Mr. Lehman could predict the prices of foreign-exchange futures more accurately than he could call a coin flip. But, being a rat, he needed the right bonus package to do so: a food pellet for when he was right, and a small shock when he was wrong. (Also, being a rat, he was not very good at flipping coins.)

Mr. Lehman was part of “Rat Traders,” a project overseen by the Austrian conceptual artist Michael Marcovici, whose work often comments on business and the economy. For the project, Marcovici trained dozens of rats to detect patterns in the foreign-exchange futures market. To do this, he converted price fluctuations into a series of notes played on a piano—if a price went up, the next note was higher—and then left it up to the rat to predict the tone of the note that followed. With some prodding, the rats began forecasting price changes, and Marcovici says that they were outperforming human traders after a few months of training—a claim, though, that’d require testing more thorough than what was done here.

As I exchanged emails with him, Marcovici never referred to his rats as part of an art project, and in a video interview he gave back in 2009, when the project was nearing its end, he never so much as displayed a sliver of a smile. But his satire is not hard to detect: “Rat Traders” has its own mock-corporate website, where it says that the company is headquartered in the Cayman Islands.

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.

Most prediction strategies turn out to be hollow correlations that don’t last. Still, people want to believe in the predictability of the stock market, perhaps as a way of coping with the stresses of investing, or even as a way of coping with the discomfort of dealing with a truly chaotic system. So, when people like Marcovici come along, many want to believe that his artwork is a shortcut to personal profit: Business Insider’s unquestioning tone in covering “Rat Traders” a few weeks ago later prompted the site to issue a disclaimer (“NOTE: This is a joke.”) at the top of the post.

The money manager and author David Leinweber once sought to prove the coincidental nature of predictions by seeking out any historical data that miraculously aligned with the stock market at the time. Finally, he found a promising indicator: Butter production in Bangladesh could be used to predict the variation in the S&P 500 index with 75 percent accuracy over the course of more than a decade. When he factored in U.S. cheese production and the number of sheep in the U.S. and Bangladesh, his accuracy shot up to 99 percent over the same period. After writing about the Bangladeshi butter correlation his book, Leinweber told The Wall Street Journal that he received several requests from overeager traders hoping he would distribute his data. “A distressing number of people don’t get that it was a joke,” he said.