all accounts its physical presence is even more unsettling. Ruskin, its first owner, could never find a place to put it, and the image haunted Mark Twain’s writings for years.

The picture, first exhibited in the Royal Academy in 1840, thirty seven years after the abolition of slavery in Britain and its colonies, evoked the sum of brutality and horror that the slave trade embodied. Yet it referenced one event in particular: the Zong massacre of 1781, an event that came to be emblematic of the horror of slaving and did much to galvanise the public to the abolitionist cause. The Zong was a slave ship and its captain, Luke Collingwood, ordered the drowning of 133 of his captives.[1]

Let’s not rehearse the details here. Let’s go instead to the poem. A cycle, in fact, called Zong! (with an exclamation mark) by M. NourbeSe Philip. You can find her reading from the cycle online; it is a tone poem of seemingly random words, forcing the listener to recognise the need to make sense of a happening that never can be understood. This, she writes, ‘is the closest we will ever get, some 200 years later, to what it must have been like for those Africans aboard the Zong’.[2]

The words are not entirely random.

The Zong massacre came to prominence through the efforts of leading abolitionist Granville Sharp. Sharp heard of the event from freed slave and campaigner Equiano, and recognising its rhetorical and political possibilities, compiled a weighty dossier which now rests in the archives of the National Maritime Museum. The massacre has, in this way and that, been expropriated ever since: as a symbol not of tyranny, but of salvation, of the abolitionist narrative that allows Britain to take credit for abolishing a practice that it had done so much to establish. A recreated Zong even sailed into the Thames for a 2007 celebration of the vote that abolished slavery.

There is another source, however, a prosaic account of the legal hearing that followed. It was not, you might be surprised to hear, a murder trial but a civil case, Gregson v Gilbert. For the massacre was not just an atrocity but the basis of an insurance claim, and when the underwriters refused to pay the slavers took them to court. Philip’s poem draws on this document. An early version of her poem, available online, begins as follows: ‘Captain slave ship Hispaniola Jamaica voyage water slaves want water overboard.”[3]  The legal report runs: ‘Where the captain of a slave ship mistook Hispaniola for Jamaica, whereby the voyage being retarded and water falling short, several of the slaves died for want of water and others were thrown overboard, it was held that these facts did not support a statement in the declaration…’ And so forth.

For Philip, the poet, this is a found text, corrupt, polluted by the murderous rationality of the law. And who could disagree?

The text comes from a collection of legal reports published in 1831, compiled from the notes of various lawyers. The editor responsible for the compilation was a barrister and legal scholar, a member of London’s inner Temple. His name was Henry Roscoe. My name is Roscoe too.

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. 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.

The recreated Zong may have sailed up the Thames, but the original never did. It was a Liverpool ship owned by the Gregson family, princes among the Liverpool slavers. To tell the story of the Zong  is to go back to the commercial world that developed in the eighteenth century at an astonishing speed in this provincial town in north-west England. The Zong is, as the literary scholar Ian Baucom has made clear in his monumental ‘Spectres of The Atlantic’, an event that is both singular (though one hundred and thirty three persons, thrown overboard, one by one, over the course of three days, is also one hundred and thirty three singular events…) and typical. It is typical because it epitomises a new kind of finance capital that had grown more than anywhere in Liverpool, and that had propelled  this sleepy provincial town to a position of such pre-eminence in the Atlantic trade that it could consider itself one of the world’s commercial capitals.

I’m writing this in the days following the spectacular dethroning of Edward Colston, the Bristol slave trader whose statue had watched over the city until just last week, and whose toppling into the harbour unleashed a great catharsis for many in the city.[4] I don’t know Bristol well so I was most surprised to hear, not that the statue was pulled down, but that it still stood. And that it did so, despite years of civic campaigning, because people had defended it as part of the history and heritage of the city. It’s just history: passive, past, powerless. If we follow Baucom’s logic, and I think we must, we come to recognise that this history is very much in the present: that the origin of global finance as we know it today is not solely in the massive deregulations of the 1980s, nor the technological leaps of the last two decades, but also in the tormented bodies of Africans captured, transported, and enslaved.

The Gregsons may not have left statues, or even many traces in the archives (thank you here to Baucom, on whose work I am relying for this account, among others listed in the notes on the podcast website). But they made an indelible mark upon Africa, the Caribbean, and Liverpool. William Gregon, patriarch of the family, embodied the entrepreneurial drive and opportunity that Liverpool offered in the eighteenth century. The son of a porter, he started out a rope maker but rose to be one of its most distinguished citizens, becoming mayor of Liverpool in 1762. During his career he invested in 152 voyages. ‘Even in the desolate world of slave statistics’, writes the historian James Walvin, ‘these are astonishing figures’: his voyages had carried 58,201 Africans, of whom 49,053 survived to landfall. By that account – and we shall return to accounts shortly – 9,143 perished.[5]

As mayor, Gregson would have occupied an office in the Liverpool Exchange, a lavish building opened in 1754. Like the later Chicago Board of Trade, which we visited in episode two, the Exchange existed not just as a physical monument to new found wealth and power but also as a political organisation devoted to the furtherance of the city’s economic growth. Unwholesome as we might have found Chicago’s industrial slaughter of animals, that city’s trade was nothing compared to that of Liverpool. Slaves never travelled through Liverpool, of course, but no one was innocent enough to suggest that the city’s newfound prosperity was due to anything but slavery. The merchants themselves, the bankers and lawyers who served them; ship builders expert in the specialised design of these floating gaols; rope makers, gun makers, ironmongers churning out gratings and manacles, sellers of victuals and rum; corrupt publicans who plied the sailors with drink and press-ganged them into service on the slave ships – the most hateful, hazardous and destructive occupation on the seas – all of this was driven by slavery. The city’s tendrils followed the new roads and waterways inland, shipping manufactured goods from Manchester to Africa and American cotton back to Lancaster. Slavery powered the economy of north-west England, and everyone knew it; those commissioning and designing the Exchange did not shy away from the truth, decorating its exterior with African heads.

I don’t want to talk about the Zong, rather to circle it, casting glances at the horror. But I am tied to these events by more than a shared heritage of English guilt. Just as the city boomed commercially, so it enjoyed an explosion of culture and refinement. The Exchange building’s piazzas of white stone were just one expression of a growing passion for all things Italian. In fact it has been argued that the British romantic notion of the Italian Renaissance came from Liverpool.[6] Liverpool’s cultural transformation was led by one man in particular. His name was William Roscoe. He was the father of Henry, barrister and transcriber of the Zong hearing, and he was the great grand-father of my great-grandfather.

