High-speed predators

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There have apparently been some reviews sniping at Flash Boys, the latest book by Michael Lewis on the financial markets, not that he will care given how well it’s selling. The grumpy reviews are wrong. It’s an excellent book. Lewis writes like a dream, and brings characters to life as well as any novelist. There are laugh out loud moments. And he explains as clearly as it is possible for a general reader the way today’s super-super-fast US equity market functions, or rather malfunctions.This is a great achievement, as it is very complicated.

I’ve not read other reviews of the book, but I gather from Twitter that some people accuse Lewis of exaggerating and making out all high frequency trading to be bad when it has cut commissions and increased liquidity. They’re wrong. Maybe there are one or two good guys doing HFT. But when there are frequent crashes and spikes in prices, and when the HFT firms do not make losses on any day, these traders are not taking on risk and enhancing liquidity; they are tax farming and increasing volatility through massive amounts of ultra-fast trading activity.

I got interested in HFT early in 2012 when I was preparing for my Tanner Lectures. It seemed the most extraordinary example of performativity, the shaping of reality by economic theory, as the options pricing formula devised by Black, Scholes and Merton had ended up causing a tunnel to be drilled through the Allegheny Mountains so a new fibre optic cable from Chicago to New Jersey could send information at something closer to the speed of light. Flash Boys starts with the same new line, built by Spread Networks. Lewis writes about the contract Spread Networks offered the Wall Street banks, whereby they could use the line for their own proprietary trading but not for their brokerage customers: “The whole point of  the line was to create inside the public markets a private space.”

The HFT markets serve the HFT firms and the big banks, which operate “dark pools”, or private markets in which they execute customers’ trades. Even giant hedge funds get a worse deal than the proprietary traders. Indeed, HFT firms pay Wall Street firms for access to their dark pools – to prey on the orders in there. No matter how big the investor, they would know nothing about how their orders were routed or when executed once they had issued the buy or sell order.

The market dysfunction had come about because of Regulation NMS, a stock exchange rule issued by the SEC with the intention of making sure investors got the best prices but with the unintended consequence that it created a spaghetti junction of orders moving around exchanges, with delays that HFT firms could use to their advantage. It isn’t just Lewis who says the rule backfired: here is a Wall Street Journal write-up questioning the benefits of the regulation. The regulation created short-term profit opportunities from gaming it, and the proliferation of exchanges it encouraged. As one character says, “It’s hard to be forward thinking when the whole of corporate America is about next quarter’s earnings.” High frequency traders, including those in big Wall Street banks, give themselves an information advantage over investors (including the funds looking after your money and mine); once an investor asks its broker to buy or sell shares, the information about the order belongs to the broker.

The solution to complexity that can be gamed and privileged information lies in simplicity and transparency, and the narrative thrust of Flash Boys is the creation of a simple, transparent exchange, IEX, by good cowboy Brad Katsuyama, who left Royal Bank of Canada to found it once he started to uncover the absolute scandal of the way high frequency trading was operating. Unexpectedly, Goldman Sachs emerges heroically, being the first major institution to route large volumes of orders through IEX. Lewis speculates that its senior people had come to realise: (a) Goldman is not very good at HFT because it has an old computer system; (b) one day, the highly complex and unstable equities market created by HFT will cause a huge, but huge, market crisis and they don’t want Goldman to get the blame. Goldman Sachs also emerges as villain for getting the FBI to arrest a Russian programmer, Sergey Aleynikov, for “stealing” some of their computer code – although found guilty and imprisoned, he had sent himself – openly – some mainly open source code when he quit the firm.

The book ends with a puzzle: the FCC license number 1215095, fixed to a microwave tower in Pennsylvania. The license application was filed in July 2012. Follow the lead, Lewis says, and you will find “another incredible but true Wall Street story, of hypocrisy and secrecy and the endless quest by human beings to gain a certain edge in an uncertain world.” Naturally, a lot of people have already done so.

As this ending suggests, he doesn’t argue that high frequency traders are evil. But the book does make a powerful case that the financial system is a dangerously complex system that creates damaging incentives. Like all complex systems, there will be a straw that breaks the camel’s back, a grain of sand that causes the whole pile to collapse. The world is uncertain in the sense that the specific straw or grain – which one, when -  is unpredictable, but the collapse is inevitable. There is an interesting question as to why innovation in finance – unlike in any other sector of the economy – so often works against the interests of consumers, not in their favour.

