Sunday, November 20, 2016

Investing AI: "Why Machines Still Can’t Learn So Good"

Everyone wants to be the next Renaissance Technologies and are looking for undiscovered data sources and/or connections, some of it gets pretty strange, some links after the jump.

From Bloomberg;
  • Man AHL took three years to create machine-learning strategy
  • Algorithms fail at 90% rate in live tests, a quant says
Anthony Ledford and his colleagues at Man AHL spent three painstaking years building a machine-learning model to do something mere mortals often can’t: find fresh ideas in an avalanche of data.
But even Ledford, chief scientist at the $19 billion Man AHL in London, rolls his eyes when he hears people say that machine learning, a type of artificial intelligence, is going to transform hedge funds tomorrow. To Ledford, a lot of the buzz smacks of hype. The technology is more robust than its predecessors but hardly revolutionary.

“There is some real science here, but it’s not the way it’s been portrayed,” said Ledford, who holds a Ph.D. in mathematics. “Some of it is really marketing, and that’s the bit that annoys me.”

Hedge funds, stung by eight years of underperformance, are latching onto machine learning as a high-tech answer to their woes. But Wall Street’s heady search for the perfect money machine has collided with a sober reality. The technology, which learns on its own to find investment ideas by hunting through troves of data, requires a heavy commitment of time and money, and a high tolerance for failure, since most algorithms turn out to be duds.

‘Unrealistic Expectations’
“I’m concerned that people may have unrealistic expectations of what is possible with the current state of the art,” David Siegel, co-founder of quant pioneer Two Sigma Investments, said at a Bloomberg summit in September. Siegel, a Ph.D. in computer science who says he’s impressed with AI’s performance in many fields, cautioned: “Machine learning systems can easily, with high confidence, make mistakes.”

The performance of AI, which doesn’t have a long track record, isn’t eye-popping. The Eurekahedge AI Hedge Fund Index, which tracks 12 pools that utilize AI as part of their core strategies, has returned an average of 9.3 percent from 2011 through 2015, and is up 13.8 percent this year through September. Those gains mostly beat the average hedge fund in the five years, but often lost to the S&P 500 Index....MORE 
HT: Abnormal Returns

If interested, see also last September's "Wall Street’s Insatiable Lust: Data, Data, Data" and the links therein:
We've been posting on the phenomena for a half-decade, since some ex-Google guys started collecting free-to-download weather data and figured the easiest way to make money off it was to peddle crop insurance. They ended up selling themselves to Monsanto for $930 million. Here's an overview of the opportunity from a few years ago:
McKinsey: Monetizing Freely Available Data Worth $3.2-$5.4Trillion per Year

From the Wall Street Journal, Sept. 12:
‘The opportunity we are chasing is that in all this huge data there are little nuggets of alpha gold’...