Unlike Gregson, Roscoe was famous. He is now remembered as one of the city’s founding fathers, commemorated in plaques and street names. There is a fine little pub called the Roscoe Head; I have a picture of it above my loo, which I think is funny. He was a leading cultural figure: his biography of Lorenzo d’ Medici brought him admiration from Horace Walpole and comparisons with Gibbon, spreading Liverpool’s identity as a cultural centre across the world. He wrote a children’s poem (originally for my great-grandfather’s grandfather), titled ‘The Butterfly’s Ball,’ which was admired by King George. He is remembered most of all as a leading abolitionist: author of three long poems condemning slavery. These were a great popular success, although to the modern ear they are unwieldy and inaccessible. He was even an MP for a crucial year which allowed him to vote for the abolition of slavery in 1807, though he faced riots and hostility on his return to Liverpool.

And yet. Roscoe’s first profession was that of lawyer, and by the age of 46 he had made enough money to retire to Allerton Hall, a stately home outside the city. His art collection included a then unfashionable Leonardo da Vinci. In the year 1800, he took up a partnership in distressed banking firm run by his friend Thomas Clark, and set it right. What did he bank? What contracts did he draw up? The British banking system was powered by these bills of exchange. Liverpool’s engine ran on slavery. Roscoe’s huge legal fees, his banking commissions, his stately home, his Leonardo, would have been tainted by its stench.

He would have certainly shared a cultural and social milieu with the Gregsons and their peers. Among the institutions that sprang up in Liverpool at the time was the Athenaeum, a subscription library that served, and still serves, as the meeting place for the city’s merchant elite. Gregson’s son-in-law, George Case, bought a large house next door to it. Roscoe was one of the Athenaeum’s founders and his library was the foundation of its extensive collection. One of Roscoe’s close friends was Matthew Gregson, who cannot of been unrelated. The slave merchants did as good eighteenth century burghers would do: giving money to the right causes, improving and developing the infrastructure of the city.  It seems likely that my great-grandfather’s great-grandfather knew these men well, conducted business with them regularly, took their subscriptions to his civic schemes, and welcomed them at his cultural events. Indeed, in the Oratorio week of 1784, just months after the Zong hearing, and a few months before his son John became Mayor, Liverpool held its Oratorio Week celebrations with theatre, shows, an art exhibition and a masked ball. Baucom speculates that the Gregsons attended the latter; I speculate that they also attended Roscoe’s exhibition of Italian art, the first such to be held in Liverpool.

And this distinction between the visceral horrors of the Middle passage and the refined highlife of Liverpool’s new commercial elite was possible only because of a variety of technical and material innovations that can be subsumed into the category of finance.

The Liverpool merchants – and lawyers and bankers – invented a system of credit that allowed them not only to greatly speed up the circulation of capital around the slave triangle, but also to benefit from interest on that capital as it flowed. Moreover, they perfected a system of insurance that helped them survive the regular total losses sustained by slaving expeditions. We tend to think of slaving as a physical endeavour, but it was a financial one as well. The trade, as we all know, operated in a triangular fashion. Manufactured goods were shipped from Liverpool and Bristol to West Africa where they were bartered for slaves. These Africans were penned in slave factories subsidised and staffed by the British government. You will remember from episode three how the London stock exchange originally developed to provide a market in the early joint-stock corporations which existed to further British colonial interests; the Royal African Company, which operated these factories in the seventeenth century and with which Edward Colson traded, was one such.

Slaves were transported across the Atlantic – the hellish Middle passage – then handed to factors who supervised the auction for a commission. The final leg of the journey saw this money converted into goods for import, such as sugar, rum and cotton and returned to Liverpool for sale.

The problem with this system was that it was slow and risky. Too much capital tied up in material goods, circulating at the pace of the breeze, vulnerable to shipwreck, piracy, and in the case of the human cargo, death, disease and insurrection.

The Liverpool merchants started to use credit in the form of bills of exchange. I paraphrase Baucom here. The factor would sell the slaves for hard cash and then, having taken his commission, return an interest-bearing bill of exchange by the next ship to Liverpool. The factor had ‘not so much sold the slaves…as borrowed an amount equivalent to the sales proceeds from the Liverpool merchants and agreed to repay that amount with interest. The Liverpool businessman invested in the trade had, by the same procedure, transformed what looked like a simple trade in commodities to trade in loans.’ The bills, like modern bonds, circulated among investors at a discount to face value. This bill-bond market became so liquid and reliable that in due course the merchants began to pay the African vendors with bills of exchange as well. The slaves, writes Baucom, ‘functioned in this system simultaneously as commodities for sale and as the reserve deposits of a loosely organized, decentered, but vast trans-Atlantic banking system: deposits made at the moment of sale and instantly reconverted into short-term bonds. This is at once obscene and vital to understanding the full capital logic of the slave trade.’[7]

Capital, as Marx figured out, is desperate to jump from this earthbound circuit of production to a situation where it can multiply upon itself. That’s the heart of financial capitalism, then and now: the search for ways of setting speculative capital free to flow more quickly and generate higher returns. By this account, it is not just the slave ship that sits at the heart of the trade, but the banking house, its solidity underpinning the circulation of credit around the Atlantic. The bank and these credit notes are enmeshed in dense social chains of guarantee, those same underwritten by the merchants’ knowledge of and trust in each other. That also was true of modern finance, at least until the algorithms arrived. It’s why I feel a little uncomfortable about William Roscoe’s social standing and I feel very uncomfortable about his bank; when he entered the partnership in 1799, it was at the behest of London banker Sir Benjamin Hammett, who held some £9m on deposit. Where can all this money have come from?

Slaves existed simultaneously in two places, in the stinking holds of the slave ships and in the disembodied realm of accounting books and ledgers. Their speculative financial value was locked into place by a final financial technology closely related to the social networks and the financial institutions of the city. This was insurance. Slave merchants realised quickly that the only means of surviving frequent total losses of capital was through mutual support and the pooling of risk. Insurance formalised this practice but by underwriting the economic value of a person it also made concrete their existence as an economic object, a chattel to be understood in terms of future revenue streams. Insurance makes speculative value real: underwriting a painting, for example, guarantees that the expectations of worth will necessarily be met, at least under the appropriate conditions.

