Day Trading Is a Sucker’s Game

I’ve got bad news for all you day traders out there. Just like assembly-line workers, switchboard operators, copy clerks, and hand weavers before you, you’ve now been automated out of existence.

Why, you ask in dismay? The latest issue of Wired explains everything.

It would appear that yet another exotic breed has been spotted in the thickets of the Wall Street jungle—or more accurately, in suburban New Jersey, which is where all the high-speed servers and fiber-optic cables that are their lifeblood are located. This new breed, the high-frequency trader, or HFT, is a scientifically engineered, ultra-streamlined version of the financial sharks of yesteryear.

Or rather they’re not, since they’re not really like investment bankers, stock analysts, junk-bond dealers, corporate raiders, sellers of complex derivatives, or any other species we’ve seen before. In fact, they’re not really interested in the stock business at all, if by “business” one means the furnishing of capital to companies so that the latter may profitably market their goods and services and go on to share the resultant bounty with investors.

What they are interested in is numbers. Streams and streams of numbers. Their approach is to develop algorithms that detect minute changes in stock prices and then to have computers place buy or sell orders on the basis of the patterns in the fluctuations. If an algorithm notices, for example, that a particular stock’s price has gone up for several minutes consecutively, it might decide to hop on the gravy train, buying up lots of shares, only to dump them a second later. Each individual sale might only net the user a fraction of a cent, but multiply that by several hundred shares a day, and by tens of thousands of iterations between 9:30 a.m. and 4 p.m., and you have, in theory at least, the possibility of some serious positive cashflow.

These HFTs (also known as “Quants”) draw their ranks not from MBAs but from former physicists, engineers, IT geeks, and even pro poker players, and they seem to share a curiously abstract view of the stock market, regarding it as a kind of abstract mathematical puzzle akin to Sudoku—you can imagine them getting together on Saturday nights to discuss Fibonacci sequences or proofs for Fermat’s Last Theorem. They don’t bother to concern themselves with p/e ratios, quarterly dividends, or earnings per share, let alone with the companies they trade in or the products made by those companies. Instead, they focus on evermore complex methods of data mining, as well as the hope of ever-faster modes of information transmission, since their profits derive from their ability to stay ahead of the curve, however infinitesimally. Their One Great Hope is the Perfect Transmission Network, one that would enable their remote transactions to be executed on Wall Street at the speed of light—in other words, without the lag time, sometimes several excruciating microseconds in length, currently imposed by technological limitations.

If all this sounds slightly insane, it’s because it is. Especially when one learns just how small the profits involved are. One HFT at a recent conference in London hypothesized that under ideal conditions—famous last words—his latest algorithm would be able to execute 64,000 trades per day, at an average profit of $0.0001 per trade, for a grand total of $600. Not shabby, by any means, but at that rate, he might as well get an honest job. Another researcher speculated that by buying up all the Tweets issued during a given time period—say, six months—and then aggregating them and analyzing them for words with emotional content (“calm,” “happy,” “relaxed,” and the like), it would be possible to divine America’s financial mood and thus predict the course the Dow will take a few days down the line.

Interesting? Sure. Sound investing strategy? Highly debatable.

What all this means for you is that now more than ever, day trading is a fool’s errand. If you were ever tempted to enter the fray, recognize once and for all that those banks of computers chugging away at their algorithms have you hopelessly outclassed. There’s simply no way an individual human being can compete against a fleet of CPUs that rivals NASA’s. Do not, I repeat, do not try it. You will lose.

The good news is that this means that our formula for investing is now at an even greater premium. The ingredients of that formula are the same as ever: (1) Find good-quality companies; (2) Buy said companies’ stock at good prices; (3) Be patient. You don’t need to be the fastest trader, or have the most gizmos working for you. You don’t have to make the perfect trade every time. What you do have to do is research the companies thoroughly, and focus on the long term.

The cult of the financial analyst was laid in its tomb ten years ago. Now the much-vaunted figure of the day trader is headed for the same scrap heap. But the intelligent investor is left standing, even if a robot beats him out of a fraction of a penny. And we’ll still be here even when all those transmissions actually take place at the speed of light, thus depriving the HFTs of their modus vivendi.

In the meantime, it’s best to remember those haunting words by T.S. Eliot, himself a Lloyd’s Bank employee:

Between the order
And the confirmation
Between the bid
And the ask
Falls the shadow.

Posted by on August 8th, 2013 at 2:20 pm

The information in this blog post represents my own opinions and does not contain a recommendation for any particular security or investment. I or my affiliates may hold positions or other interests in securities mentioned in the Blog, please see my Disclaimer page for my full disclaimer.