Bloomberg: traditional quant money manager shifts to machine learning

A $7.5 billion money manager with roots almost as old as quant investing itself is going all-in with machine learning. Millburn Ridgefield Corporation placed robots at the very heart of its open systematic strategies after a six-year experiment. Now, the New York firm is raising cash for a new computer-powered strategy trading single-name stocks.

Millburn is banking on artificial intelligence as it moves further away from its 1970s-era tradition in trend following, which typically uses futures contracts to surf the momentum of assets. Co-chief executive Barry Goodman says statistical-learning programs scanning a broader set of data can figure out the nervous system connecting markets. That’s how the firm plans to beat the increasingly crowded world of quantitative investing.

“The machine-learning approaches in a broad sense allow us to adapt relatively quickly to environments where alpha gets arbitraged away, or where the structure of the markets themselves changes,” the Millburn executive said in an email to Bloomberg. Millburn’s new equity fund will use machine learning to decipher signals from exchange-traded funds in order to make long bets on the underlying securities such as members of the S&P 500 and MSCI World.

The algorithm, for example, might discover that momentum trades work best during seasonal shifts in volatility — something often buried in masses of data. “Figuring this out is not trivial, and not something humans could do,” according to Goodman, who joined the company in 1982.

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