This goes to the heart of the Zong massacre. As Captain Collingwood, incompetent or deranged, or both, found himself unlikely to land a cargo of slaves, he sought to crystalize by murder that guaranteed value. If the slaves had died of natural causes, or landed unsaleable, it would have resulted in a loss for Gregson’s syndicate. By the maritime insurance principle of general average, if part of the cargo had to be jettisoned to save the ship, all stakeholders would pay their share. And so, on the flimsy justification of navigational error and water shortage, he instructed his crew to hurl overboard one hundred and thirty three men. It took three days, even if the final ten, grasping what little agency they had left, chose to throw themselves voluntarily into the ocean. NourbeSe Philip’s cacophonous words make as much sense of this as anything: it is senseless. But not to Captain Collingwood. His actions cleaned up the messy, bodily aspect of these persons cum commodities, catapulting them headlong into the realm of speculative value; of capital already made real by the insurance contract.

James Walvin warns us to be careful about the surviving testimony of motivations – how can we really know what was decided on the ship? – but the fact remains that the Gregsons sought redress from their insurers. But the chattels in question were human souls, one hundred and thirty three black lives, and they mattered then, as they do now.

I would like to say that is why the insures refused to pay, but Henry Roscoe’s papers show a legal system unconcerned with the niceties of life and death. Finding that they should have a bad market for their slaves, argue the lawyers for the insurers, the slavers took these means to transfer the loss from the owners to the underwriters. The Gregsons’s lawyers begin, ‘it has been decided, whether wisely or unwisely, that a portion of our fellow creatures should become the subject of property. This, therefore, was a throwing overboard of goods, and of part to save the residue.’ Lord Mansfield, presiding, concedes the matter to be ‘a very uncommon case’, the claim unsupported by evidence, and worthy of a second hearing. ‘It would be dangerous,’ says Justice Buller, ‘to suffer a plaintiff to recover a peril not stated in the declaration!’ See what is not contested: the morality of slavery, the existence of property rights, the act of murder.[8]

Throughout this series of podcasts, I have made one point over and over. Finance is sustained by a network of practices and technologies, and these are political. They are worked into material devices, the infrastructures of markets, and these are political too. Bills of exchange, accounting technologies and insurance policies are not neutral bystanders to atrocity, but the socio-material substrate through which such atrocities are conducted, just as much as manacles and slave ships.

Fast forward two hundred and twenty five years, to the year 2008. The global financial system is on the verge of collapse. The US government injects $182.5bn into AIG, one of the nation’s great insurers, which pays out to Wall Street creditors at 100 cents in the dollar, a direct transfer of wealth from American taxpayers to the richest stratum of society. The insurance had been doing then what Gregson’s insurance was doing in 1781, making real speculative value, and once again the state intervenes to keep this fiction in place.

To understand the roots of the global financial crisis we need to head back to the late 1970s and Wall Street. It was here that collection of traders, led by Salomon Brothers’ colourful Lewie Ranieri, invented the mortgage bond. Mortgages had, for years, been part of the American dream, one of the ways that middle America could climb aboard the raft of rising prosperity in the post-war years. Mortgage lending was handled by thrifts, what we UK would call building societies: sleepy institutions dedicated to the safe custody of savings and low risk loans to reliable local property owners. Legislation favoured the borrower, to the point where Ranieri could grumble that ‘the mortgage instrument becomes so perfect for the borrower that a large economic benefit is taken away from the other participants, including the long-term investor’.[9]

In order to increase supply, two giant government organisations had been founded to pump money into the system, but the result was still unappealing for investors. The main risk, from the investor’s point of view, was prepayment. With legislation allowing mortgage holders to repay their mortgages at will and without penalty, any financial instrument based on mortgages would be extremely sensitive to changes in interest rates, exactly what an investor would be seeking to avoid. The technique perfected by Ranieri, supported by legislative changes of the kind that Salomon’s massive capital and influence could achieve, was to collect a large number of individual mortgages into a pool. The pool was divided into tranches, or slices. The lowest slice absorbed the earliest prepayments (and since mortgages were effectively guaranteed by the government, defaults also registered as prepayments) in return for the highest interest rates. The middle tranche absorbed the next, and the senior tranche held the longest-surviving mortgages. The genius of this structure was that one did not have to know which individual mortgages fell into which tranche; they self-selected by virtue of defaulting. Across the whole thing it was possible therefore to have a robust, statistically informed understanding of the likelihood of  prepayment (the risk) set against the interest returns.

The bond is a device for standardising, and typifying, for translating the irregularity and grit of everyday domestic situations into a smooth and predictable flow of returns. One could forget about the underlying particularities. As Michael Lewis, who chronicles this project in Liar’s Poker, so colourfully puts it: ‘Thus standardized, the pieces of paper could be traded. All the trader would see was the bond. All the trader wanted to see was the bond. A bond he could whip and drive. A line which would never be crossed could be drawn down the centre of the market. On one side would be the homeowner, on the other, investors and traders.’[10] To make things even more certain, the bond could be insured. Issuers took to insuring the mezzanine layer with giants like AIG, who thought it good business. Insurance is the final step in the concretisation of this value, a legal guarantee that even in the event of catastrophic failure, the bond remains worth what it is worth. Backed by this apparatus, the credit rating agencies issued the highest level of creditworthiness to the senior bonds, treble-A, equivalent to the national debt of a healthy nation state. The interest payable on the super safe senior tranche, while still low, was much higher than the equivalent return on, say, US Treasury bills and therefore very attractive to pensions funds and public sector organizations.

For those constructing the bonds, the profits came in the difference between the interest received and the monies paid out. The quickest way to increase this spread, as it was known, was to lend at higher interest rates, and to do that one had to make riskier loans. A parallel technology of credit scoring had emerged in the United States over the previous decade and it made it possible to issue such higher-risk, higher reward loans. These became known as sub-prime, a category of borrower with a creditworthiness scored below a certain level, suddenly accessible and tractable to lenders. In episode four I explained how theories of adverse selection suggest that banks should not be chasing high risk – high return loans. But if the thrifts were able to pass on the debt to investors, they no longer cared about the risk, and they rapidly became brokers on commission, interested only in the volume of mortgages they could issue and pass on.

We now have to look sideways, to the corporate banking departments of Wall Street, who were in the 1990s inventing a similar structure. Constrained by new regulations, they sought to shift risk from their balance sheets so they could lend more. They constructed tranches of corporate debt which paid out in the same way as the mortgage bonds, the earliest defaults being taken by the junior tranches which earned more interest and were bought by specialists, the mezzanine level sold to more conservative investors. The super safe senior level offered such low returns that it wasn’t worth selling so the issuers held on to the bonds, shifting them off their books by means of insurance.

