Debt: The First Five Thousand Years

By David Graeber

Anthropologist David Graeber argues that it is only with a general historical understanding of debt and its relationship to violence that we can begin to appreciate our emerging epoch. Here he begins to fill in our historical knowledge gap

What follows is a fragment of a much larger project of research on debt and debt money in human history. The first and overwhelming conclusion of this project is that in studying economic history, we tend to systematically ignore the role of violence, the absolutely central role of war and slavery in creating and shaping the basic institutions of what we now call ‘the economy'. What's more, origins matter. The violence may be invisible, but it remains inscribed in the very logic of our economic common sense, in the apparently self-evident nature of institutions that simply would never and could never exist outside of the monopoly of violence - but also, the systematic threat of violence - maintained by the contemporary state.

Let me start with the institution of slavery, whose role, I think, is key. In most times and places, slavery is seen as a consequence of war. Sometimes most slaves actually are war captives, sometimes they are not, but almost invariably, war is seen as the foundation and justification of the institution. If you surrender in war, what you surrender is your life; your conqueror has the right to kill you, and often will. If he chooses not to, you literally owe your life to him; a debt conceived as absolute, infinite, irredeemable. He can in principle extract anything he wants, and all debts - obligations - you may owe to others (your friends, family, former political allegiances), or that others owe you, are seen as being absolutely negated. Your debt to your owner is all that now exists.

This sort of logic has at least two very interesting consequences, though they might be said to pull in rather contrary directions. First of all, as we all know, it is another typical - perhaps defining - feature of slavery that slaves can be bought or sold. In this case, absolute debt becomes (in another context, that of the market) no longer absolute. In fact, it can be precisely quantified. There is good reason to believe that it was just this operation that made it possible to create something like our contemporary form of money to begin with, since what anthropologists used to refer to as ‘primitive money', the kind that one finds in stateless societies (Solomon Island feather money, Iroquois wampum), was mostly used to arrange marriages, resolve blood feuds, and fiddle with other sorts of relations between people, rather than to buy and sell commodities. For instance, if slavery is debt, then debt can lead to slavery. A Babylonian peasant might have paid a handy sum in silver to his wife's parents to officialise the marriage, but he in no sense owned her. He certainly couldn't buy or sell the mother of his children. But all that would change if he took out a loan. Were he to default, his creditors could first remove his sheep and furniture, then his house, fields and orchards, and finally take his wife, children, and even himself as debt peons until the matter was settled (which, as his resources vanished, of course became increasingly difficult to do). Debt was the hinge that made it possible to imagine money in anything like the modern sense, and therefore, also, to produce what we like to call the market: an arena where anything can be bought and sold, because all objects are (like slaves) disembedded from their former social relations and exist only in relation to money.

But at the same time the logic of debt as conquest can, as I mentioned, pull another way. Kings, throughout history, tend to be profoundly ambivalent towards allowing the logic of debt to get completely out of hand. This is not because they are hostile to markets. On the contrary, they normally encourage them, for the simple reason that governments find it inconvenient to levy everything they need (silks, chariot wheels, flamingo tongues, lapis lazuli) directly from their subject population; it's much easier to encourage markets and then buy them. Early markets often followed armies or royal entourages, or formed near palaces or at the fringes of military posts. This actually helps explain the rather puzzling behavior on the part of royal courts: after all, since kings usually controlled the gold and silver mines, what exactly was the point of stamping bits of the stuff with your face on it, dumping it on the civilian population, and then demanding they give it back to you again as taxes? It only makes sense if levying taxes was really a way to force everyone to acquire coins, so as to facilitate the rise of markets, since markets were convenient to have around. However, for our present purposes, the critical question is: how were these taxes justified? Why did subjects owe them, what debt were they discharging when they were paid? Here we return again to right of conquest. (Actually, in the ancient world, free citizens - whether in Mesopotamia, Greece, or Rome - often did not have to pay direct taxes for this very reason, but obviously I'm simplifying here.) If kings claimed to hold the power of life and death over their subjects by right of conquest, then their subjects' debts were, also, ultimately infinite; and also, at least in that context, their relations to one another, what they owed to one another, was unimportant. All that really existed was their relation to the king. This in turn explains why kings and emperors invariably tried to regulate the powers that masters had over slaves, and creditors over debtors. At the very least they would always insist, if they had the power, that those prisoners who had already had their lives spared could no longer be killed by their masters. In fact, only rulers could have arbitrary power over life and death. One's ultimate debt was to the state; it was the only one that was truly unlimited, that could make absolute, cosmic, claims.

The reason I stress this is because this logic is still with us. When we speak of a ‘society' (French society, Jamaican society) we are really speaking of people organised by a single nation state. That is the tacit model, anyway. ‘Societies' are really states, the logic of states is that of conquest, the logic of conquest is ultimately identical to that of slavery. True, in the hands of state apologists, this becomes transformed into a notion of a more benevolent ‘social debt'. Here there is a little story told, a kind of myth. We are all born with an infinite debt to the society that raised, nurtured, fed and clothed us, to those long dead who invented our language and traditions, to all those who made it possible for us to exist. In ancient times we thought we owed this to the gods (it was repaid in sacrifice, or, sacrifice was really just the payment of interest - ultimately, it was repaid by death). Later the debt was adopted by the state, itself a divine institution, with taxes substituted for sacrifice, and military service for one's debt of life. Money is simply the concrete form of this social debt, the way that it is managed. Keynesians like this sort of logic. So do various strains of socialist, social democrats, even crypto-fascists like Auguste Comte (the first, as far as I am aware, to actually coin the phrase ‘social debt'). But the logic also runs through much of our common sense: consider for instance, the phrase, ‘to pay one's debt to society', or, ‘I felt I owed something to my country', or, ‘I wanted to give something back.' Always, in such cases, mutual rights and obligations, mutual commitments - the kind of relations that genuinely free people could make with one another - tend to be subsumed into a conception of ‘society' where we are all equal only as absolute debtors before the (now invisible) figure of the king, who stands in for your mother, and by extension, humanity.

What I am suggesting, then, is that while the claims of the impersonal market and the claims of ‘society' are often juxtaposed - and certainly have had a tendency to jockey back and forth in all sorts of practical ways - they are both ultimately founded on a very similar logic of violence. Neither is this a mere matter of historical origins that can be brushed away as inconsequential: neither states nor markets can exist without the constant threat of force.

One might ask, then, what is the alternative?

Towards a History of Virtual Money

Here I can return to my original point: that money did not originally appear in this cold, metal, impersonal form. It originally appears in the form of a measure, an abstraction, but also as a relation (of debt and obligation) between human beings. It is important to note that historically it is commodity money that has always been most directly linked to violence. As one historian put it, ‘bullion is the accessory of war, and not of peaceful trade.'¹

The reason is simple. Commodity money, particularly in the form of gold and silver, is distinguished from credit money most of all by one spectacular feature: it can be stolen. Since an ingot of gold or silver is an object without a pedigree, throughout much of history bullion has served the same role as the contemporary drug dealer's suitcase full of dollar bills, as an object without a history that will be accepted in exchange for other valuables just about anywhere, with no questions asked. As a result, one can see the last 5,000 years of human history as the history of a kind of alternation. Credit systems seem to arise, and to become dominant, in periods of relative social peace, across networks of trust, whether created by states or, in most periods, transnational institutions, whilst precious metals replace them in periods characterised by widespread plunder. Predatory lending systems certainly exist at every period, but they seem to have had the most damaging effects in periods when money was most easily convertible into cash.

So as a starting point to any attempt to discern the great rhythms that define the current historical moment, let me propose the following breakdown of Eurasian history according to the alternation between periods of virtual and metal money:

I. Age of the First Agrarian Empires (3500-800 BCE)

Dominant money form: virtual credit money

Our best information on the origins of money goes back to ancient Mesopotamia, but there seems no particular reason to believe matters were radically different in Pharaonic Egypt, Bronze Age China, or the Indus Valley. The Mesopotamian economy was dominated by large public institutions (Temples and Palaces) whose bureaucratic administrators effectively created money of account by establishing a fixed equivalent between silver and the staple crop, barley. Debts were calculated in silver, but silver was rarely used in transactions. Instead, payments were made in barley or in anything else that happened to be handy and acceptable. Major debts were recorded on cuneiform tablets kept as sureties by both parties to the transaction.

Certainly, markets did exist. Prices of certain commodities that were not produced within Temple or Palace holdings, and thus not subject to administered price schedules, would tend to fluctuate according to the vagaries of supply and demand. But most actual acts of everyday buying and selling, particularly those that were not carried out between absolute strangers, appear to have been made on credit. ‘Ale women', or local innkeepers, served beer, for example, and often rented rooms; customers ran up a tab; normally, the full sum was dispatched at harvest time. Market vendors presumably acted as they do in small scale markets in Africa, or Central Asia, today, building up lists of trustworthy clients to whom they could extend credit.

