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 that will actively trade exchange-traded funds and baskets of underlying securities.

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.

Systematic traders of all stripes are investing in machines designed to improve over time without explicit human instruction in order to get ahead of the pack.

Millburn’s new equity fund will use machine learning to decipher signals from ETFs in order to make bets on the products and baskets of 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.

Millburn is the successor to a quant shop set up back in 1971, shortly before research into options pricing helped unleash an explosion of systematic trading. The firm’s managed-futures program launched in 1977, representing one of the world’s longest-running trend-following strategies.

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