The CDOs, or collateralised debt obligations as they should properly be known, were initially successful but were badly hit by the dotcom collapse and subsequent recession. Mortgage bonds continued to do well, so a new practice arose in corporate debt offices. They began to use mortgage bonds as the underlying material for CDOs. What made this so attractive was the fact that the high-paying risky junior tranches from a number of bonds could be scrabbled together into a CDO that would pay out at much lower rates. Indeed, the riskier the underlying tranche, the higher the income and the bigger the gains to be made on the deal. A canny trader would book the total profit from the life of the bond upfront and demand a bonus on that basis. The Wall Street tail soon began to wag the dog and the demand for high-risk mortgages led to a massive explosion in borrowing, a moment captured by the movie The Big Short: two wide-boy, white mortgage salesman in a tacky country club in Florida, boasting of their loans to migrants unable to read the small print. In real life, as a substantial amount of scholarship has shown, predatory lending was directed disproportionately at black and Latino communities previously excluded from mainstream lending.[11]

These devices for creating future certainty depended upon certain assumptions to make the un-knowable concrete and tractable. One such was the idea of correlation, the extent to which defaults are dependent upon one another. MacKenzie has found that measures of correlation for debt based bonds settled around 0.3. That was a most conservative assumption: if one third of American blue-chip business simultaneously defaulted on its debt there would have been an economic Armageddon. If you have been following my explanation, however, you will have by now spotted a flaw that eluded the great minds of Wall Street.

Bonds are a device for creating future certainty, and the future certainty created by the mortgage bonds is that all of the defaults, wherever and whenever they might arise, will end up in one place. If you take a bundle of those low, risky tranches you will find that you are holding not some but all of the defaults on the property market, and that a relatively tiny movement in the underlying portfolio will completely destroy the value of the bond. Donald MacKenzie puts it politely when he remarks that the lunch of diversification was being eaten twice; one of Lewis’ characters in the Big Short shrieks ‘but the more we looked at what a CDO really was, the more we were like, Holy shit, that’s just fucking crazy. That’s fraud. Maybe you can’t prove it in a court of law. But it’s fraud.’

With the exception of a few sceptical hedge fund managers, nobody seems to have figured this out. MacKenzie suggests that the problem lies in the organisation of the banks, with large departments who didn’t talk to each other re-duplicating a process and therefore destroying its benefits. Certainly AIG didn’t know, or it wouldn’t have insured the super senior tranches and suddenly found itself needing $182.5 billion in taxpayers funds to meet its obligations. Those sceptical hedge fund managers – the hero of The Big Short – found that the only way they could bet against the market was to buy insurance against default, thus reifying the speculative value of the instruments. Worse still, their premiums could be used to make copies of the mortgage based CDOs that amplified eventual losses enormously.

These deals offered an ‘irresistible arbitrage opportunity’, as MacKenzie puts it. An arbitrage is a risk-free profit, free money, but it was only risk-free for those constructing the deals. At one end of the trail are poor Americans, whose adverse credit ratings and lack of financial skills made them easy prey for the issuers of mortgages so constructed as to lock them into economic bondage. These people were disproportionately black, Latino, or migrant. Their future repayments were sold on, packaged and repackaged, underwritten by insurance. Sophisticated financial instruments backed by novel ways of measuring and counting – the Gaussian copula, soon to be known as the formula that blew up Wall Street – allow the solid value of brick, concrete, and the steady stream of hard won weekly wages to cross to the realm of financial circulation.

When the whole turns out to be phantasm and doesn’t so much tumble down simply evaporate, nation states produce bailouts to the tune of thousands of billions of dollars. Only in one country, Iceland, were prosecutions made. The after effects linger a decade later. The U.K.’s policy of austerity, a deliberate attempt to balance the national books for the benefit of those financial classes that depend upon such things, has hollowed out the national infrastructure in ways that have become terribly apparent in the country’s response to Covid-19. Here too the BAME community has suffered worst.[12] The credit crisis bailout is eerily reminiscent of another, then the largest in British history. By the time of abolition slave ownership was so thoroughly imbricated into British society that the government was forced to produce an enormous bailout to compensate individual owners. Slavery, like the banks, had become too big to fail.

Let me be precise. I’m not claiming that contemporary finance employees whips and manacles, even metaphorically, or that Wall Street is as bad as Gregson and his clan. I am saying that there are regimes of dominance and exploitation at work in contemporary finance, still. If you doubt me, take a look at the uncanny similarities between the strategies of cutting-edge philanthro-capitalism and the slave owners.

Social theorists Zenia Kish and Justin Leroy notice the Zong massacre too.[13] For them, it is a ‘cautionary tale of how moral outrage at instances of overt racial violence can obscure the more subtle and persistent relationship between race and finance… the fact that England’s financial development over the previous half century was predicated not only on compelling African bodies to work but also on innovating ever more creative ways of extracting value from those bodies.’ Slave owners in the US used the bodies of their slaves as collateral against debt and capital for expansion; training the children of slaves, born into bondage, as artisans greatly enhanced the future capital streams available and the value of those assets. Economic practices constituted the living slave as not just a source of labour but also the basis for financial speculation, allowing the slavers to benefit twice. Here, argue Kish and Leroy, modern finance offers an uncomfortable parallel. Since the financial crisis, financiers have sought to bring their capital to the benefit of social good and have invented instruments that invest in various social impact projects, with returns triggered when the target population hits certain milestones. So prison inmates, or young offenders, or members of whatever social stratum is considered disreputable, undesirable and costly become recast as potential investments. Where they had previously been a cost to society they become incorporated into ‘financial systems that invent new ways to generate capital returns for others out of the risks personally shouldered by subprime subjects.’ Finance wins twice, praised for ‘solving’ (in scare quotes) the very same problems that it has benefitted from creating.

In some cases, such as the application of such programs to prison inmates, we cannot even claim that the participants are free. There really are manacles. And real poverty is as hard and binding as steel. Such clouds hang, for example, over the fashionable bottom of the pyramid program, the argument that multinational corporations should take the lead in fighting global poverty by teaching the world’s poorest folk to become consumers. Or the global trade in organs for transplantation, from poor brown bodies to rich white ones, with compelling empirical evidence that kidneys are sold only by those most disadvantaged and most trapped in debt.[14]

From Tom Wolfe’s description of the bond trading floor – well educated young white men baying for money, through Michael Lewis’s account of the whitening of Salomon Brothers in the 1980s, to Karen Ho’s ethnography of the gendered, racist and classed valences of smartness in Wall Street, we know that those at the top of financial markets are white. In this episode I have made explicit the corollary, that those at the bottom are black, brown, Latino, migrant. White markets need black markets.