The habit of money at interest also originates in Sumer - it remained unknown, for example, in Egypt. Interest rates, fixed at 20 percent, remained stable for 2,000 years. (This was not a sign of government control of the market: at this stage, institutions like this were what made markets possible.) This, however, led to some serious social problems. In years with bad harvests especially, peasants would start becoming hopelessly indebted to the rich, and would have to surrender their farms and, ultimately, family members, in debt bondage. Gradually, this condition seems to have come to a social crisis - not so much leading to popular uprisings, but to common people abandoning the cities and settled territory entirely and becoming semi-nomadic ‘bandits' and raiders. It soon became traditional for each new ruler to wipe the slate clean, cancel all debts, and declare a general amnesty or ‘freedom', so that all bonded labourers could return to their families. (It is significant here that the first word for ‘freedom' known in any human language, the Sumerian amarga, literally means ‘return to mother'.) Biblical prophets instituted a similar custom, the Jubilee, whereby after seven years all debts were similarly cancelled. This is the direct ancestor of the New Testament notion of ‘redemption'. As economist Michael Hudson has pointed out, it seems one of the misfortunes of world history that the institution of lending money at interest disseminated out of Mesopotamia without, for the most part, being accompanied by its original checks and balances.

II. Axial Age (800 BCE - 600 CE)

Dominant money form: coinage and metal bullion

This was the age that saw the emergence of coinage, as well as the birth, in China, India and the Middle East, of all major world religions.² From the Warring States period in China, to fragmentation in India, and to the carnage and mass enslavement that accompanied the expansion (and later, dissolution) of the Roman Empire, it was a period of spectacular creativity throughout most of the world, but of almost equally spectacular violence.

Coinage, which allowed for the actual use of gold and silver as a medium of exchange, also made possible the creation of markets in the now more familiar, impersonal sense of the term. Precious metals were also far more appropriate for an age of generalised warfare, for the obvious reason that they could be stolen. Coinage, certainly, was not invented to facilitate trade (the Phoenicians, consummate traders of the ancient world, were among the last to adopt it). It appears to have been first invented to pay soldiers, probably first of all by rulers of Lydia in Asia Minor to pay their Greek mercenaries. Carthage, another great trading nation, only started minting coins very late, and then explicitly to pay its foreign soldiers.

Throughout antiquity one can continue to speak of what Geoffrey Ingham has dubbed the ‘military-coinage complex'. He may have been better to call it a ‘military-coinage-slavery complex', since the diffusion of new military technologies (Greek hoplites, Roman legions) was always closely tied to the capture and marketing of slaves. The other major source of slaves was debt: now that states no longer periodically wiped the slates clean, those not lucky enough to be citizens of the major military city-states - who were generally protected from predatory lenders - were fair game. The credit systems of the Near East did not crumble under commercial competition; they were destroyed by Alexander's armies - armies that required half a ton of silver bullion per day in wages. The mines where the bullion was produced were generally worked by slaves. Military campaigns in turn ensured an endless flow of new slaves. Imperial tax systems, as noted, were largely designed to force their subjects to create markets, so that soldiers (and also, of course, government officials) would be able to use that bullion to buy anything they wanted. The kind of impersonal markets that once tended to spring up between societies, or at the fringes of military operations, now began to permeate society as a whole.

However tawdry their origins, the creation of new media of exchange - coinage appeared almost simultaneously in Greece, India, and China - appears to have had profound intellectual effects. Some have even gone so far as to argue that Greek philosophy was itself made possible by conceptual innovations introduced by coinage. The most remarkable pattern, though, is the emergence, in almost the exact times and places where one also sees the early spread of coinage, of what were to become modern world religions: prophetic Judaism, Christianity, Buddhism, Jainism, Confucianism, Taoism, and eventually, Islam. While the precise links are yet to be fully explored, in certain ways, these religions appear to have arisen in direct reaction to the logic of the market. To put the matter somewhat crudely: if one relegates a certain social space simply to the selfish acquisition of material things, it is almost inevitable that soon someone else will come to set aside another domain in which to preach that, from the perspective of ultimate values, material things are unimportant, and selfishness - or even the self - illusory.

III. The Middle Ages (600 CE - 1500 CE)³

The return to virtual credit money

If the Axial Age saw the emergence of complementary ideals of commodity markets and universal world religions, the Middle Ages were the period in which those two institutions began to merge. Religions began to take over the market systems. Everything from international trade to the organisation of local fairs increasingly came to be carried out through social networks defined and regulated by religious authorities. This enabled, in turn, the return throughout Eurasia of various forms of virtual credit money.

In Europe, where all this took place under the aegis of Christendom, coinage was only sporadically, and unevenly, available. Prices after 800 AD were calculated largely in terms of an old Carolingian currency that no longer existed (it was actually referred to at the time as ‘imaginary money'), but ordinary day-to-day buying and selling was carried out mainly through other means. One common expedient, for example, was the use of tally-sticks, notched pieces of wood that were broken in two as records of debt, with half being kept by the creditor, half by the debtor. Such tally-sticks were still in common use in much of England well into the 16th century. Larger transactions were handled through bills of exchange, with the great commercial fairs serving as their clearing houses. The Church, meanwhile, provided a legal framework, enforcing strict controls on the lending of money at interest and prohibitions on debt bondage.

The real nerve centre of the Medieval world economy, though, was the Indian Ocean, which along with the Central Asia caravan routes connected the great civilisations of India, China, and the Middle East. Here, trade was conducted through the framework of Islam, which not only provided a legal structure highly conducive to mercantile activities (while absolutely forbidding the lending of money at interest), but allowed for peaceful relations between merchants over a remarkably large part of the globe, allowing the creation of a variety of sophisticated credit instruments. Actually, Western Europe was, as in so many things, a relative late-comer in this regard: most of the financial innovations that reached Italy and France in the 11th and 12th centuries had been in common use in Egypt or Iraq since the 8th or 9th centuries. The word ‘cheque', for example, derives from the Arab sakk, and appeared in English only around 1220 AD.

The case of China is even more complicated: the Middle Ages there began with the rapid spread of Buddhism, which, while it was in no position to enact laws or regulate commerce, did quickly move against local usurers by its invention of the pawn shop - the first pawn shops being based in Buddhist temples as a way of offering poor farmers an alternative to the local usurer. Before long, though, the state reasserted itself, as the state always tends to do in China. But as it did so, it not only regulated interest rates and attempted to abolish debt peonage, it moved away from bullion entirely by inventing paper money. All this was accompanied by the development, again, of a variety of complex financial instruments.

All this is not to say that this period did not see its share of carnage and plunder (particularly during the great nomadic invasions) or that coinage was not, in many times and places, an important medium of exchange. Still, what really characterises the period appears to be a movement in the other direction. Most of the Medieval period saw money largely delinked from coercive institutions. Money changers, one might say, were invited back into the temples, where they could be monitored. The result was a flowering of institutions premised on a much higher degree of social trust.

IV. Age of European Empires (1500-1971)

The return of precious metals

With the advent of the great European empires - Iberian, then North Atlantic - the world saw both a reversion to mass enslavement, plunder, and wars of destruction, and the consequent rapid return of gold and silver bullion as the main form of currency. Historical investigation will probably end up demonstrating that the origins of these transformations were more complicated than we ordinarily assume. Some of this was beginning to happen even before the conquest of the New World. One of the main factors of the movement back to bullion, for example, was the emergence of popular movements during the early Ming dynasty, in the 15th and 16th centuries, that ultimately forced the government to abandon not only paper money but any attempt to impose its own currency. This led to the reversion of the vast Chinese market to an uncoined silver standard. Since taxes were also gradually commuted into silver, it soon became the more or less official Chinese policy to try to bring as much silver into the country as possible, so as to keep taxes low and prevent new outbreaks of social unrest. The sudden enormous demand for silver had effects across the globe. Most of the precious metals looted by the conquistadors and later extracted by the Spanish from the mines of Mexico and Potosi (at almost unimaginable cost in human lives) ended up in China. These global scale connections that eventually developed across the Atlantic, Pacific, and Indian Oceans have of course been documented in great detail. The crucial point is that the delinking of money from religious institutions, and its relinking with coercive ones (especially the state), was here accompanied by an ideological reversion to ‘metallism'.⁴

Credit, in this context, was on the whole an affair of states that were themselves run largely by deficit financing, a form of credit which was, in turn, invented to finance increasingly expensive wars. Internationally the British Empire was steadfast in maintaining the gold standard through the 19th and early 20th centuries, and great political battles were fought in the United States over whether the gold or silver standard should prevail.

This was also, obviously, the period of the rise of capitalism, the industrial revolution, representative democracy, and so on. What I am trying to do here is not to deny their importance, but to provide a framework for seeing such familiar events in a less familiar context. It makes it easier, for instance, to detect the ties between war, capitalism, and slavery. The institution of wage labour, for instance, has historically emerged from within that of slavery (the earliest wage contracts we know of, from Greece to the Malay city states, were actually slave rentals), and it has also tended, historically, to be intimately tied to various forms of debt peonage - as indeed it remains today. The fact that we have cast such institutions in a language of freedom does not mean that what we now think of as economic freedom does not ultimately rest on a logic that has for most of human history been considered the very essence of slavery.

