nav search
Data Center Software Security Transformation DevOps Business Personal Tech Science Emergent Tech Bootnotes BOFH

Hey, Michael Lewis: Stop DEMONISING Wall Street’s SUPERHUMAN high-speed trading

HFT's NOT the free-market crusher new book says it is

By Tim Worstall, 2 Apr 2014

Yesterday's energetic debate on CNBC between BATS Global Markets president William O'Brien and Flash Boys author Michael Lewis and IEX's Brad Katsuyama put the cat among the pigeons over high-frequency trading.

It was all provoked by Moneyball writer Lewis' new book, Flash Boys, which, among other things, makes the claim that the American stock markets are "rigged" as a result of this practice.

This could be true of course: every participant in every market is always trying to rig it to their own advantage. But the important question is not whether people are trying to do so it's whether they are succeeding in doing so – and even if they are could the solution be worse than the problem?

High frequency trading (HFT) basically is just what it says on the tin. It's buying and selling stuff really quickly: even just threatening to do so is used as a technique. At its heart it's a very old technology, it's really just time arbitrage, which has been around for ages.

There was a time, many moons ago, when profit could be made by observing the prices on the London and NY stock exchanges for shares that were listed on both. If the prices diverged (or the exchange rate did) then small margins could be made by buying on one market and selling on the other at the same time.

And it is exactly that buying and selling that moves prices back into equilibrium.

The people who could manage to profit from the London/NY trading differential were those who could get information a little bit faster than everyone else and a better comms system: perhaps privileged access to the telegraph, or later, dedicated phone lines where they didn't have to pay the usual extortionate per minute fees for a transatlantic phone call.

All that HFT does is take this same basic idea and upgrading the technology involved. Stick the process on computers and let them get on with it. Write algorithms that look at past correlations between the co-movements in prices to certain pieces of news and then trade on that linkage on similar future movements in said prices.

Say, for example, that the price of sugar changes: we've seen what happens to the price of Coca Cola stock when this happens. So, get the algo to look at sugar prices and when they twitch, buy or sell Coke appropriately.

Yes, of course, it gets more complicated than this. The algos are working rather more quickly than human traders are. The market is working fast enough that simple latency in communication, light speed itself, becomes a competitive edge here. Traders pay exchanges vast sums to have their servers co-located with the exchanges' own in order to be those milliseconds (and for some, nanoseconds) ahead of the others.

Prices? Do flock off

All of this has some interesting effects. The first of which is just what we would expect from large amounts of time arbitrage going on: prices start to “flock like birds”, in the words of one physicist.

One of the advantages of computers and algos is that they can calculate across those pricing correlations rather faster than we meatsacks can. So not only can we run with the idea that a change in the price of sugar is going to change the price of Coke, but that also of Pepsi, and of the firm that makes Polos and so on, but the relative price changes of the Polo maker and Pepsi and on through the entire marketplace. This isn't quite there yet of course, but there's a very fierce evolutionary race underway. The effective lifespan of an algo is now estimated at a few weeks for example, perhaps a couple of months, before it is out-evolved.

Being able to cross-calculate these price changes also takes us a little closer to being able to plan the economy. This is the “Socialist Calculation Problem” writ small in fact: if you're going to try to plan an economy then you've got to have a method of being able to calculate the interactions in that economy.

You need to be able to make connections between a change in demand, supply or price of one item and the ensuant ripples through the economy. Hayek pointed out that only the market itself can do that, everything's just too complex to handle it any other way. But building these algos that are doing just that is the first baby step along the way to being able to calculate more directly.

There are still a couple of centuries of Moore's Law necessary before we can actually do it in full.

We've perhaps 1 billion items for sale in London at any one time. There's 63 million odd people in the country. We don't actually know the utility function of each person so what are we trying to optimise? And we've got to add in geography. A balti in the East End isn't the same good as one in Glasgow. We're not going to have the computing power to solve those equations for some time yet, but this is the start of the process.

What's the worst that could happen? 'Front running'

On the downside, this concentration on trading speed has enabled some market participants to see large orders before they are transacted. The US stock market include perhaps 13 or 15 actual exchanges.

Given the latency of information travel, those close to one exchange might see a large buy or sell order before other exchanges do: thus they can go and buy and sell that stock before that large order actually arrives, move the price either way by a cent or two and then sell to that large order when it arrives.

This is known as “front running” and can be thought of as being a bit naughty. Certainly, if you get the information from your mate executing the large order and do this you're guilty of insider trading. It's this bit that Lewis is decrying in his new book.

Whether this is important is another matter: most of the book is actually about an exchange that has managed to frustrate this tactic simply by having the fibre optics coiled up in certain lengths so that all market participants see the information at the same time whatever their geography. If there's such a trivial solution perhaps it's not actually a large problem.

But that front running is something entirely different from the basic concept of HFT itself. Bit like a shotgun perhaps: which can be used to get yummy peasants* for tea or to take out the troublesome ex. One isn't a problem, the other is a crime – although both use the same tool.

And the equivalent of our yummy peasants for tea here is that HFT, by its very nature, something that is going to increase the flow of traffic across exchanges. This is also known as increasing liquidity and it has an interesting effect.

There's something called the “bid-ask” or the spread. You cannot both buy and sell Microsoft at $39.95 at the same moment. You can buy at perhaps $39.97 and sell at $39.93 at any one moment: that's the spread (or the fee that you're paying to the bloke willing to do the buying and selling).

More liquidity drops these spreads – so much so that we've had a two orders of magnitude drop in the spread over the last two decades as HFT has expanded. It has plunged from perhaps 0.2 per cent of the order amount in the early '90s to 0.002 per cent today. That saves money for everyone buying or selling anything: yes, including your pension plan even if you've no stock holdings directly.

And it's pretty much a slam dunk that the savings from this collapse of spreads is larger than whatever is being picked off by that (illegal or not) front running.

What Lewis has actually done here is point to one possibly important implication of HFT: front running – which is all rather blown up into a rampage about HFT itself.

Given that HFT makes trading on a market cheaper by orders of magnitude, this might not be all that good an idea, as it confuses the benefits of the greater technology with the costs of one particular use to which people may be putting it.

But then hysterical attacks from Main Street on Wall Street are an evergreen of American public discourse, rather like Islington v The City here in the UK.

And I have seen one proposal for doing away with that front running: let's have a financial transactions tax to make it unprofitable. Something which would, presumably, widen that spread back out to 0.2 per cent again, to the cost of everyone trading anything. What was that thing about babies and bathwater again? ®

*I refer you to the errata slip at the start of 1066 And All That (see page 50 "The Pheasants revolt" et cetera).

Does Algorithmic Trading Improve Liquidity? (PDF) – Terry Hendershott, Charles M Jones and Albert J Menkveld

More on High Frequency Trading and Liquidity – Alex Tabarrok

The Register - Independent news and views for the tech community. Part of Situation Publishing