So what about William Roscoe, my famous abolitionist ancestor? He voted for abolition and faced physical reprisals for doing so. He was brave. But even he did not entirely reject the commercial realm of value when it came to abolition: he voted in Parliament for compensation for slave owners. Though he was horrified by the cruelty of the bodily trade, he could not escape the patterns of capital that underpinned it. He owed his legal practice and his bank to just that capital. Perhaps he thought that slavery had to be reformed from the inside. It strikes me that Roscoe’s position was uncannily like that of the critical academic in a contemporary business school: seeking to give voice to the injustices that flow directly from the system that pays our salaries; playing the game, warily, ironically, but playing it all the same.

In fact, we haven’t been nearly as brave as Roscoe. We nip the hand that feeds us, but not too hard, as we earn a comfortable living from the expropriations that underpin contemporary globalisation. Not directly, but that’s the point. No one gets out of this cleanly. Statue toppling may be justified and cathartic, but the emphasis on spectacle as a moment of change can hide the fact that Colston’s history – and Gregson’s and Roscoe’s – is still with us. There’s a lot to set right: reforming our curriculum, our institutions, and of course, our financial markets. Telling better stories about how the world might be, and enacting them through our own practice and habits. It will be difficult.

Still, I’m certain that it’s better to be a Roscoe than a Gregson, and the fact that his bank collapsed and he was run into bankruptcy helps assuage the thoughts of tainted money passing through the generations. Though I wouldn’t have minded if we could have hung onto the Leonardo.

I’m Philip Roscoe, and you’ve been listening to How to Build a Stock Exchange. If you’ve enjoyed this episode, please share it. If you’d like to get in touch and join the conversation, you can find me on Twitter @philip_roscoe. Thank you for listening. Join me next time – for the last episode, when we’ll finally be building that stock exchange.



Sound effects under an attribution licence from

Prison door lock

Cash register:




[1] For accounts of the massacre see, among others, James Walvin, The Zong: A Massacre, the Law and the End of Slavery (Yale University Press, 2011). and Ian Baucom, Specters of the Atlantic: Finance Capital, Slavery, and the Philosophy of History (Durham, NC: Duke University Press, 2005).

[2] Quoted in Anita Rupprecht, “‘A Limited Sort of Property’: History, Memory and the Slave Ship Zong,” Slavery & Abolition 29, no. 2 (2008).



[5] Walvin, The Zong: A Massacre, the Law and the End of Slavery, 57.

[6] Stella Fletcher, Roscoe and Italy: The Reception of Italian Renaissance History and Culture in the Eighteenth and Nineteenth Centuries (Routledge, 2016).

[7] Baucom, Specters of the Atlantic: Finance Capital, Slavery, and the Philosophy of History, 61.

[8] George Chandler, William Roscoe of Liverpool (London: B.T. Batsford Ltd, 1953).

[9] Quoted in Donald MacKenzie, “The Credit Crisis as a Problem in the Sociology of Knowledge,” American Journal of Sociology 116, no. 6 (2011). This paper informs much of the following account.

[10] M Lewis, Liar’s Poker (London: Coronet, 1989), 99-100.

[11] See, for example, the accounts in Justin P. Steil et al., “The Social Structure of Mortgage Discrimination,” Housing Studies 33, no. 5 (2018); Gary Dymski, Jesus Hernandez, and Lisa Mohanty, “Race, Gender, Power, and the Us Subprime Mortgage and Foreclosure Crisis: A Meso Analysis,” Feminist Economics 19, no. 3 (2013).


[13] Zenia Kish and Justin Leroy, “Bonded Life,” Cultural Studies 29, no. 5-6 (2015). Quotations from p641 and p645

[14] For critical perspectives on the BoP seeSuparna Chatterjee, “Articulating Globalization: Exploring the Bottom of the Pyramid (Bop) Terrain,” Organization Studies 37, no. 5 (2016).; for organ markets see, e.g. Nancy Scheper-Hughes, “Keeping an Eye on the Global Traffic in Human Organs,” The Lancet 361, no. 9369 (2003).

Episode 16. Markets at the speed of light

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.


FrankensteinThe 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 advanced the automation of trading until, on the day of Big Bang, 6 October 1986, the LSE opened in a fully electronic form. We saw in episode eight how this change took many by surprise, not least the LSE’s own management which had expected to operate a hybrid face-to-face and electronic trading system. But within days the trading floor was dead, and within months it had been closed. The engineers had built their own networks of power within the organisation and suddenly they were running the show. We saw how TOPIC, the LSE’s dealing screen, augmented by the FTSE 100 trigger page, created a completely new space for the market: a series of digital representations of trade accessible anywhere. It was still, however, a hybrid solution with dealers advertising prices that would be transacted by phone or voice, ‘folding’ existing practices into a new technological arrangement; the engineers’ institutional advancement did not really upset the money-making hierarchies of the LSE.

A different kind of challenge came from outside the LSE. By the mid-1990s, as Pardo Guerra shows, an industry had sprung up in the provision of computerised infrastructures which could be bought almost off-the-shelf by anyone with the desire to set up a new exchange. “Within this sprawling ecology,” he writes, “there was increasing recognition of the dominant design… electronic order books that allowed for the direct interaction of instructions from investors without the intervention of humans to coordinate transactions.”[2] Three engineers, named Peter Bennett, Michael Waller-Bridge and Stephen Wilson, had spent years at the LSE trying to set up a pan-European order book system. Blocked in this endeavour they set out on their own. They called their start-up system Tradepoint, and parked it symbolically out of the City, in the architect Lord (then Richard) Rogers’ building in Thames Wharf, also home to the renowned River Café, the first of London’s great stripped-down continental-fare gastro hubs. All of this was a performance, even if the restaurant did help bring visitors to the office and allow them to make their case on home territory. What was it a performance of? Of difference, of outside status, of the power of technology to break up cliques and upset apple carts. Another performance took the form of a ‘computer room’, an ordinary room equipped with a huge ventilation duct and mains cable, out of bounds apart from the sign on the door, that helped to convince visitors that the market was backed by sufficiently weighty technology. In reality, the computer system was quite moderate, enhanced by the programming skills of a colleague Ian McLelland, who customised a software package bought off the shelf from the Vancouver Stock Exchange. As for the upset apple carts, that was a performance as well: Tradepoint brought to bear an impressively deep network of social relationships with existing players, including making an agreement with the London clearing house and inviting its boss, Sir Michael Jenkins, onto the Tradepoint board.