V. Current Era (1971 onwards)

The empire of debt

The current era might be said to have been initiated on 15 August 1971, when US President Richard Nixon officially suspended the convertibility of the dollar into gold and effectively created the current floating currency regimes. We have returned, at any rate, to an age of virtual money, in which consumer purchases in wealthy countries rarely involve even paper money, and national economies are driven largely by consumer debt. It's in this context that we can talk about the ‘financialisation' of capital, whereby speculation in currencies and financial instruments becomes a domain unto itself, detached from any immediate relation with production or even commerce. This is of course the sector that has entered into crisis today.

What can we say for certain about this new era? So far, very, very little. Thirty or forty years is nothing in terms of the scale we have been dealing with. Clearly, this period has only just begun. Still, the foregoing analysis, however crude, does allow us to begin to make some informed suggestions.

Historically, as we have seen, ages of virtual, credit money have also involved creating some sort of overarching institutions - Mesopotamian sacred kingship, Mosaic jubilees, Sharia or Canon Law - that place some sort of controls on the potentially catastrophic social consequences of debt. Almost invariably, they involve institutions (usually not strictly coincident to the state, usually larger) to protect debtors. So far the movement this time has been the other way around: starting with the '80s we have begun to see the creation of the first effective planetary administrative system, operating through the IMF, World Bank, corporations and other financial institutions, largely in order to protect the interests of creditors. However, this apparatus was very quickly thrown into crisis, first by the very rapid development of global social movements (the alter-globalisation movement), which effectively destroyed the moral authority of institutions like the IMF and left many of them very close to bankrupt, and now bsy the current banking crisis and global economic collapse. While the new age of virtual money has only just begun and the long term consequences are as yet entirely unclear, we can already say one or two things. The first is that a movement towards virtual money is not in itself, necessarily, an insidious effect of capitalism. In fact, it might well mean exactly the opposite. For much of human history, systems of virtual money were designed and regulated to ensure that nothing like capitalism could ever emerge to begin with - at least not as it appears in its present form, with most of the world's population placed in a condition that would in many other periods of history be considered tantamount to slavery. The second point is to underline the absolutely crucial role of violence in defining the very terms by which we imagine both ‘society' and ‘markets' - in fact, many of our most elementary ideas of freedom. A world less entirely pervaded by violence would rapidly begin to develop other institutions. Finally, thinking about debt outside the twin intellectual straitjackets of state and market opens up exciting possibilities. For instance, we can ask: in a society in which that foundation of violence had finally been yanked away, what exactly would free men and women owe each other? What sort of promises and commitments should they make to each other?

Let us hope that everyone will someday be in a position to start asking such questions. At times like this, you never know.

David Graeber undertook his original research in the relations between former nobles and former slaves in a rural community in Madagascar; it was about magic as a tool of politics, about the nature of power, character, and the meaning of history. He has recently completed a research project on social movements dedicated to principles of direct democracy and has written widely on the relation between anthropology and anarchism. He is currently working on a project about the history of debt

Footnotes

1 Geoffrey W. Gardiner, ‘The Primacy of Trade Debts in the Development of Money', in Randall Wray (ed.), Credit and State Theories of Money: The Contributions of A. Mitchell Innes, Cheltenham: Elgar, 2004, p.134.

2 The phrase the ‘Axial Age' was originally coined by Karl Jaspers to describe the relatively brief period between 800 BCE - 200 BCE in which, he believed, just about all the main philosophical traditions we are familiar with today arose simultaneously in China, India, and the Eastern Mediterranean. Here, I am using it in Lewis Mumford's more expansive use of the term as the period that saw the birth of all existing world religions, stretching roughly from the time of Zoroaster to that of Mohammed.

3 I am here relegating most of what is generally referred to as the ‘Dark Ages' in Europe into the earlier period, characterised by predatory militarism and the consequent importance of bullion: the Viking raids, and the famous extraction of danegeld from England in the 800s, might be seen as one the last manifestations of an age where predatory militarism went hand and hand with hoards of gold and silver bullion.

4 The myth of barter and commodity theories of money was of course developed in this period.

Inside the Machine: A Journey into the World of High-Frequency Trading - Michael Peltz - Institutional Investor

An editor's journey into the world of high-speed trading and proprietary algorithms that make or break markets.

At 2:45p.m. on Thursday, May 6, George (Gus) Sauter received a frantic call from one of his traders to get in front of a Bloomberg terminal. The Dow Jones industrial average, already down 3.9 percent that day on fears about Greece, was in free fall. In just five minutes the index plunged 573 points. Less than two minutes later, the Dow had rocketed back up 543 points, going on to finish the day down 3.2 percent.

“It was just crazy,” Sauter, chief investment officer of mutual fund giant Vanguard Group, told me a few days later. “I had to go to our fixed-income building, about a five-minute walk from my office. By the time I got there, the market had rallied.”

Crazy, indeed. The aptly named “flash crash” temporarily wiped out more than a half trillion dollars in equity value, shaking what little faith nervous investors had in U.S. markets. Shares of Dow component Procter & Gamble Co., the ultimate defensive blue-chip stock, dropped more than one third in a matter of minutes before recovering almost as quickly, all for no apparent reason. A few other large U.S. companies, including accounting firm Accenture, saw their stocks trade as low as a penny a share, only to close not far from where they had begun the day (nearly $42 a share in the case of Accenture) — again, on no news. By the time the dust settled, a whopping 19.3 billion shares had changed hands, more than twice the average daily U.S. equity market volume this year and the second-biggest trading day ever.

But for me, the single most amazing fact about the flash crash was that no one had a clue as to what had triggered it. Not that I should have been surprised, based on the conversation I’d had two days earlier with Mary Schapiro, chairman of the Securities and Exchange Commission. Schapiro, whose organization is charged with maintaining “fair and orderly” markets, explained to me how the SEC did a detailed study after the October 1987 crash to reconstruct what had happened. “We’ve lost some of the capacity to do that given the dramatic volumes of trading that exist today,” Schapiro said. “But we need to be able to do that to understand where are the vulnerabilities in our marketplace and what are the practices that have the potential to hurt investors and the marketplace in the long run.”

In 1987 the SEC had a much easier task because the vast majority of listed U.S. equities were traded in one place — on the floor of the New York Stock Exchange, where specialists employed by the Big Board’s member firms made a market based on an open-outcry auction system. Today, as a result of a series of regulatory changes designed to increase competition and make the market fairer for mom-and-pop investors, only about one quarter of all U.S. equity trading occurs through the now publicly held NYSE Euronext. And the majority of that trading is done electronically, either by the new NYSE floor specialists, called designated market makers, or on the fully automated NYSE Arca platform. The rest of the trading in U.S. equities is spread across a wide range of venues, including the three other major exchanges (Nasdaq Stock Market, BATS Exchange and Direct Edge) and dozens of broker-dealer-operated trading systems, electronic communications networks (ECNs) and dark pools, where buyers and sellers are matched up anonymously.

[Click here to view the Top 25 Most-Favored Stocks In High-Frequency Trading.]

The past decade of fragmentation and automation has given rise to a whole new type of professional trading firm: one that uses sophisticated computer algorithms, often running on servers housed right next to exchanges’ own machines, and high-speed market data feeds to buy and sell securities in rapid-fire fashion. Some of these high frequency traders place hundreds of millions, even billions, of buy and sell orders a day, continually canceling and replacing them, and are likely to be on the other side of your trade. Not that you’d know who they are — proprietary trading firms are not required to disclose their identity — or recognize their names. The bulge bracket of high frequency trading includes firms like Allston Trading, DRW Holdings, Global Electronic Trading Co. (Getco), Hudson River Trading, Quantlab Financial, RGM Advisors, Sun Trading, Tower Research Capital and Tradebot Systems.

High frequency trading has become a multibillion-dollar business, accounting for an estimated 50 to 70 percent of the total U.S. equity market volume on any given day. Since last summer it has also been a lightning rod for the populist anger directed at Wall Street, despite the fact that most of the largest high frequency firms operate far from the canyons of lower Manhattan, in places like Chicago, Kansas City and Austin, Texas. Critics accuse high frequency traders of being fair-weather market makers who, unlike the former NYSE specialists they’ve largely replaced, don’t have a legal obligation to trade during periods of stress. They also say that the growth in high frequency trading has created a two-tiered market of technology haves and have-nots that is unfair to long-term investors and poses potential systemic risks.

I grew interested in high frequency trading last year when I was writing a feature on hedge fund firm Citadel Investment Group (more on that later). As an editor, however, it wasn’t until January that I was able to dig into what I soon learned is an incredibly arcane world. My first stop was a company called Pragma Securities, an agency-only brokerage firm that aggregates more than 40 different dark pools, electronic trading venues and open market destinations into a single liquidity source for clients. Douglas Rivelli and David Mechner, Pragma’s co-CEOs, spent two hours at the firm’s spacious New York offices taking me through that world.

