Marcovici got the idea of training rats to make investment decisions after thinking about the highly-paid jobs that might not need humans in the future. The default assumption is that these jobs will be taken over by robots, but Marcovici wondered if rats might be able to recognize patterns in the data that humans, with their messy biases and status concerns, overlook.

To test this, he set up a semi-scientific training program. Rats spent as much as five hours a day for three months making predictions in the temperature-controlled boxes Marcovici built for them. Correct picks were rewarded with food, and incorrect picks were punished with minor shocks. “The good rats became fat very fast,” Marcovici wrote on his website.

Over the course of months, he began weeding out the rats that traded at less than 52 percent accuracy. After trials with about 1,000 piano tracks, Marcovici was left with four “really gifted traders,” which he then cross-bred to produce a generation that outperformed their progenitors. One rat in this second generation, Mr. Kleinworth Morgan Jr., had a 57 percent accuracy rate. “I managed to outperform some of the world’s leading human fund managers,” Marcovici wrote. (His findings did not undergo tests for statistical significance, and the rigor of his experimental design is limited at best.)

Accuracy Rates for the Offspring of Mr. Morgan and Ms. Kleinworth

Michael Marcovici

In an interview five years ago, he said that multiple hedge funds were interested in testing his rats, but that interest didn't pan out. Even if it were verified that a rat could predict prices, Marcovici says now, one bottleneck is that a rat can only make about 20 trades before getting tired—so hedge funds would need a lot of rats to accumulate any useful amount of data. That said, he’s still in “loose contact” with some hedge funds, should they change their minds. Marcovici himself retired the project years ago. “With about 100 rats at home I had to stop at some point with the experiment,” he says.

“Rat Traders” is founded on the assumption, perhaps the universal desire, that historical market data can be used to predict prices. “Because people are the ones who influence prices,” Marcovici insisted in one interview, there are patterns, shaped by human biases, detectable in the numbers. There’s little in the way of literature to back that up, but one 2011 study did find that patterns could be used to predict stock prices for up to one minute. Another recent study found that stock prices could be predicted by activity on Twitter.

But when Mashable talked to one author of that Twitter study, he said he wasn't sure why he found that correlation. And that’s the point here: It’s fairly clear that the price of any given stock cannot be predicted, and that anyone who tries to predict it is, without an undue amount of luck, fated to fail. A far-reaching survey of 60,000 households in the early ‘90s done by researchers from the University of California Berkeley confirmed this: “Our central message is that trading is hazardous to your wealth,” they concluded.