There was, as Pardo Guerra points out, a moral imperative to the Tradepoint offering: ‘by allowing competition beyond the control of the LSE’s market-makers, their electronic order book would narrow spreads, driving down costs for end investors’. The order books, and the practices that came to be associated with them, notably anonymity, were attractive to overseas investors, derivatives trades and hedge funds. It was a venue for early robot traders, market participants ‘represented by installed boxes literally sporting flashing lights’. Tradepoint never amassed the volume of orders necessary to be a commercial success, but it did, in Pardo-Guerra’s words, change ‘the language of what was possible and permissible’[3].  Although an attempt in 1995 to forcibly introduce an order-driven system led to a members’ rebellion and the sacking of chief executive Michael Lawrence, order-driven trading was now inevitable and in October 1997 the LSE introduced its new system, SETS. Order books began to diffuse through the institution from the most senior markets downwards.[4]

Pardo-Guerra’s observation that Tradepoint changed the language of the possible is crucial here. It takes us back to our second causal factor, the evolving understanding of the purpose of an exchange. Moving away from thinking of a stock exchange as an institution rooted in geographic and social place to a distributed network of information processing shifts what we value. Speed, efficiency and structural elegance are the things that matter. This is the engineer’s aesthetic rather than the financier’s and it flows from a wellspring of technological expertise. But you will remember also our account of markets as comprising organisational fields, a social theory that sheds light on the evolution of institutions as high status actors seeking to consolidate their advantages at the expense of the less powerful. As the Tradepoint episode shows, these new technologies and conceptions of market organisation become the next battleground in struggles for institutional dominance. You might recall how, when the LSE designed its junior market AIM, a group of influential market-makers managed to hold off electronic order books and preserve their profitable positions. But order books remained a contentious issue and by the early noughties, with AIM internationalised and home to stocks larger than British SMEs, the LSE began to employ them in its junior market. What could the market makers do? External competition seemed to be the only way for the market-makers to resist the power of the LSE but there was no competitor ready to hand. Or was there?


We left OFEX in dire straits, with a failed fundraising, and the Jenkins family evicted from the firm. Into this void of leadership stepped Simon Brickles, the barrister who had been instrumental in setting up the constitution of AIM and had later become head of the market. He had left the LSE in 2003, frustrated by an increasing emphasis on order books and its move away from his vision of a market with light-touch regulation, a high temple of capitalism. Brickles sensed that the way out of OFEX’s problem was a headlong charge – not away from the LSE but towards it.[5]

His shareholders agreed. The market-makers who had supported the rescue fundraising to become major shareholders in OFEX were chafing at the high fees imposed by the London Stock Exchange – now a demutualised and revenue-focused global corporation – for settlement and transaction. The European MiFID regulations, expected in 2007, sought to open up competition between markets, but there was no possibility of competition unless a vehicle to challenge the LSE could be found. Brickles therefore began to expand the market’s offering. The company announced a £2.5 million fundraising to pay for an expansion in the number of securities traded, stating ‘the company intends to markedly broaden its existing trading services to encompass an extended range of securities. The enlarged trading service will allow brokers and investors flexibility in selecting their execution venue’. In other words, the junior market was to be positioned as a direct competitor to LSE’s smaller company markets and AIM.  On November 10, 2005, the Times reported a private meeting at the offices of mid-tier broker Charles Stanley: ‘Present at the meeting were representatives from Stanley and dealers such as Seymour Pierce, Peel Hunt and Winterflood Securities, which has led the opposition to the LSE. Some brokers are upset at the extension of the LSE’s SETS part-electronic trading platform to various small-cap and AIM stocks, for which they claim it is unsuitable.’ And there you have it, an outbreak of strife over the rights and privileges to make money in the markets.

On 30 November 2005, after a period of intensive work, the PLUS service (as it was now called) was launched. It enabled brokers to trade any stock on the Official List, ‘everything from Vodafone, down to the smallest FTSE All-Share.’ But it was not yet a fully-fledged stock exchange and another funding followed, pegged to the ambition of achieving a licence as a Recognized Investment Exchange. According to the offer document, the firm, currently focused ‘on providing cost-effective quote and trading services dovetailed to the needs of small and mid-cap companies… is seeking to expand into offering services to meet the quotation and trading needs of larger companies and the UK institutional community.’ In February 2007 the offer, heavily oversubscribed, valued the company at £43m.

Central to the whole endeavour was PLUS’ trading system. It had to be fast. Tradelect, the LSE’s new £40m system, went live on 18 June 2007, cutting order processing time to 10 milliseconds and greatly reducing trading costs. PLUS’ efforts show that the process of setting up a new stock exchange had evolved from a primarily social to a material and technological project. It ordered a platform from the Scandinavian firm OMX, but that was just the start: it needed to connect to market-makers, brokers, data vendors and the internal surveillance system. It had to be robust. It was, as Brickles said, ‘a huge spider’s web, and if any one of those bits of the spider’s web doesn’t connect you cannot launch the market.’ July 2007 saw the granting of the RIE license, and the OMX X-Stream platform launched in November, just as MiFID came into force. Both took up quantities of management time and were finished in time for the November deadline: ‘No mean feat. We were running pretty hard’, said one of the executives.

But, as Tradepoint’s founders had clearly understood, starting a market isn’t just a technological project. PLUS’ concentration on the material infrastructure perhaps overwhelmed the social and discursive labour involved in setting up a new exchange. Despite a shared management expertise, PLUS failed to engage in the processes that had made the AIM launch a success: prolonged, interactive consultation with the investee community. Indeed, many in the smaller company community felt that PLUS was no longer seriously committed to its original constituency. They levelled the same critique that PLUS had been making against the LSE: a steady drift upstream towards bigger companies and more lucrative business. John French, the businessman who chaired the advisory panel, described the task of maintaining a focused market for smaller company shares as being like ‘pushing water uphill’ in the face of scant interest from institutional investors and the market’s own management.

Any doubts over the market’s direction of travel – from smaller company nursery to discount trading and trade reporting venue – would have been settled by the Turquoise affair, a significant and ‘traumatic’ distraction for management in the autumn of 2007. Turquoise was a dark pool, a lightly regulated trading venue, that would offer anonymity and low fees. Like PLUS’ move to compete with the LSE’s small-cap markets, Turquoise sprung from the fact that in the mid-2000s ‘people hated the LSE,’ then run by Clara Furse, ‘it was…vicious.’ It had formidable backers, a number of senior executives of global investment banks , ‘big swinging dicks,’ according to one interviewee, ‘…big players, nothing to do with small company investing but big players…[who] got it into their heads, probably rightly, that the LSE was taking too much of the pot in trading terms…’ Although it had first been mentioned in the press in April 2007 it had not made much progress, earning itself the sobriquet ‘Project Tortoise’. These executives needed infrastructure and expertise in market operation, and on 6 October 2007 the Daily Telegraph ‘revealed’ that PLUS was negotiating the terms of a ‘takeover’ with Turquoise, while the Independent announced a ‘merger’. PLUS shares were suspended at 28p following the announcement of a ‘non-binding heads-of-terms agreement with a third party’. But nothing happened. By 19 October talks were over, and Turquoise was reported as looking for a deal with Cinnober, a Swedish technology firm. Still no progress was made and eventually the whole thing was quietly absorbed by the London Stock Exchange, now run by the shrewd and politically aware Xavier Rolet.