High frequency traders, Rivelli and Mechner explained, generally fall into one of two camps: proprietary trading shops that act as electronic market makers, using computers to generate and adjust buy and sell orders automatically throughout the day, and hedge funds that specialize in statistical arbitrage, seeking to exploit pricing inefficiencies among different securities and asset classes. The distinctions between the two sometimes blur, however, as proprietary trading firms often try to capitalize on some of the same buy and sell signals that statistical arbitrageurs use and hedge funds trade on ever-shorter time horizons. High frequency firms are best known for trading equities, but they also trade futures, options and foreign exchange — basically, anything that can be traded electronically. High frequency trading is also an increasingly global phenomenon, gaining ground in both Europe and Asia.

One thing is clear: Hedge funds don’t like to be called high frequency traders, as I quickly discovered after visiting with some of the biggest quantitative managers, including AQR Capital Management in Greenwich, Connecticut, and D.E. Shaw & Co. and Renaissance Technologies Corp. in New York.

In the wake of the flash crash, as people scrambled to determine what had triggered the market plunge, it didn’t take much longer than the 400 to 600 microseconds (millionths of a second) that high frequency traders typically need to identify and place a trade for fingers to start pointing at them. “The potential for giant high-speed computers to generate false trades and create market chaos reared its head again today,” Delaware Senator Ted Kaufman said in a statement released that same afternoon. When I caught up with the Democratic lawmaker a week later, he was even more incensed, pointing out that regulators still didn’t know what had caused the flash crash.

“We have a 300-pound gorilla in the room, and we’re saying that we’re going to keep it in a cage somewhere,” he told me. “This thing will be 600 pounds.”

“But isn’t part of the problem that there are 300 gorillas?” I asked, referring to the fact that an estimated 200 to 400 firms do high frequency trading.

“Good point,” he replied. “We have all these gorillas, and guess what? We put them in zoos where the people running the zoos don’t have enough information and authority to take care of them.”

Kaufman’s interest in high frequency trading predates mine. When he was sworn into office in January 2009 to fill the Senate seat of his former boss Joe Biden, Kaufman was hell-bent on making sure that everybody responsible for the 2008 market meltdown paid for their actions. He soon focused on short-selling, urging the SEC to reinstate the uptick rule requiring short sales to be filled at a higher price; the rule had been eliminated in 2007. He told me that when he was in business school in the 1960s, it was “an article of faith” that the uptick rule was “one of the two or three things that helped deal with predatory bear raids.” As a result of his interest in short-selling, Kaufman said, his office started getting calls from some fairly sophisticated people, including former Wall Streeters, telling him that if he thought that practice was bad, he should look at high frequency trading.

Kaufman likes to draw an analogy between high frequency trading and the swaps market. “With synthetic derivatives, you had a lot of money at stake, no transparency and then a major meltdown,” he explained to me. “If you look at high frequency trading, I think the same Kaufman formula works.”

A graduate of the Wharton School of the University of Pennsylvania, the 71-year-old Kaufman is a quick study and understands markets. If I were a high frequency trader, I’d take him seriously.

Kaufman has been high frequency trading’s loudest critic. But he’s far from alone. Seth Merrin, founder and CEO of Liquidnet Holdings, which operates an electronic marketplace that provides block trading for institutional investors, likes to compare high frequency traders to the American army during the Revolutionary War. “The institutions are the equivalent of the British army, walking down the battlefield wearing bright red,” he told me back in March in his glass-enclosed office at Liquidnet’s sleek midtown Manhattan headquarters. “The high frequency traders are the Americans hiding in the woods in camouflage, picking them off. If the British army hadn’t changed its tactics, they would have lost every subsequent war.”

Even Duncan Niederauer, who as the pragmatic CEO of NYSE Euronext has been retooling his exchange to attract more business from high frequency traders, took a swipe at them. “We as an industry have to say how much is too much of this technology,” he said during an interview on CNBC after the flash crash, undoubtedly causing some consternation among the folks at NYSE Euronext who are selling space in the company’s new, 400,000-square-foot data center and co-location facility in Mahwah, New Jersey.

High frequency traders say that any efforts to rein in technology would be misplaced. Although speed is important to what they do, the quality of a firm’s computer models for analyzing markets and identifying where and at what price to buy and sell securities is what really determines success or failure, they argue. In their defense, high frequency traders say that they increase liquidity, lower trading costs, improve price discovery and reduce risk by dampening short-term volatility.

“High frequency trading is the liquidity backbone of the equity markets,” Manoj Narang, the founder, CEO and chief investment strategist of Tradeworx, told me when I first met him, in early March. “Long-term investors are the ones who cause bubbles, as well as liquidity crises when these bubbles burst.”

Narang, 40, is one of only a handful of proprietary traders I found willing to talk openly with a journalist about what they do. Most prefer to operate in the shadows, both to protect their valuable algorithms and to avoid regulatory scrutiny. But Narang, who left Wall Street in 1999 to start Tradeworx, sought me out when he heard through a public relations contact this winter that I was working on a story on high frequency trading. His 25-person firm, which operates out of an office above a Restoration Hardware store in Red Bank, New Jersey, trades about 40 million shares a day on about $6 million in proprietary capital. Tradeworx also runs a $500 million statistical arbitrage hedge fund (which trades another 40 million shares a day) and owns a subsidiary, Thesys Technologies, which licenses its high-performance trading platform to other investors.

Narang lifted his profile on May 6 when he revealed to the Wall Street Journal that his firm turned off its high frequency trading computers during the flash crash. Tradeworx wasn’t the only one to do so. Kansas City–based Tradebot, started by BATS founder David Cummings, also stopped trading. Tradebot is one of the world’s two largest high frequency firms, reportedly trading as many as 1 billion shares a day in U.S. equities. Only Chicago-based Getco is thought to be bigger. Although Getco won’t comment on its daily trading volume, a spokeswoman for the firm did tell me that it continued to provide a two-sided market on all the electronic exchanges during the flash crash.

Most high frequency traders, in fact, kept their computers running, according to Jeffrey Wecker, president and CEO of Lime Brokerage. Wecker should know. His firm, which accounts for as much as 5 percent of the daily equity trading volume in the U.S., is the oldest and largest provider of high-speed trading solutions and access to all major U.S. exchanges for high frequency traders.

The high frequency firms that did stop trading on May 6 have been criticized for contributing to the decline by pulling liquidity from the market when it was needed most. But Narang told me that his firm had no choice because the exchanges were likely to cancel, or break, trades that were clearly erroneous (like selling Accenture at a penny a share). “If the exchanges broke all our buys and not our sells, we could have exceeded our capital requirements,” he explained. “We didn’t want to take the risk. The high frequency traders who continued to trade that afternoon made a fortune.”

IN JANUARY THE SEC PUBLISHED A CONCEPT RELEASE on equity market structure, seeking public comment on everything from high frequency trading strategies and systemic risks to co-location and dark pools. At 74 pages, the report might seem like a real snoozer, but it’s actually a great primer on how the U.S. equity markets have responded to regulatory changes, starting in 1996 with the adoption of “order-handling” rules. These new rules, which were designed to make the markets fairer following the Nasdaq price-fixing scandal in the mid-’90s, created ECNs and gave them the power to publish their stock quotes publicly alongside those of the listed markets. In 1999, Regulation Alternative Trading System (ATS) went into effect, enabling ECNs to operate as market centers without having to register as exchanges. By the following year ECNs like Island and Archipelago had taken about one third of market makers’ volume in Nasdaq-listed stocks. But it wasn’t until after April 2001 — the deadline the SEC mandated for all U.S. exchanges to switch from fractions to decimals — that electronic trading really started to take off.

As bid-offer spreads shrunk and competition increased, ECNs and exchanges adopted a “maker-taker” pricing scheme to attract liquidity. Under the maker-taker model, market participants that offer to provide, or make, liquidity by posting an order to buy or sell a certain number of shares at a particular price receive a rebate. Those that execute against that order — that is, take the liquidity — have to pay a fee. Exchanges earn the difference between the rebate they pay and the fee they charge. The SEC limits taker fees to 0.30 cents a share; rebates tend to be lower for economic reasons, but for high frequency firms trading millions of shares a day, they can make for a pretty good living.

“The maker-taker model created an arbitrage that provided incentive for those firms that could properly blend together knowledge of trading, financial economics and computers all into a single, scalable system that could handle high volumes of transactions,” Lime Brokerage CEO Wecker told me back in April when we met at his firm’s Greenwich Village offices.

The final major regulatory change was Regulation NMS (for “National Market System”), which was passed by the SEC in 2005 and went into effect in 2007. One of the key pieces of Reg NMS is the “trade-through” rule prohibiting any exchange from executing a trade at an inferior price to one quoted at another trading venue. Trade-through protection is critical for high frequency traders; it ensures that if they are the first to post the best price for a stock, they’ll get the trade.

“High frequency trading is a product of Reg NMS, decimalization and technology improvements,” says John Knuff, general manager of global financial markets for Equinix, a Foster City, California–based company that runs 87 data centers in 35 key metropolitan areas around the world. “High frequency traders are the democratic enforcers of Reg NMS’s trade-through rules.”

