http://blogs.reuters...requency-trading/

A good read. Some excerpts.

But! If you can lay an undersea cable across the Arctic, you can save yourself about 5,000 miles, not to mention the risk of routing your information past a lot of political flash points. And when you’re sitting in your office in London and you get that dollar/yen exchange rate from Tokyo, it’s fresh from the oven, comparatively speaking: only 0.168 seconds old. If everybody else is using the old cables and you’re using the new ones, then you have somewhere between 20 milliseconds and 60 milliseconds when you know something they don’t.

[...]

The more obvious problem with exchanges run by computers is that computers don’t have any common sense. We saw this on the 6th of May, 2010 — the day of the so-called “flash crash”, when in a matter of a couple of minutes the US stock market plunged hundreds of points for no particular reason, and some stocks traded at a price of just one cent. It was sheer luck that the crash happened just before 3pm, rather than just before 4pm, and that as a result there was time for the market to recover before the closing bell. If there hadn’t been, then Asian markets would have sold off as well, and then European markets, and hundreds of billions of pounds of value would have been destroyed, just because of a trading glitch which started on something called the e-mini contract in Chicago.

Most of the trading on US stock exchanges is done by something called algobots, these days. These are algorithms: they’re computers which are programmed to put in orders, take out orders, trade in big size, trade in small size – all according to very sophisticated rules, called algorithms. And one of the ironies about the flash crash is that it was actually caused in large part by algobots not trading. The US has over a dozen different stock exchanges, places where stocks are bought and sold. Most of us have only ever heard of the listing exchanges, the New York Stock Exchange and the Nasdaq. But there are many more you probably haven’t heard of, with names like Arca and BATS, as well as sinister-sounding things called Dark Pools. What happened in the flash crash is that when the trading got completely crazy, the algobots just switched themselves off. This was something they weren’t used to, they didn’t know how to react, and so they just went away. And there was suddenly no liquidity in the market. No one was offering to trade. And with no one offering to trade, the prices just plunged, all the way down to one cent. Because there were no bids in the market any more.

[...]

In any case, if any given stock exchange is an incredibly complicated thing, the fragmentation of the stock exchanges has created a much more complex system yet. Most big banks and stockbrokers — and the algobots they control — have access to all of the different exchanges, and they trade wherever they think they can get the best prices. Since the best prices tend to be found wherever the most traders are trading, you end up with something a bit like six-year-olds playing football: everybody’s running towards the ball at the same time. And the result is these huge waves of activity, where traders move en masse, from one stock exchange to the next, in very unpredictable ways. If you layer that unpredictability on top of the complexity inherent in any system of multiple stock exchanges, you end up with something which will almost certainly break in a pretty catastrophic manner at some point. We don’t know how, and we don’t know when, but there’s an ironclad rule of any system: the more complex it is, the less predictable it is, and the more likely it is to fail catastrophically in some unforeseeable manner.

[...]

This is a real improvement, which means that the rise of high-frequency trading had genuinely beneficial effects between, say, 2002 and 2007. In those years, the computers helped markets to become ever more efficient and liquid — and they were just in time, too. When the financial crisis came along in 2008, bond markets seized up, but the world’s stock markets actually came through with flying colors. They did what markets are supposed to do: they went down when people were selling, and they kept on falling until they were so cheap that people started buying again. If you wanted to sell, you could always sell, and if you wanted to buy, you could always buy. We take these things for granted, but creating a system which stays that liquid, all the way through such a big crisis, is a real achievement, and the algobots deserve a lot of credit there. After all, imagine what would have happened if you had to phone up your broker at Lehman Brothers in order to sell your shares.

But if you look at what’s happened over the past five years, since 2007, the benefits of high-frequency trading have pretty much plateaued. And the downsides are becoming more and more obvious. There was the flash crash, of course, and then there was the implosion of Knight Capital, one of the biggest and most respected high-frequency trading shops, which released a faulty algorithm one morning and was almost bankrupt an hour later, after losing somewhere in the region of $10 million per minute. If that could happen to Knight, it could happen to anybody. Then there was the botched flotation of one of the stock exchanges, BATS. Once again, its algorithms turned out to be not up to the task. And this was in an expected, rather than an unexpected, situation.

[...]

There's a simple solution to the problems in high-frequency trading - a transactions tax. (And maybe a tax on "price probing" offers of trades that are placed then immediately canceled as mentioned in the comments.) We need it. But if Rmoney and his ilk win, then it's more likely for "Job Creators" like these folks to get tax credits and rebates for laying fiber every which way to save another few microseconds than for this stuff to be reigned in.

Cheers,
Scott.