Lewis cites some others who have written about HFT: Sal Arnuk and Jospeh Saluzzi in Broken Markets; Eric Hunsader, founder of Nanex, a stock market data company; researcher Adam Clark-Joseph (pdf), whose work on HFT led the CFTC to shut its programme giving researchers access to data. There is also a book, Dark Pools, by journalist Scott Patterson. Publications like Automated Trader are well worth a look too.

Anyway, Flash Boys joins Lewis’s earlier book on the 2008 crisis, The Big Short, and John Lanchester’s Whoops as must-read guides to the insanity of modern finance.

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Shiny models versus human nature

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It’s been one of those weeks – three days with meetings from morning to night. So I’m only half way through Flash Boys by Michael Lewis, even though he writes like a dream and it’s a pleasure to read.

Meanwhile, I was distracting myself this morning with this interview with E.O.Wilson. Why did he become a biologist? Not much else to do growing up in Alabama, he says here, apart from looking closely at ants.

I’ve not read many of his books, including the famous/notorious Sociobiology; but I was inspired by Consilience: The Unity of Knowledge (1998) and enjoyed The Diversity of Life.

My notes from reading it in 1999, nicely scrawled on by a 2 year old, have the following quotations:

“Social scientists as a whole have paid little attention to the foundations of human nature and they have almost no interest in its deep origins.” (This obviously does not refer to the earliest social scientists such as David Hume, John Locke, Adam Smith, and is becoming less true of at least some of today’s social scientists.)

“Thanks to science and technology, access to factual knowledge of all kinds is rising exponentially while dropping in unit cost. Soon it will be available everywhere on television and computer screens. What then? The answer is clear: Synthesis. We are drawing in information while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information and the right time, think critically about it and make important choices wisely.” (Right analysis but optimistic conclusions? Not much overt sign of more wisdom in action.)

And on economic models: “Their appeal is in the chrome and the roar of the engine, not the velocity or destination.” Vroom, vroom.

Capital and destiny

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It is with some trepidation that I offer my review of Thomas Piketty’s Capital in the 21st Century, as so much has been written, almost all of it verging on the adulatory. Of course it’s an important book – who could disagree with that when almost everybody in my world is talking about it, and it has cemented the question of inequality of income and wealth on the economic policy agenda? The book has obviously plugged into the zeitgeist. It has some flaws too.

Piketty’s construction of a long-run multi-country World Top Incomes Database for income and wealth, along with Emmanuel Saez and Anthony Atkinson,’ is a magnificent achievement. As the book notes several times, the data – constructed from a range of sources including tax records – are likely to understate the very highest fortunes and incomes because of the failure to declare everything. The assembly of these statistics has helped put inequality at the centre of economic debate.

Capital in the 21st Century concentrates on wealth and on the share of capital’s income in total national income. ‘Capital’ is defined as marketable assets, at their market price, including land, houses, shares and other financial instruments (but not for example bridges or factories). James Galbraith’s review of the book was critical of the definition. I think Galbraith is right to pick away at the data used and what the definitions actually mean.

Setting this aside, Piketty shows that the income share of (marketed financial) capital (at market values) declined substantially in the second half of the 20th century but is now climbing again. His argument is that this increase is a near-inexorable trend. The mid-20th century decline was essentially the result of Depression and war, or in other words, the massive destruction of assets and social dislocation; and the capital share stayed low for some decades because economic growth was unusually high, which – he argues – will no longer be the case. Specifically, population growth has slowed or turned negative, and Piketty is clearly gloomy about the prospect of productivity growth.

It’s clear that many readers have taken this argument as a given without concerning themselves about how it adds up. It is based on two equations (the only two in the book), which are asserted rather than given a clear rationale. I couldn’t work out the reasoning until I found Piketty’s lecture notes. So this is my explanation of the lecture notes.