Under Reg NMS, exchanges are required to handle electronic orders immediately or risk having them redirected to other venues. Once the rule was adopted, the NYSE — which even after decimalization had been clinging desperately to its manual specialist system — had no choice but to embrace automation. In 2007 the NYSE switched to a system it called the Hybrid Market, expanding its automatic execution facility, Direct+, and giving specialists the power to create their own algorithms to quote and trade electronically. The hybrid system included circuit breakers, called liquidity replenishment points, that would be triggered if a stock experienced a large price swing, at which time automated trading would stop and human specialists would step in.

That’s exactly what happened on the afternoon of May 6, when the NYSE imposed a trading slowdown in Big Board stocks like P&G and Accenture. Investors who wanted to sell or buy were forced to go to other electronic exchanges or ECNs. Although Nasdaq OMX Group CEO Robert Greifeld and other competitors criticized the NYSE on May 6 for making the meltdown worse, NYSE Euronext CEO Niederauer staunchly defended its actions, pointing out that the exchange did exactly what it should have under Reg NMS. He was vindicated two weeks later when the SEC proposed instituting similar circuit breakers for all exchanges that would pause trading in any stock in the Standard & Poor’s 500 index if its price moved 10 percent or more in a five-minute period. The new circuit breaker rule, which is likely to be approved by the SEC this month, would go into effect on a pilot basis through December 10, at which point the regulator could expand it to other stocks and exchange-traded funds.

“When a stock gets overheated, some form of stock-specific circuit breaker is a very effective means for letting information repopulate in the marketplace,” Lime’s Wecker told me a few days after the flash crash. He advocates an initial short-term cooling-off period measured in seconds or minutes; if a stock suffers a subsequent steep decline in price, the next halt would be longer.

Like many of the people I have interviewed about high frequency trading over the past five months, Wecker is concerned that regulators could try to rein in the practice by putting limits on technology. After all, his business is built on speed. “The challenge with speed bumps is that you are slowing down innovation to accommodate the players who have no interest in investing in innovation,” says Wecker, 47, who spent 11 years at Goldman, Sachs & Co., including six in its famed quantitative trading group, before eventually moving to Lehman Brothers to build its electronic trading group. He left Lehman in April 2008, five months before the investment bank filed for bankruptcy, and was hired by Lime founder Mark Gorton that November.

Lime handles hundreds of millions of trade orders a day. This spring it introduced a product called LimeInside that enables customers to place an order with Nasdaq, NYSE Arca and BATS in less than ten microseconds, on average — including real-time pretrade risk checks. That’s blazingly fast, confirms Tradeworx CEO Narang. It takes his group about 20 microseconds to do a trade from the moment a stock quote enters its system, triggers a signal, determines an order and passes through risk controls. Besides Lime, the only firms that are faster than Tradeworx, Narang says, are Tradebot and Getco.

Trading in the single-digit microseconds would be impossible for firms like Lime, Tradebot and Getco if they didn’t house their algorithms near the computer matching engines that power exchanges, ECNs and other electronic marketplaces. Brokerages, proprietary trading firms, hedge funds and other asset managers can lease co-location space in exchange-owned facilities (such as the NYSE’s Mahwah data center) or those owned and operated by third-party providers like Equinix.

Co-location has been a hot-button issue for critics of high frequency trading. I wonder, however, how many have actually visited a co-location facility. In March I got the chance to do just that at Equinix’s 340,000-square-foot NY4 data center in Secaucus, New Jersey. My host was Brandon Travan, head of the information technology infrastructure, co-location and cloud-hosting services divisions for Gravitas Technology, one of the growing number of companies that provide turnkey technology solutions for high frequency traders — and one of the first tenants at NY4.

From the outside, the white, two-story, unmarked building, located 11 miles west of downtown Manhattan in an area known best for outlet shopping, looks like a suburban medical office or law firm. (I later learned that it had been an eyeglass factory.) The lobby is equally nondescript, if not a little odd — there’s not much more than a phone, a plain steel door and a biometric hand scanner. After dialing in a personal code matched against the geometry of his hand, Travan got us into an inner lobby, where three security guards sat behind bulletproof glass and Kevlar-reinforced walls. I gave them my driver’s license (which, I was told, I’d get back when I left), and after two more sets of hand scans and steel doors, we entered the co-location area.

I was glad that I had decided to wear a light coat over my suit that day, because Equinix keeps the facility at a cool 65 to 72 degrees Fahrenheit. The design itself is also very cool. Built on a concrete slab with 45-foot-high ceilings, the building is organized along a rectangular grid system, with rows and rows of servers housed in metal cages for as far as the eye can see. Yellow trays snake above the cages, carrying all types of cables. Orange “innerducts” transport fiber-optic connections within the cages. Giant air-conditioning units, located outside the co-location area in case of a water leak, pump air through large green ducts that come down over the cages, creating a giant convection loop that sends the heat from the servers and networking equipment up toward the ceiling and out through the roof.

The facility is kept dark, both to improve its energy efficiency and to protect the anonymity of Equinix’s tenants. Each cage has lights that come on automatically when someone enters, I learned when Travan typed in the code to unlock his cage. Gravitas has about 35 clients operating out of its space, including one large hedge fund firm that spent more than $1 million on computer hardware, software and setup costs. The majority of Gravitas’s clients, however, are small. The company provides all of its clients with direct high-speed connections to all the market data providers and trade execution networks, including other NY4 tenants, like Direct Edge and the International Securities Exchange.

“We make the electronic trading community of Equinix available to smaller players by taking advantage of economies of scale — helping them get in with the technology they need with almost no up-front capital,” Travan told me. “If you’ve got a coder and the next best algo for trading equities, currencies or other vehicles, instead of needing a quarter-million dollars to start up, you can simply install your code on our hosting platform or send us servers to plug in, and you’re ready to go.”

Not everybody, however, buys the democratization argument. James McCaughan, CEO of Principal Global Investors, says co-location gives high frequency traders an unfair advantage. “Co-location creates an informational asymmetry that is fundamentally acting against the interests of long-term investors,” McCaughan told me exactly one week after my visit to the Equinix data center. “I have no problem with people developing algorithms for high frequency trading as long as they’re doing it with the same information as everybody else.”

McCaughan, whose team manages $215 billion in mostly 401(k) and other retirement assets for Principal Financial Group, considers himself to be a pretty savvy investor. His equity-trading desk has six people at the company’s Des Moines, Iowa, headquarters; two each in London and Singapore; and one in Tokyo, as well as access to state-of-the-art trade-execution algorithms offered by all the leading brokerage firms and third-party vendors. Although there’s nothing stopping Principal from using co-location, McCaughan told me that for a long-term investor, it’s probably not worth the effort. “As a large, sophisticated investor, we can compete,” he said. “But it is a weaker market if you have to be that sophisticated to compete.”

HIGH FREQUENCY TRADING BURST into the public consciousness last summer when news broke that a former Goldman Sachs Group computer programmer had been arrested by Federal Bureau of Investigation agents at Newark Liberty International Airport for allegedly stealing software code. According to the FBI, the programmer, Sergey Aleynikov, transferred thousands of files related to Goldman’s proprietary trading program to his home computers with the intention of using them to help his new employer build a high frequency trading platform. It didn’t take long for that employer, Chicago-based Teza Technologies, to cut its ties with Aleynikov. But Teza’s co-founders soon landed in hot water themselves when just six days after Aleynikov’s arrest, hedge fund firm Citadel sued them for violating a noncompete agreement and trying to steal its trade secrets. Last fall Citadel finally got the injunction against Teza that it was seeking, but by the time the judgment was rendered, the nine-month noncompete period had nearly expired.

The Citadel-Teza lawsuit provides an illuminating window into the world of high frequency trading. The person at the center of the drama is Mikhail Malyshev, a brilliant Russian émigré with a Ph.D. in plasma physics who joined Citadel’s high frequency ­trading group in 2003. During Malyshev’s six years at Citadel, the firm spent hundreds of millions of dollars researching and developing high frequency trading models and building out the IT infrastructure and systems to implement them. Its market data system, for example, contains roughly 100 times the amount of information in the Library of Congress. Citadel uses this historical data to test its models, which attempt to forecast changes in the prices of securities by analyzing statistical pricing patterns, supply and demand imbalances and other factors. The signals, or alphas, that prove to have predictive power are then translated into computer algorithms, which are integrated into Citadel’s master source code and electronic trading program.

Malyshev oversaw all aspects of Citadel’s nearly 60-person high frequency business, including the approval of trading strategies. He resigned on February 16, 2009; the next day his top lieutenant, Jace Kohlmeier, left too. By April they had incorporated Teza. Last fall, while I was reporting my story on Citadel, Kenneth Griffin, the firm’s billionaire founder and CEO, told me that before the arrest of Aleynikov, he had no idea what Malyshev and Kohlmeier were doing at Teza. After all, he said, the two were still on Citadel’s payroll as part of their noncompete agreements.

Like most hedge fund firms, Citadel is secretive about its investment strategies. The fact that Griffin would pursue a very public lawsuit with Teza’s founders says a lot about the importance of high frequency trading to the $12 billion-in-assets Citadel. In 2008 its high frequency group made $1.15 billion, compared with gains of $892 million the previous year and $75 million in 2005, according to Malyshev’s testimony. The 2008 performance was especially impressive given how poorly Citadel’s large multistrategy funds did that year: Its flagship Kensington and Wellington funds were each down about 55 percent.