By the early noughties, then, we have reached a situation where the scuffles between markets – battles for domination and profit among rival market participants – are played out through technological systems. The ‘market in markets’ longed for by regulators materializes quite literally in the wires of market systems and the code that flows through them. US markets followed the same trajectory. Throughout the 1970s and 80s ongoing institutional bricolage had led to the electronic NASDAQ system, where brokers displayed prices and dealt with each other by phone. Although the network spanned America, it encoded existing patterns of dominance and buttressed the power of the New York Stock Exchange and NASDAQ’s broker-dealers. These latter colluded, at least by habit and practice, to offer prices in even-eights only, keeping the commission to a quarter of a dollar per trade.[6] At around the same time, the New York Stock Exchange was mired in its own scandals, including the payment of $139m to CEO Richard Grasso as a ‘compensation package’ – the number so big it certainly warrants a euphemism.

The scene is right for a coup, or at the very least a culture war. Just as Tradepoint had set itself up as a self-consciously outside challenger to the LSE, all River Café and Thames Wharf, so in the US a new generation of code-writing techno-libertarians started to play in the markets. Their innovations cracked open the long established monopolies of NASDAQ and the New York Stock Exchange.

A subset of the NASDAQ automated system was the small order execution system, or SOES. After the crash of 1987 when market-makers just stopped processing orders, regulators made it compulsory for brokers to publish quotations and honour them. The unexpected consequence of such a move was that it provided a facility for outsiders to day trade smaller sums in the NASDAQ markets: youngsters in T-shirts and jeans and baseball caps staring at screens and hoping to catch out the brokers with a speedy click here or there. Traders congregated in the offices of firms like Datek with its headquarters in Broad Street, just round the corner from Wall Street. These youngsters became known as SOES bandits, revelling in their outsider status as they needled the established players in ways that transgressed the established etiquette of trading. Tensions often flared. MacKenzie and Pardo-Guerra quote an episode where a member of staff of a NASDAQ broker-dealer located at 43 Broad St, infuriated at being ‘SOES-ed’ by Datek’s traders, crossed to no 50, and barged into Datek’s trading room, screaming ‘You did it again, I’ll fucking kill you!’ He leapt at one of the Datek traders, so a more senior trader picked up a letter opener and stabbed him forcibly, fortunately only in the shoulder. This trading was edgy, all-in, as another colourful detail shows – ‘No one blinked when a chalk-faced guy doubled over a garbage pail and puked violently, never leaving his seat and trading right through the puke’.

Josh Levine was an engineer who tumbled into this world. At Datek, Levine began to build hard and software hacks that avoided more longhand operations, for example allowing quick keystrokes, or hijacking the printer feed from a NASDAQ terminal into a computer system. These eventually became a slick trading system in their own right, helping to crack open the closed shop of the NASDAQ broker dealers: faster, sharper, leaner than anything NASDAQ could provide. A crucial step forward came when Levine realised that he could cut out the expensive NASDAQ dealers altogether by allowing Datek traders to exchange stock between themselves. This required a matching engine, and Levine built one. He called it Island. It had low fees and even offered rebates to those posting sell orders. Levine built systems that worked elegantly from an engineering viewpoint, completely rethinking the organisation of algorithm and exchange, a programmers aesthetic that valued speed and efficiency above all else. Trade time dropped from two seconds to two milliseconds; Island’s engine was so quick that users realised the distance between their own server and the central machine mattered, and the practice of ‘co-locating’ servers in the exchange building – for a fee – appeared.

The offices in Broad Street, Manhattan, maintained the flavour of the dot-com start-up: T-shirts, hoodies, junk food and eccentricities, but soon enough, as MacKenzie and Pardo-Guerra put it, Island became a continent. By 2005, through a series of acquisitions, it had become part of NASDAQ and transformed the giant exchange from the inside out, rebuilding NASDAQ’s technological infrastructure along the Island model. Other programmers moved from Island to exchanges elsewhere and spread the technology as they went. Traces of Levine’s code still flow in the veins of NASDAQ, and his vision of how the engine of the market might work has been enacted worldwide. Order books as we know them today began life on a screen surrounded by junk food wrappers, in the office of a day-trading outfit in a Manhattan backstreet. The hackers won, intellectually at least.

Technological upheaval transformed not just the exchanges, but also their customers. It wasn’t long before the robots arrived, the real world equivalents of Harris’ fearsome algorithm. Program trading, where algorithms made suggestions to brokers, had been around since the mid-eighties. Indeed they had taken some of the blame for Black Monday in 1987, but they still depended on humans to get the orders transacted. Levine’s Island was perfectly suited for entirely automated trading, even down to the hacker-libertarian politics. In another study MacKenzie tells the story of one such firm, based in Charleston, Carolina, set up by academic statisticians who had previously built a model to predict the outcomes of horse races and figured the methodology would transfer to the stock market. In good times the firm came to be one of the leading tech firms in the county, though these good times came and went.

What MacKenzie shows, however, is that for all the barefoot, T-shirt, take on the world hacker aesthetic, the firm only really flourished when it discovered pockets of systematic advantage that were already being exploited by human actors. So, for example, the programmers learnt about the SOES bandits and built an algorithm that mimicked what these humans were doing, looking out for tell-tale signs of big movements in the markets. Then it was a question of machine competing against human, a simple race where the ones outcompeted weren’t the incumbent NASDAQ brokers but the human bandits in Broad Street. Trading at that speed needed a matching engine capable of managing the order flow and the algorithm plugged straight into Island’s, sometimes breaching the order limit of a million trades per day. It was trading figures like these that forced NASDAQ to buy Island, inviting the algorithms into the mainstream. And, of course, once trading becomes a race then only speed matters and everyone has to run; some 90% of global stock trade is now conducted algorithmically.[7]