One equation says that the share of capital in national income (α) is defined as the rate of return on capital (r) times the ratio of the capital stock to income (β). This is an accounting identity – it is how the concepts are defined and the figures calculated. If the capital stock is six times a year’s national income, and the rate of return on capital is 5%, the capital share is 30%. Historically, the rate of return on capital has been in the range 3-6%, which for that size of capital stock implies a capital share of 18% to 36% a year of national income, roughly one fifth to one third. Again, in the historical figures, the capital income ratio has typically been 5 or 6.

The second equation, which drives his argument about the upward trend in capital’s share, is a ‘steady state’ condition: when the economy settles down in a stable way in the very long run, at its long-term potential growth rate, the ratio of capital stock to income equals the savings rate (s) divided by the growth rate (g) – in other words, in the unchanging steady state, the ratio of the annual changes in capital growth (saving) and in income growth is the same as the ratio of the capital stock to the level of income.

This is not made all that clear in the book, but putting the two together, the capital share will tend to rise when the rate of return on capital is greater than the growth rate, assuming the saving rate does not decline to offset the impact of r > g. Piketty notes that in the long term data set, this inequality happens to have held: “The inequality r > g is a contingent historical proposition, which is true in some periods and political contexts and not in others.” The exception was the latter part of the 20th century.

This simple algebra based on an accounting identity and a balanced growth rule are the basis of the book’s argument – which has been pounced on by commentators – of an almost inexorable upward trend in the capital share. I am sceptical about the economy ever reaching the balanced growth state, although perhaps this is a useful tool for thinking about direction of travel, and I’m also doubtful that the saving rate would not adjust should the capital share in national grow ever-bigger. I also wish Piketty had spent more time discussing the rate of return on capital – both how it is constructed in the data set and what determines it – as the book treats it as a given at 4-5%. As Barry Eichengreen pointed out in a recent Project Syndicate article, there are some puzzles in saving and interest rate data, and real interest rates have been declining for 30 years. They are only one element of the rate of return series Piketty considers, but at 2-3%, this real interest rate is not too far above the potential growth rate of the major OECD economies. This takes us back to James Galbraith’s point about the definitions: is marketable capital consisting mainly of financial assets the right definition to plug into a balanced growth model?

I would like to have had more practical explanation of the data used in the book in general, as some of the charts are surprising. For instance, the charts suggest the housing stock in France is a bigger share of national income, and has grown faster, than in the UK. (As an aside, the charts are terrible – very hard to decipher, a decade on the x-axis given the same space as a half century or 60 years, multiple lines of equal weight with clashing symbols, much chart junk, Australia classed as ‘Anglo-Saxon’ when it looks like Germany in the data – I hope they all get redrawn for future editions.)

Of course I’m nit-picking by complaining about the impression of an inexorable trend towards an ever-greater capital share created by Piketty’s reliance on a growth model, because there is a deeper truth – as he puts it: “The inequality r > g in one sense implies that the past tends to devour the future: wealth originating in the past automatically grows more rapidly, even without labour, than wealth stemming from work, which can be saved.” In order for an economy to grow at all, the future must win the struggle against the past. But of course there have been several episodes when that has been the case – not just the aftermath of World War 2, highlighted in the book, but also much of the Victorian era, and the early Industrail Revolution (even though the charts here show r well in excess of g during those years too).

Still, the sense of inevitability or otherwise does matter. Piketty’s policy proposal is a global wealth tax. He’s acknowledged how unrealistic this is, but says it’s important to change the intellectual climate. True, but how about also debating the rigged markets in finance and the corporate legal framework that have contributed so significantly to the growth in very high incomes, which are quickly turned into new wealth? What about income and inheritance taxes? And rather than treating savings, the return on capital and the growth rate as givens, isn’t it worth thinking about what determines them, and what actually determines causality in the book’s simple algebra.

I’m glad Capital in the 21st Century has succeeded in drawing such attention to inequality of wealth as well as incomes, and to our new era of patrimonial capitalism. (Another sobering illustration of this is Greg Clark’s recent book, The Son Also Rises.) It’s just a bit of a shame it does so in such a deterministic – and therefore disempowering – way.

Nevertheless, pretty much every review I’ve read has raved about the book! Here are Paul Krugman, Branko Milanovic, John Cassidy, The Economist. No doubt there will be many more positive reviews to come.