Benjamin Blander, who joined the firm in 2004 from Banc One Corp., now leads the high frequency group, which manages a portion of Citadel’s $1.8 billion Tactical Trading fund. Citadel, however, was the only large hedge fund firm I could find that was willing to admit that it does high frequency trading. Most say they use many of the same tools as high frequency traders — employing high-speed computer programs and co-location services to generate, route and execute orders — but that their strategies have a longer time horizon.

“Even the slowest high frequency traders are turning over their portfolios at least a half dozen times a day,” AQR principal Michael Mendelson told me when I met with him in January at the firm’s Greenwich headquarters. “We tend to hold things for at least a day or two, and usually longer.”

Mendelson was head of quantitative equity trading at Goldman Sachs before joining AQR in 2005; he oversees the firm’s statistical arbitrage strategies. He explained to me that high frequency trading doesn’t require much in the way of capital — in fact, it would be hard-pressed to put hundreds of millions of dollars to work. The typical high frequency firm, he added, is likely to have about $5 million in proprietary capital and trade a few million shares a day through a specialized brokerage firm like Lime or Wedbush Securities.

High frequency trading, I learned, is a very low-margin, low-risk strategy. Traders earn less than a penny a share and rarely hold overnight positions. Profits are measured in hundredths of a cent, or “mils,” to use the industry parlance. According to Narang, high frequency traders typically earn about 10 mils, or 0.1 cent, a share trading U.S. equities. One of the attractions of the strategy is its consistency. High frequency traders rarely have losing days. They also tend to do very well during periods of high volatility. May was likely a great month for them.

Narang and other high frequency traders I spoke with gripe about the press, saying that it has often misrepresented what they do and grossly inflated the profitability of their business. They’ve got a legitimate beef. Last summer, a few weeks after the Goldman software-theft news broke, the New York Times ran a front-page story by Charles Duhigg describing how a handful of traders use powerful computers to “reap billions at everyone else’s expense.” The article went on to say that “these systems are so fast they can outsmart or outrun other investors, humans and computers alike,” using flash orders to step in front of those investors. (Under Reg NMS, exchanges were given the ability to “flash” marketable orders electronically for a split second to some professional traders before they are displayed to the broad public.) The article included the bold assertion that high frequency traders generated some $21 billion in profits in 2008.

The source of the data was TABB Group, a New York– and London-based research firm. The problem with the Times story, as I discovered when I met with Larry Tabb at his Wall Street office in early March, was that the $21 billion included a lot more than just high-frequency market making. “That number included anybody following an equities-related time-sensitive strategy that doesn’t take a significant end-of-day position,” the TABB founder and CEO explained. “It is pairs trading, options market making, futures and cash arbitrage, exchange-traded funds.” The profits for the virtual market makers in U.S. equities, he said, were roughly $8 billion in 2008 and $7.2 billion in 2009 and likely to be lower this year because of the drop in volatility and trading volume. (Tradeworx’s Narang says that high frequency trading in U.S. equities generates no more than $2 billion to $4 billion a year in profits overall.)

New York Senator Charles Schumer probably didn’t ask Larry Tabb for clarification after he read the Times article. The very same day it appeared, the longtime lawmaker fired off a letter to Mary ­Schapiro demanding that the SEC do something about high frequency traders and their ability to view order-flow information before the general public by using flash orders. “This kind of unfair access seriously compromises the integrity of our markets and creates a two-tiered system where a privileged group of insiders receives preferential treatment,” he wrote. If the SEC failed to curb flash trades, Schumer threatened to introduce legislation that would.

THE SEC'S NEW HEADQUARTERS IS a marvel of modern architecture. Conveniently located next to Washington’s historic Union Station, the building has a spectacular glass-and-steel atrium where visitors can watch the news on a giant flat-screen television while waiting to make their way into the agency’s inner sanctum. That’s exactly what I was doing one cloudy Tuesday afternoon in late March when John Nester, the SEC’s director of public affairs, came to get me. I’d taken the train down from New York that day to meet with James Brigagliano, deputy director of the agency’s Division of Trading and Markets, and several other members of his team to discuss high frequency trading. The problem was, I didn’t know in advance who was going to be in the meeting, and as Brigagliano and three other staffers from the SEC division filed into the room and quickly introduced themselves, I didn’t catch all of their names. I handed out business cards to each of them in hopes of getting them in return, but only one person (assistant director John Roeser) had brought a card.

It took me about 20 minutes into the interview to piece together the two missing names — “Dan” (who I later found out was market structure counsel Daniel Gray) and “Dave” (associate director David Shillman). Despite my initial confusion, I was impressed with the SEC staff’s knowledge of high frequency trading. We had a wide-ranging discussion, spanning everything from market structure and regulation to Washington politics and financial reform. The SEC’s interest in high frequency trading, I learned, long preceded Schumer’s famous letter to Schapiro last summer (and a similar call from Senator Kaufman for the SEC to do a comprehensive review of market structure). Brigagliano told me that the SEC began hearing about high frequency trading not long after it passed Reg NMS and that his group started working on the equity market structure concept release early last year.

The SEC has a tripartite mission: to protect investors, maintain fair and orderly markets and facilitate capital formation. Although the mandates can sometimes be at odds with one another, getting the first two right can go a long way toward ensuring the third. “We see confidence in the markets as essential for capital formation,” ­Brigagliano told me. “Investors are not going to commit capital if they think that the system is rigged.”

By the time I met with Brigagliano and his team, the SEC had proposed several new rules to help safeguard the market, including the elimination of flash orders and a prohibition against broker-dealers providing clients with unfiltered, or “naked,” access to exchanges and other alternative trading systems. Naked access has been popular among some speed-conscious high frequency traders because it enables them to place buy and sell orders directly with an exchange or trading venue without being slowed down by pretrade credit and risk checks. The SEC’s rule proposal, if approved, would require brokerage firms to create and maintain strict risk management controls for clients that are given direct sponsored access to electronic trading venues.

Of course, one of the biggest problems the SEC and other regulators have faced is that they simply haven’t had the tools or the data to track the billions and billions of trades that fire across the electronic exchanges and trading platforms each day. Although several of the largest high frequency players, like Getco, are registered broker-dealers and have the reporting requirements that go along with that, the vast majority of firms operate in anonymity. In April the SEC looked to change that when it voted to propose the creation of a large-trader reporting system. If the proposal is approved, any firm or individual that trades 2 million shares or $20 million in exchange-listed securities in a day, or 20 million shares or $200 million in securities in a month, will be required to identify itself to the SEC. The agency will then assign that trader a number, which its broker-dealer will use to tag all its transactions, reporting them, upon request, to the SEC.

“The large-trader reporting system will be simple to put in place,” the SEC’s Shillman told me during my March meeting at the agency. “Creating a consolidated audit trail is more complicated, and could take several years, because it requires systems changes at exchanges and broker-dealers.”

The SEC began working on a consolidated audit-trail proposal last summer, consulting with exchanges and broker-dealers on what would need to be done and how much it would cost. On May 26 the agency unveiled its new rule, which would create a consolidated order-tracking system that would enable the agency to access in real time most of the data needed to reconstruct a market dislocation like the flash crash. But progress doesn’t come cheap: The SEC estimates that it will initially cost about $4 billion to build the system and an additional $2.1 billion a year to maintain it. Taxpayers, however, won’t have to worry about footing the bill; the costs would be borne by broker-dealers, exchanges and other trading venues.

The large-trader tagging and consolidated audit-trail proposals are likely to be approved by the commission over the coming months. Although it’s wishful thinking to expect the SEC to ever be able to match the technological sophistication of high frequency traders, the new rules should eventually give the regulator the necessary tools to monitor and police their activity. I’m sure that is going to make some high frequency traders very nervous, but they shouldn’t be. Unlike some of the more vocal critics of high frequency trading, SEC chairman Schapiro knows that the technological clock cannot be turned back.

“While technology has provided benefits to the market, it has also created real issues,” she told me in early May. “We want to be very careful and thoughtful about how we approach it. The idea that you can say, ‘Let’s just unplug everything’ or ‘Let’s put something into the machines that makes everything go slower’ is probably not realistic.”
In other words, in the battle of man versus machine, both sides could end up winning.

Does Your Language Shape How You Think?

Seventy years ago, in 1940, a popular science magazine published a short article that set in motion one of the trendiest intellectual fads of the 20th century. At first glance, there seemed little about the article to augur its subsequent celebrity. Neither the title, “Science and Linguistics,” nor the magazine, M.I.T.’s Technology Review, was most people’s idea of glamour. And the author, a chemical engineer who worked for an insurance company and moonlighted as an anthropology lecturer at Yale University, was an unlikely candidate for international superstardom. And yet Benjamin Lee Whorf let loose an alluring idea about language’s power over the mind, and his stirring prose seduced a whole generation into believing that our mother tongue restricts what we are able to think.

