Remember the improbably rich tow truck driver in the old commercial? The unshaven, ungainly driver caught his passenger—a guy in a pressed white shirt and tie—by surprise. Not only was a copy of Barron’s resting in the trucker’s front seat, but the disheveled fellow had made enough money to retire and, yes, buy his own island. (He continued to drive the truck because he liked to help people out.)
That spot ran in 1999, right before the dot-com crash in 2000 that, presumably, cost the trucker/investor his nest egg and possibly his island. The days of the get-rich-fast individual investor are not what they used to be. And they may not have been what we think they were.
The only people making real money day-trading individual stocks in 2013 have state-of-the-art computer algorithms on their side executing trades at lightning speeds. Once the exclusive province of Wall Street investment banks and hedge funds, Forbes reports that algorithmic trading is now beginning to “trickle down” to the individual investor:
Armed with $4.5 million in funding, the 2011 Harvard grad [Christopher Ivey] recently launched a Web-based platform called Rizm, designed to let individual investors with no coding skills build computer programs that select and trade stocks automatically, similar to the trading programs used by quant funds and high-frequency trading firms.
The pitch: For $99 per month investors get quick cloud access to sophisticated algorithm-building tools and the capability to back-test strategies. You can easily generate rapid-fire executable trades, sans emotion, and place them with an e-broker.
Suddenly the notion of blasting out math-driven trades like über-successful quant hedge funds, such as James Simons‘ Renaissance Technologies, are a few clicks away.
“If you can only follow five trades a day, because that’s the mental bandwidth for a human trader, now run it against 500 stocks,” says Ivey. “Or just let it run on your five, and go spend time with your daughter and hang out, because it’s running for you.”
There are problems with a stock market run overwhelmingly by machines rather than traditional investors concerned with such hoary details like a company’s earning reports and forecasts. But never mind such nostalgia for slower, wiser times. If the argument in Tyler Cowen’s new book Average is Over is sound, the geekiest will rise to the top while luddites and technophobes will languish in poverty. If this sounds worrisome, there is an upside: the opportunity gap I have written about will dissolve as the most industrious people thrive in a new “hyper-meritocracy.” Andrew Lewis explains:
If this process holds, it’s not difficult to see why incomes will become increasingly polarized. The top end of the income distribution—which he envisions as the 15 percent, rather than the 1 percent—will be comprised of those who are truly talented or creative in their ability to work with technology. These folks will “win” the most in the new system because of their ability to make computers more productive. The rest of the population will fall into lower paying service jobs.
This idea is sobering, but one major benefit of this future would be the reduction of “opportunity inequality”. These trends will disenfranchise many subpar performers (and their shortcomings, he says, will be increasingly illuminated by an array of public fora for reviews, as well as various automated assessments of value). But they will also reward those who are most deserving—a fact, says Cowen, that “will make it easier to ignore those who are left behind.”
Thus the advance of machine intelligence will cause a surge in income inequality, but will also level the playing field for opportunity. In a recent interview with NPR Cowen predicted that “for a lot of people upward mobility will be a lot easier.”
So there’s your uplifting message, and your kick in the pants. Put down your Schlitz and get your MOOC on, or something.