Tag Archives: high-frequency trading

Hackers could skim microtime cream from stock markets

As if I needed more reasons to mistrust the wild and wacky world of high-frequency trading [via SlashDot]:

High-frequency trading networks, which complete stock market transactions in microseconds, are vulnerable to manipulation by hackers who can inject tiny amounts of latency into them. By doing so, they can subtly change the course of trading and pocket profits of millions of dollars in just a few seconds […]

[…] the root of the problem is the increasing speed of networks; as they get faster and faster, our ability to actually understand events taking place within them isn’t keeping up. Network monitoring technology can detect perturbations in network traffic happening in milliseconds, but when changes occur in microseconds, they’re not visible, he says.

Basically, if you can exploit these tiny differences in latency, you can make your trade before your rival, and get a better profit. For doing, y’know, sweet f*ck all.

Given that the above article comes from an IT news source, this problem is being framed as a hack or exploit; I dare say there’s a lot of trading firms who’d see it as more of a “competitive edge”.

Location, location, location

Why would anyone in their right mind consider building a server farm in deepest darkest Siberia, or the middle of the Indian Ocean? Possibly because the intersection of geography and information flow means such locations would give you a slight yet crucial edge in the high-stakes imaginary-money game of high-frequency trading [via SlashDot]:

The insight of the MIT researchers, Alexander Wissner-Gross and Cameron Freer, is that some automated traders–or at the very least, their server farms–will be best positioned in-between certain exchanges. Since some trading strategies capitalize on price fluctuations between separate exchanges in different parts of the world, the optimally located server will receive information from those exchanges at precisely the same moment, gaining that millisecond advantage over the competitor. In some cases that pefect location is the midpoint between the two exchanges, but not always–it depends on whether the exchanges’ prices move at the same speed or not.

Wissner-Gross and Freer rounded up the locations and price-speeds on the 52 largest global exchanges, and plotted a map of the ideal locations for traders who would want to be perfectly positioned between any given pair. The map, which appears today in an article in the journal Physical Review E, dictates that some traders’ servers will be ideally positioned in central Africa, others in the remotest forests of Canada, others in the middle of the Indian Ocean, and still others in Siberia. This all assumes, of course, a proper infrastructure in place–in the short term, Freer tells Fast Company, it might make more sense to approximate these locations, rather than invest in installing a server farm underneath the ocean.

Brilliant… yet another way for compulsive gamblers to squeeze more profits out of the aether (not to mention shades of Ian McDonald’s Dervish House – which, if you haven’t read it yet, should be added to your stack of pending reads with immediate effect). But according to New Scientist, this might actually represent the last possible way to grasp advantage in the automated trading system:

“This shows that the technological arms race to extract every penny from high-frequency mechanical arbitrage will soon reach its ultimate limits,” says physicist and hedge-fund manager Jean-Philippe Bouchaud, based in Paris. “Maybe the buzz around high-frequency trading will then calm down.”

We can live in hope, I guess.

Econopocalypse scenario #3654: the Fat-finger Collapse

Ars Technica has an interesting article about a couple of recent stock-market glitches caused by high-frequency trading algorithms run amok. Long story short: a screw-up at Credit Suisse was caused by “a trader who accidentally double-clicked an icon in a trading program’s interface, when he should’ve single-clicked.Yipes.

OK, so it’s not quite the same as a tired technician leaning on the nuclear launch button by accident, but given the utter dependence we have on the instruments of high-speed high finance, similar mistakes could cause global catastrophes. [image by Coffee Maker]

The problem is connected to so-called “day-traders”, computer-assisted stock deals that occur in the blink of an eye, often without much human interaction, and minor errors are amplified at the speed of light (or at least the speed of data in optical fibers) by the networks, causing fluxes that folk like you and I never notice, but which cost bankers and investors thousands of dollars in losses and fines…

Of course, the fact that such computer-driven volatility hurts day traders matters little to long-term investors. But the fear is that these glitches are fleeting indications that the system as a whole is vulnerable and unstable, and that the right combination of circumstances could cause what happend to RMBS to happen on a wider scale. This is especially true as even more of the trading activity, even among individual traders, shifts to automated platforms.

However, it’s not all doom and gloom; the last few years have seen a sharp increase in small trading firms of the two-guys-and-a-fast-computer type, small independent operators using the same techniques as the big banks to trade automatically through the blind of commercially-available trading software.

The Obama administration’s efforts to rein in high-frequency trading by eliminating flash orders and banning proprietary trading (much of which is HFT-based) from large banks will probably have the effect of leveling the playing field a bit for these smaller algo shops. As Matthew Goldstein at points out in his Reuters article on the topic, the prop desks may disappear, but the software and expertise will not. Instead of being concentrated at a few large banks, algo trading will just spread, as the talent behind it either jumps to new funds or goes solo.

Once again, the network corrodes hegemony… but whether a world where anyone and his dog can engage in automated high-frequency wheeler-dealing will be a safer, better and richer one remains to be seen.

Get up to speed on high-frequency trading

New York Stock Exchange buildingRemember that story we ran a few weeks back about the alleged theft of the Goldman-Sachs automated trading code?

Well, thanks to said case, Goldman-Sachs and the high-frequency automatic trading (HFT) practices that they dominate are increasingly sliding into the spotlight of Congressional scrutiny, so Ars Technica have knocked up a brief guide to what it’s all about. If you thought “the markets” were those guys in suits shouting at each other on the trading room floor, think again. [image by Coffee Maker]

If you look under the hood of the markets in 2009, you’ll find that the trading floor has been replaced by electronic networks; the frantic, hand-signaling traders have been replaced by computer systems; and all of moves in the trader’s dance—a thousand little tricks and techniques (some legal, some questionable, and some outright illegal) for taking regular advantage of speed, location, and information to generate profits—are executed hundreds of times per second, billions of times per day. And the whole enterprise is mainly powered by the same hardware from Intel, AMD, and NVIDIA, that Ars readers use for gaming.

[…]

Only about three percent of the trading volume on the NYSE is actually carried out by means of traditional “open outcry” trading, where flesh-and-blood humans gather to buy and sell securities. The other 97 percent of NYSE trades are executed via electronic communication networks (ECNs), which, over the past ten years, have rapidly replaced trading floors as the main global venue for buying and selling every asset, derivative, and contract. So the ECNs are the markets in 2009, and those pit traders who pose for the cameras are mainly there for the cameras.

In other words, Josephine Average Stock-Trader is going head to head with supercomputers every time she dips a toe into the game. The ECN algorithms specialise in making millions of tiny trades, each making fractions of pennies of profit – small beer when considered in isolation, but big profits when scaled up to the sheer volume of transactions that these systems can handle.

It’s like a vast virtual ecosystem of predatory code-critters; go find out more about it. Know thy enemy, and all that.