Enlarge This Image

Horacio Salinas for The New York Times

In particular, Whorf announced, Native American languages impose on their speakers a picture of reality that is totally different from ours, so their speakers would simply not be able to understand some of our most basic concepts, like the flow of time or the distinction between objects (like “stone”) and actions (like “fall”). For decades, Whorf’s theory dazzled both academics and the general public alike. In his shadow, others made a whole range of imaginative claims about the supposed power of language, from the assertion that Native American languages instill in their speakers an intuitive understanding of Einstein’s concept of time as a fourth dimension to the theory that the nature of the Jewish religion was determined by the tense system of ancient Hebrew.

Eventually, Whorf’s theory crash-landed on hard facts and solid common sense, when it transpired that there had never actually been any evidence to support his fantastic claims. The reaction was so severe that for decades, any attempts to explore the influence of the mother tongue on our thoughts were relegated to the loony fringes of disrepute. But 70 years on, it is surely time to put the trauma of Whorf behind us. And in the last few years, new research has revealed that when we learn our mother tongue, we do after all acquire certain habits of thought that shape our experience in significant and often surprising ways.

Whorf, we now know, made many mistakes. The most serious one was to assume that our mother tongue constrains our minds and prevents us from being able to think certain thoughts. The general structure of his arguments was to claim that if a language has no word for a certain concept, then its speakers would not be able to understand this concept. If a language has no future tense, for instance, its speakers would simply not be able to grasp our notion of future time. It seems barely comprehensible that this line of argument could ever have achieved such success, given that so much contrary evidence confronts you wherever you look. When you ask, in perfectly normal English, and in the present tense, “Are you coming tomorrow?” do you feel your grip on the notion of futurity slipping away? Do English speakers who have never heard the German word Schadenfreude find it difficult to understand the concept of relishing someone else’s misfortune? Or think about it this way: If the inventory of ready-made words in your language determined which concepts you were able to understand, how would you ever learn anything new?

SINCE THERE IS NO EVIDENCE that any language forbids its speakers to think anything, we must look in an entirely different direction to discover how our mother tongue really does shape our experience of the world. Some 50 years ago, the renowned linguist Roman Jakobson pointed out a crucial fact about differences between languages in a pithy maxim: “Languages differ essentially in what they must convey and not in what they may convey.” This maxim offers us the key to unlocking the real force of the mother tongue: if different languages influence our minds in different ways, this is not because of what our language allows us to think but rather because of what it habitually obliges us to think about.

Consider this example. Suppose I say to you in English that “I spent yesterday evening with a neighbor.” You may well wonder whether my companion was male or female, but I have the right to tell you politely that it’s none of your business. But if we were speaking French or German, I wouldn’t have the privilege to equivocate in this way, because I would be obliged by the grammar of language to choose between voisin or voisine; Nachbar or Nachbarin. These languages compel me to inform you about the sex of my companion whether or not I feel it is remotely your concern. This does not mean, of course, that English speakers are unable to understand the differences between evenings spent with male or female neighbors, but it does mean that they do not have to consider the sexes of neighbors, friends, teachers and a host of other persons each time they come up in a conversation, whereas speakers of some languages are obliged to do so.

On the other hand, English does oblige you to specify certain types of information that can be left to the context in other languages. If I want to tell you in English about a dinner with my neighbor, I may not have to mention the neighbor’s sex, but I do have to tell you something about the timing of the event: I have to decide whether we dined, have been dining, are dining, will be dining and so on. Chinese, on the other hand, does not oblige its speakers to specify the exact time of the action in this way, because the same verb form can be used for past, present or future actions. Again, this does not mean that the Chinese are unable to understand the concept of time. But it does mean they are not obliged to think about timing whenever they describe an action.

When your language routinely obliges you to specify certain types of information, it forces you to be attentive to certain details in the world and to certain aspects of experience that speakers of other languages may not be required to think about all the time. And since such habits of speech are cultivated from the earliest age, it is only natural that they can settle into habits of mind that go beyond language itself, affecting your experiences, perceptions, associations, feelings, memories and orientation in the world.

BUT IS THERE any evidence for this happening in practice?

Let’s take genders again. Languages like Spanish, French, German and Russian not only oblige you to think about the sex of friends and neighbors, but they also assign a male or female gender to a whole range of inanimate objects quite at whim. What, for instance, is particularly feminine about a Frenchman’s beard (la barbe)? Why is Russian water a she, and why does she become a he once you have dipped a tea bag into her? Mark Twain famously lamented such erratic genders as female turnips and neuter maidens in his rant “The Awful German Language.” But whereas he claimed that there was something particularly perverse about the German gender system, it is in fact English that is unusual, at least among European languages, in not treating turnips and tea cups as masculine or feminine. Languages that treat an inanimate object as a he or a she force their speakers to talk about such an object as if it were a man or a woman. And as anyone whose mother tongue has a gender system will tell you, once the habit has taken hold, it is all but impossible to shake off. When I speak English, I may say about a bed that “it” is too soft, but as a native Hebrew speaker, I actually feel “she” is too soft. “She” stays feminine all the way from the lungs up to the glottis and is neutered only when she reaches the tip of the tongue.

In recent years, various experiments have shown that grammatical genders can shape the feelings and associations of speakers toward objects around them. In the 1990s, for example, psychologists compared associations between speakers of German and Spanish. There are many inanimate nouns whose genders in the two languages are reversed. A German bridge is feminine (die Brücke), for instance, but el puente is masculine in Spanish; and the same goes for clocks, apartments, forks, newspapers, pockets, shoulders, stamps, tickets, violins, the sun, the world and love. On the other hand, an apple is masculine for Germans but feminine in Spanish, and so are chairs, brooms, butterflies, keys, mountains, stars, tables, wars, rain and garbage. When speakers were asked to grade various objects on a range of characteristics, Spanish speakers deemed bridges, clocks and violins to have more “manly properties” like strength, but Germans tended to think of them as more slender or elegant. With objects like mountains or chairs, which are “he” in German but “she” in Spanish, the effect was reversed.

In a different experiment, French and Spanish speakers were asked to assign human voices to various objects in a cartoon. When French speakers saw a picture of a fork (la fourchette), most of them wanted it to speak in a woman’s voice, but Spanish speakers, for whom el tenedor is masculine, preferred a gravelly male voice for it. More recently, psychologists have even shown that “gendered languages” imprint gender traits for objects so strongly in the mind that these associations obstruct speakers’ ability to commit information to memory.

Of course, all this does not mean that speakers of Spanish or French or German fail to understand that inanimate objects do not really have biological sex — a German woman rarely mistakes her husband for a hat, and Spanish men are not known to confuse a bed with what might be lying in it. Nonetheless, once gender connotations have been imposed on impressionable young minds, they lead those with a gendered mother tongue to see the inanimate world through lenses tinted with associations and emotional responses that English speakers — stuck in their monochrome desert of “its” — are entirely oblivious to. Did the opposite genders of “bridge” in German and Spanish, for example, have an effect on the design of bridges in Spain and Germany? Do the emotional maps imposed by a gender system have higher-level behavioral consequences for our everyday life? Do they shape tastes, fashions, habits and preferences in the societies concerned? At the current state of our knowledge about the brain, this is not something that can be easily measured in a psychology lab. But it would be surprising if they didn’t.

The area where the most striking evidence for the influence of language on thought has come to light is the language of space — how we describe the orientation of the world around us. Suppose you want to give someone directions for getting to your house. You might say: “After the traffic lights, take the first left, then the second right, and then you’ll see a white house in front of you. Our door is on the right.” But in theory, you could also say: “After the traffic lights, drive north, and then on the second crossing drive east, and you’ll see a white house directly to the east. Ours is the southern door.” These two sets of directions may describe the same route, but they rely on different systems of coordinates. The first uses egocentric coordinates, which depend on our own bodies: a left-right axis and a front-back axis orthogonal to it. The second system uses fixed geographic directions, which do not rotate with us wherever we turn.

We find it useful to use geographic directions when hiking in the open countryside, for example, but the egocentric coordinates completely dominate our speech when we describe small-scale spaces. We don’t say: “When you get out of the elevator, walk south, and then take the second door to the east.” The reason the egocentric system is so dominant in our language is that it feels so much easier and more natural. After all, we always know where “behind” or “in front of” us is. We don’t need a map or a compass to work it out, we just feel it, because the egocentric coordinates are based directly on our own bodies and our immediate visual fields.

But then a remote Australian aboriginal tongue, Guugu Yimithirr, from north Queensland, turned up, and with it came the astounding realization that not all languages conform to what we have always taken as simply “natural.” In fact, Guugu Yimithirr doesn’t make any use of egocentric coordinates at all. The anthropologist John Haviland and later the linguist Stephen Levinson have shown that Guugu Yimithirr does not use words like “left” or “right,” “in front of” or “behind,” to describe the position of objects. Whenever we would use the egocentric system, the Guugu Yimithirr rely on cardinal directions. If they want you to move over on the car seat to make room, they’ll say “move a bit to the east.” To tell you where exactly they left something in your house, they’ll say, “I left it on the southern edge of the western table.” Or they would warn you to “look out for that big ant just north of your foot.” Even when shown a film on television, they gave descriptions of it based on the orientation of the screen. If the television was facing north, and a man on the screen was approaching, they said that he was “coming northward.”