One of the ironies of high-speed trading is that, just as the market has slipped into the cloud, so designers have had to pay attention to the place where trading actually happens. HFT has foregrounded the brute material from which markets are made, and this material is political. Automated markets are housed in heavily guarded warehouses outside major cities, New Jersey in the US or Slough the United Kingdom. As the market is literally and actually made in these places, the speed with which prices travel back to the trading algorithms is crucial.  Co-location has become a sine qua non of high-frequency trading, with firms paying to locate their boxes as close to the exchange’s engine as possible. Links between exchanges come to matter. Michael Lewis’s book Flash boys is held together by the story of an extraordinary construction project, the building in secret of a fibre-optic link between New York and Chicago, drilling through the Appalachian mountains. Fibre-optic cables had already been laid along the railway track but that bends and twists through the mountains. The few milliseconds that could be saved by travelling in a straight line made the difference between being able to make a profit trading in the markets and never being able to do so. The investors who funded the line could hold traders to ransom. But the speed of light through glass is only two thirds of the speed of light through the air, so rivals have installed chains of microwave dishes between the cities, and finally a major project has built a line as close to the geodesic as possible. It’s faster on a clear day, but slower in the rain, and at certain phases of the moon the line is blocked by the tidal pull on Lake Michigan. We are literally at the limits of physics and yet, as MacKenzie points out, this is an economic arms race of the classic kind: enormously wasteful with huge rents being paid just so players can stay in the game. Even the players can see this: in the middle of describing how engineers have worked day and night to shave five to 10 nanoseconds from the processing time of specialised chips one of MacKenzie’s interviewees pauses to reflect that all that training, all that expertise could have done something else… something different.[8]

Though we might like to think of algorithmic trading as possessing the diabolic intelligence conjured up by Harris, it is much more a case of early bird catching the worm, where early bird is measured in power consumption, heat dissipation, and metres of fibre-optic cable. This in turn has thrown up serious questions about the fairness of high-frequency trading. Michael Lewis argued that we – pension holding, long-term investing citizens – are being scalped by these traders. Part of the difficulty is that algorithms are programmed to spot predictable trades and large buy and sell orders are by their nature predictable, despite the best efforts of brokers to hide them through their own high-speed slicing and dicing. Meanwhile machine learning and huge datasets have started to undo the formal anonymity of electronic exchanges as the most predatory algorithms learn to recognise and outmanoeuvre their more docile cousins.

Even if we do accept the necessity of high-frequency trading there are questions about how much the interaction order that we take for granted in everyday life – queueing, or telling the truth, for example – should transfer into the world of algorithms. In a recent blog, the sociologist Christian Borch has argued that culture is needed to prevent further flash crashes – there have already been several more. He writes about a group of firms working to introduce a better moral culture in algorithms; ‘they strive to eliminate any negative effects their algorithms may have on markets, and they have developed an ethos built on ensuring market integrity in every respect… these firms expend massive, ongoing efforts to comprehend how and why their algorithms behave the way they do, alone and together with other algorithms.’ Makers of algorithms must expend massive efforts to understand how they behave precisely because learning algorithms have a degree of autonomy. Indeed, writes the sociologist Kristian Bondo Hansen, algorithms have a tendency to over learn, making causal associations where there are plainly none and have to be taught to be good scientists, employing Occam’s razor and the principle of parsimonious explanation. AI turns out not to be so I after all. Hansen prefers to explain machine learning algorithms as a means of making sense of the swathes of noisy data that make up contemporary markets, distributed cognitive systems organised and curated by their programmers. But this is a circular defence; as so much of global equities trade is algorithmic, those same algorithms must be the source of that noise and HFT looks like the solution to a problem that it has itself created.[9]

All of which goes to remind us, once again, that stock exchanges have histories and organisational path dependencies that do much to shape their present form. We see in the development of cyber markets the outcome of a series of struggles between established players and new ones. Techno-libertarianism turns out to be just another elite discourse, just as gendered and riddled with privilege as the stock market monopolies it set out to crack open. Suggesting that culture can somehow be imposed upon high-frequency trading from the outside ignores the fact that it is there already: the engineer’s aesthetic, the junk food wrappers and Star Trek posters. And sometimes the establishment wins anyway. The story of PLUS tails off in 2009, with a pyrrhic victory on the courtroom steps after the LSE blocked PLUS from trading AIM stocks; the legal action had exhausted the smaller firm and when the LSE cut its fees its customers drifted back once more. The credit crisis did the rest.

Crisis seems an appropriate place to finish. For all the talk of culture and supervision and care for creation of algorithmic systems, contemporary cyber markets are fragile things. They can move so quickly as to out run even the exchange’s failsafe mechanisms. Hostile trading conditions created by predatory algorithms make it increasingly likely that institutional investors – the eventual users of equity markets – will attempt to trade over-the-counter in a situation that ironically parallels the organisation of AIM. Cyber markets are crisis markets, the material enactment of a narrative the market as a dis-embedded information processor, free from space and time. You can trace this story downwards, from the big ideas of liberal, then neoliberal, economists to the regulation and organization of markets. Or the other way, from the bottom up, through the technological projects of engineers and the mundane wires and circuits of finance through to a conception of markets as giant computers. We should allow both. No idea was born outside of the material world, just as every engineer who thinks markets might be better built has recourse to some imaginings of how things should be organized. Even if they are just ‘one day all of this will be mine.’

I’m Philip Roscoe, and you’ve been listening to How to Build a Stock Exchange. If you’ve enjoyed this episode, please share it. If you’d like to get in touch and join the conversation, you can find me on Twitter @philip_roscoe. Thank you for listening. Join me next time – for the penultimate episode, when we’ll be talking about crisis and exploitation.

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[1] This observation is drawn from Daniel Beunza et al., “Impersonal Efficiency and the Dangers of a Fully Automated Securities Exchange,” in Foresight Driver Review, DR11 (London: Foresight, 2012).

[2] Juan Pablo Pardo-Guerra, Automating Finance: Infrastructures, Engineers, and the Making of Electronic Markets (Oxfoird: Oxford University Press, 2019), 189.

[3] Ibid., 201.

[4] Michie, The London Stock Exchange: A History, 616.

[5] This next section is taken from Philip Roscoe, The Rise and Fall of the Penny-Share Offer: A Historical Sociology of London’s Smaller Company Markets (University of St Andrews, 2017), Other report.

[6] The SEC eventually launched a huge antitrust action against the broker dealers, with damages reported to be $910m in total. see Donald MacKenzie and Juan Pablo Pardo-Guerra, “Insurgent Capitalism: Island, Bricolage and the Re-Making of Finance,” Economy and Society 43, no. 2 (2014).

[7] Adam Hayes, “The Active Construction of Passive Investors: Roboadvisors and Algorithmic ‘Low-Finance’,” Socio-Economic Review  (2019).

[8] Donald MacKenzie, “‘Making’, ‘Taking’ and the Material Political Economy of Algorithmic Trading,” Economy and Society 47, no. 4 (2018): 518.

[9] Kristian Bondo Hansen, “The Virtue of Simplicity: On Machine Learning Models in Algorithmic Trading,” Big Data & Society 7, no. 1 (2020).