Writers, geeks – and economists

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I very much enjoyed reading Vikram Chandra’s Geek Sublime: Writing Fiction, Coding Software. It’s just what it says, the reflections of somebody who writes novels and has made a living along the way out of programming software. There isn’t a big message, unless it’s the conclusion that the two activities are – despite some tantalising similarities – ultimately very different. (This is my terminology, but I would describe fiction-writing as art and coding as craft, both highly skilled but distinct.)

Along the way, Chandra makes a series of extremely interesting observations. One extended section is about Sanskrit and Hindu literature. The book describes Sanskrit as a fundamentally algorithmic language, with a given number of phonemes and rules for combining them, and yet the literature is as sublime and transcendent as any. I have no basis on which to comment on this but it was interesting.

Another fascinating section is about how strongly macho American (and I would add British) computer science has become, in contrast to the profession (or vocation) in India. The book traces this to the frontier spirit of early computer science (it refers to Nathan Ensmenger’s The Computer Boys, which I reviewed here a while ago.). The macho, cowboy attitude – “no bullshit” becoming simply rude and anti-social – was progressively reinforced by the sociology of the venture capital industry, and by the wider stereotyping so pervasive in American culture. The book cites figures suggesting that white, North American-born women are even less likely than African-American, Hispanic or Asian North American women, or European-born women, to study as computer scientists. American geekiness is particularly solitary and aggressive.

I found this section fascinating because it carries such strong echoes of the way American economics developed and subsequently imposed its social and cultural norms elsewhere. Economists are wannabee geeks, too, but we’re not nearly as fashionable as computer science geeks (for good reason).

The book has lots of other nuggets. I love the illustrations of Lego models of logic gates and the point they make that there’s nothing inherently electronic about the digital. There’s a cracking explanation of logic gates too – the very basics of how computers work. This cites one of the books I learned about such things from, Charles Petzold’s Code. The book compares the iPhone’s computing power to ENIAC: to get the same capability with ENIAC-era technology would cost $50 trillion (roughly world GDP) and weigh the same as 2,500 Nimitz-class aircraft carriers. You could break the Enigma code with your smartphone.

All in all, a real pleasure to read, and a must for anybody interested in what computing is doing to culture and society. Maybe I’ll now have to try Chandra’s novels.

Informal economics

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In a discussion on Twitter last week about the rebasing exercise that increased Nigeria’s GDP by 89%, Olumide Abimbola offered to provide a reading list in informal economic activity – and here it is, very useful.The list includes Keith Hart’s pioneering paper – Keith wrote a retrospective as the intro to a more recent (2006) book, Linking the Formal and Informal Economy: Concepts and Policies, edited by Basudeb Guha-Khasnobis, Ravi Kanbur and Elinor Ostrom.

I have a couple of other suggestions to add.

For estimates of the size of the informal economy in different countries, the work of Friedrich Schneider and Dominic Enste, published by the IMF, is the most comprehensive  – initially in this 2002 publication, but there are no later estimates that I can find, although Schneider and Andreas Buehn have a working paper about methodology.

A nice general read is Robert Neuwirth’s The Stealth of Nations, reviewed by me here.

And, in terms of the economics literature, that’s about it. Which is extraordinary when you think about what an important phenomenon informal economic activity is. The IMF estimates put it at between 14/16% of GDP in the OECD countries (much more in some) to as high as 44% in low-income countries. Economists can be lazy about finding data, and ignoring phenomena for which there are no readily-available data. But surely this is too big to ignore? All the more so as:

  • globalization has allowed multinational criminal enterprise (as well as international finance) to flourish – see Misha Glenny’s reportage eg in McMafia or the wonderful Treasure Islands by Nicholas Shaxson on tax evasion
  • new technologies have changed the decision margin between formal and informal activity in several ways – for example, mobiles helping people in the developing world transition into the formal sector
  • in the digital world, new types of “peer production” are emerging, in a new kind of informal space the authorities don’t know how to deal with – The Umlaut had a very interesting article about this recently. And then there’s Bitcoin etc.

On Twitter, @illicit_econ does sterling work linking to articles and news of interest on the subject. Which economists out there are publishing research on the informal and/or illicit economy, though? Who can add more to this resource list?