When these peculiarities of Guugu Yimithirr were uncovered, they inspired a large-scale research project into the language of space. And as it happens, Guugu Yimithirr is not a freak occurrence; languages that rely primarily on geographical coordinates are scattered around the world, from Polynesia to Mexico, from Namibia to Bali. For us, it might seem the height of absurdity for a dance teacher to say, “Now raise your north hand and move your south leg eastward.” But the joke would be lost on some: the Canadian-American musicologist Colin McPhee, who spent several years on Bali in the 1930s, recalls a young boy who showed great talent for dancing. As there was no instructor in the child’s village, McPhee arranged for him to stay with a teacher in a different village. But when he came to check on the boy’s progress after a few days, he found the boy dejected and the teacher exasperated. It was impossible to teach the boy anything, because he simply did not understand any of the instructions. When told to take “three steps east” or “bend southwest,” he didn’t know what to do. The boy would not have had the least trouble with these directions in his own village, but because the landscape in the new village was entirely unfamiliar, he became disoriented and confused. Why didn’t the teacher use different instructions? He would probably have replied that saying “take three steps forward” or “bend backward” would be the height of absurdity.

So different languages certainly make us speak about space in very different ways. But does this necessarily mean that we have to think about space differently? By now red lights should be flashing, because even if a language doesn’t have a word for “behind,” this doesn’t necessarily mean that its speakers wouldn’t be able to understand this concept. Instead, we should look for the possible consequences of what geographic languages oblige their speakers to convey. In particular, we should be on the lookout for what habits of mind might develop because of the necessity of specifying geographic directions all the time.

In order to speak a language like Guugu Yimithirr, you need to know where the cardinal directions are at each and every moment of your waking life. You need to have a compass in your mind that operates all the time, day and night, without lunch breaks or weekends off, since otherwise you would not be able to impart the most basic information or understand what people around you are saying. Indeed, speakers of geographic languages seem to have an almost-superhuman sense of orientation. Regardless of visibility conditions, regardless of whether they are in thick forest or on an open plain, whether outside or indoors or even in caves, whether stationary or moving, they have a spot-on sense of direction. They don’t look at the sun and pause for a moment of calculation before they say, “There’s an ant just north of your foot.” They simply feel where north, south, west and east are, just as people with perfect pitch feel what each note is without having to calculate intervals. There is a wealth of stories about what to us may seem like incredible feats of orientation but for speakers of geographic languages are just a matter of course. One report relates how a speaker of Tzeltal from southern Mexico was blindfolded and spun around more than 20 times in a darkened house. Still blindfolded and dizzy, he pointed without hesitation at the geographic directions.

How does this work? The convention of communicating with geographic coordinates compels speakers from the youngest age to pay attention to the clues from the physical environment (the position of the sun, wind and so on) every second of their lives, and to develop an accurate memory of their own changing orientations at any given moment. So everyday communication in a geographic language provides the most intense imaginable drilling in geographic orientation (it has been estimated that as much as 1 word in 10 in a normal Guugu Yimithirr conversation is “north,” “south,” “west” or “east,” often accompanied by precise hand gestures). This habit of constant awareness to the geographic direction is inculcated almost from infancy: studies have shown that children in such societies start using geographic directions as early as age 2 and fully master the system by 7 or 8. With such an early and intense drilling, the habit soon becomes second nature, effortless and unconscious. When Guugu Yimithirr speakers were asked how they knew where north is, they couldn’t explain it any more than you can explain how you know where “behind” is.

But there is more to the effects of a geographic language, for the sense of orientation has to extend further in time than the immediate present. If you speak a Guugu Yimithirr-style language, your memories of anything that you might ever want to report will have to be stored with cardinal directions as part of the picture. One Guugu Yimithirr speaker was filmed telling his friends the story of how in his youth, he capsized in shark-infested waters. He and an older person were caught in a storm, and their boat tipped over. They both jumped into the water and managed to swim nearly three miles to the shore, only to discover that the missionary for whom they worked was far more concerned at the loss of the boat than relieved at their miraculous escape. Apart from the dramatic content, the remarkable thing about the story was that it was remembered throughout in cardinal directions: the speaker jumped into the water on the western side of the boat, his companion to the east of the boat, they saw a giant shark swimming north and so on. Perhaps the cardinal directions were just made up for the occasion? Well, quite by chance, the same person was filmed some years later telling the same story. The cardinal directions matched exactly in the two tellings. Even more remarkable were the spontaneous hand gestures that accompanied the story. For instance, the direction in which the boat rolled over was gestured in the correct geographic orientation, regardless of the direction the speaker was facing in the two films.

Psychological experiments have also shown that under certain circumstances, speakers of Guugu Yimithirr-style languages even remember “the same reality” differently from us. There has been heated debate about the interpretation of some of these experiments, but one conclusion that seems compelling is that while we are trained to ignore directional rotations when we commit information to memory, speakers of geographic languages are trained not to do so. One way of understanding this is to imagine that you are traveling with a speaker of such a language and staying in a large chain-style hotel, with corridor upon corridor of identical-looking doors. Your friend is staying in the room opposite yours, and when you go into his room, you’ll see an exact replica of yours: the same bathroom door on the left, the same mirrored wardrobe on the right, the same main room with the same bed on the left, the same curtains drawn behind it, the same desk next to the wall on the right, the same television set on the left corner of the desk and the same telephone on the right. In short, you have seen the same room twice. But when your friend comes into your room, he will see something quite different from this, because everything is reversed north-side-south. In his room the bed was in the north, while in yours it is in the south; the telephone that in his room was in the west is now in the east, and so on. So while you will see and remember the same room twice, a speaker of a geographic language will see and remember two different rooms.

It is not easy for us to conceive how Guugu Yimithirr speakers experience the world, with a crisscrossing of cardinal directions imposed on any mental picture and any piece of graphic memory. Nor is it easy to speculate about how geographic languages affect areas of experience other than spatial orientation — whether they influence the speaker’s sense of identity, for instance, or bring about a less-egocentric outlook on life. But one piece of evidence is telling: if you saw a Guugu Yimithirr speaker pointing at himself, you would naturally assume he meant to draw attention to himself. In fact, he is pointing at a cardinal direction that happens to be behind his back. While we are always at the center of the world, and it would never occur to us that pointing in the direction of our chest could mean anything other than to draw attention to ourselves, a Guugu Yimithirr speaker points through himself, as if he were thin air and his own existence were irrelevant.

IN WHAT OTHER WAYS might the language we speak influence our experience of the world? Recently, it has been demonstrated in a series of ingenious experiments that we even perceive colors through the lens of our mother tongue. There are radical variations in the way languages carve up the spectrum of visible light; for example, green and blue are distinct colors in English but are considered shades of the same color in many languages. And it turns out that the colors that our language routinely obliges us to treat as distinct can refine our purely visual sensitivity to certain color differences in reality, so that our brains are trained to exaggerate the distance between shades of color if these have different names in our language. As strange as it may sound, our experience of a Chagall painting actually depends to some extent on whether our language has a word for blue.

In coming years, researchers may also be able to shed light on the impact of language on more subtle areas of perception. For instance, some languages, like Matses in Peru, oblige their speakers, like the finickiest of lawyers, to specify exactly how they came to know about the facts they are reporting. You cannot simply say, as in English, “An animal passed here.” You have to specify, using a different verbal form, whether this was directly experienced (you saw the animal passing), inferred (you saw footprints), conjectured (animals generally pass there that time of day), hearsay or such. If a statement is reported with the incorrect “evidentiality,” it is considered a lie. So if, for instance, you ask a Matses man how many wives he has, unless he can actually see his wives at that very moment, he would have to answer in the past tense and would say something like “There were two last time I checked.” After all, given that the wives are not present, he cannot be absolutely certain that one of them hasn’t died or run off with another man since he last saw them, even if this was only five minutes ago. So he cannot report it as a certain fact in the present tense. Does the need to think constantly about epistemology in such a careful and sophisticated manner inform the speakers’ outlook on life or their sense of truth and causation? When our experimental tools are less blunt, such questions will be amenable to empirical study.

For many years, our mother tongue was claimed to be a “prison house” that constrained our capacity to reason. Once it turned out that there was no evidence for such claims, this was taken as proof that people of all cultures think in fundamentally the same way. But surely it is a mistake to overestimate the importance of abstract reasoning in our lives. After all, how many daily decisions do we make on the basis of deductive logic compared with those guided by gut feeling, intuition, emotions, impulse or practical skills? The habits of mind that our culture has instilled in us from infancy shape our orientation to the world and our emotional responses to the objects we encounter, and their consequences probably go far beyond what has been experimentally demonstrated so far; they may also have a marked impact on our beliefs, values and ideologies. We may not know as yet how to measure these consequences directly or how to assess their contribution to cultural or political misunderstandings. But as a first step toward understanding one another, we can do better than pretending we all think the same.

Guy Deutscher is an honorary research fellow at the School of Languages, Linguistics and Cultures at the University of Manchester. His new book, from which this article is adapted, is “Through the Language Glass: Why the World Looks Different in Other Languages,” to be published this month by Metropolitan Books.