But the algorithms we see at work here are different. They don't serve any function in the market. University of Pennsylvania finance professor, Michael Kearns, a specialist in algorithmic trading, called the patterns "curious," and noted that it wasn't immediately apparent what such order placement strategies might do.
Donovan thinks that the odd algorithms are just a way of introducing noise into the works. Other firms have to deal with that noise, but the originating entity can easily filter it out because they know what they did. Perhaps that gives them an advantage of some milliseconds. In the highly competitive and fast HFT world, where even one's physical proximity to a stock exchange matters, market players could be looking for any advantage.
"They are moving the high-frequency services as close to the exchanges as possible because even the speed of light matters," in such a competitive market, said Stanford finance professor Peter Hansen.
Given Nanex's data, let's say that these algorithms are being run each and every day, just about every minute. Are they really a big deal? Donovan said that quote stuffing or market spoofing played a role in the Flash Crash, but that event appears to have had so many causes and failures that it's nearly impossible to apportion blame. (It is worth noting that European markets are largely protected from a similar event by volatility interruption auctions.)
But already since the May event, Nanex's monitoring turned up another potentially disastrous situation. On July 16 in a quiet hour before the market opened, suddenly they saw a huge spike in bandwidth. When they looked at the data, they found that 84,000 quotes for each of 300 stocks had been made in under 20 seconds.
"This all happened pre-market when volume is low, but if this kind of burst had come in at a time when we were getting hit hardest, I guarantee it would have caused delays in the [central quotation system]," Donovan said. That, in turn, could have become one of those dominoes that always seem to present themselves whenever there is a catastrophic failure of a complex system.
There are ways to prevent quote stuffing, of course, and at least one of the members of the Commodity Futures Trading Commission's Technology Advisory Committee thinks it should be outlawed.
"Algorithms that might be spoofing the market are something that should be made illegal," said John Bates, a former Cambridge professor and the CTO of Progress Software. But he didn't want this presumably negative practice to color the more mundane competitive practices of high-frequency traders.
"There is algorithmic terrorism and then there is reverse engineering, which is probably just part of good business practice," Bates said.
For now, Donovan plans to keep putting out the charts, which he calls "crop circles," of the odd trading algorithms at work. That's an apt name for the visualizations we see of this alien world of bot trading. And it certainly gets at a central mystery surrounding them: if trading firms aren't sending out these orders, how are they getting into the market?
On the quantitative trading forum, Nuclear Phynance, the consensus on the patterns seemed to be that they simply just emerged. They were the result of "a dynamical system that can enter oscillatory/unstable modes of behaviour," as one member put it. If so, what you see here really is just the afterscent of robot traders gliding through the green-on-black darkness of the financial system on their way from one real trade to another.
No matter why the bots end up executing these behaviors, the Nanex charts offer a window onto a kind of market behavior that's fascinating and oddly beautiful. And we may never have seen them, if not for the mildly obsessive behavior of one dedicated nerd.
"Who looks at millisecond charts?" Donovan said. "You'd never see those patterns in any other fashion. The SEC and CFTC certainly weren't."
Here are a few more bots at work with explanations of what's going on.
Here we see a "flag repeater" being executed on the BATS Exchange, the third-largest equity market after the NYSE and NASDAQ. 15,000 quote requests were made in 11 seconds in a repeating pattern. Each iteration upped the quote a penny until $9.36, and then the algorithm went down the same way, a penny at a time.
This is an extreme closeup of just one second of trading of the stock SHG, the Shinhan Financial Group. This is 760 quotes from a total of 10,000 made in 12 seconds.
This chart shows a different kind of strategy. It represents 56,000 quotes in one second all at the same price (the top chart) but with the size of the order increasing by one (i.e. 100 shares) all the way up to 40,000.