AQR head of machine learning set to leave after 7 months

Marcos Lopez de Prado, head of machine learning at AQR Capital Management, is set to leave after less than a year at the firm.

AQR named Bryan Kelly, a researcher and Yale professor of finance, as the new leader of the AI effort, according to a person familiar with the matter. As part of the change, the firm bought certain intellectual property owned by Mr. Lopez de Prado, including multiple patent applications related to machine learning.

“We appreciate Dr. Lopez de Prado’s insightful contributions, we value his thought leadership, and we wish him every success in his future endeavors,” Suzanne Escousse, an AQR principal, said Friday in a statement.

The quantitative investing giant, which was co-founded by billionaire Cliff Asness and manages $196 billion, has struggled to make money for investors recently. More than half of its about 40 funds lost money in the past year, according to data compiled by Bloomberg.

Mr. Lopez de Prado, who holds two doctorates, had earlier worked at Guggenheim Partners where he helped build a proprietary quantitative-strategy business that managed as much as $13 billion.

When Guggenheim announced Mr. Lopez de Prado’s departure in early 2018, it said he was leaving to start his own business and agreed to transfer to him the quant unit he started. As part of the agreement, Guggenheim said that it had amicably resolved a dispute over ownership of intellectual property, some of which was developed by him during his time at the firm.

AQR hired him in September to fill a newly created role, leading a group in analyzing complex data for strategy development.

“During my tenure, I enjoyed collaborating with the innovative team at AQR on machine learning tools and techniques, and I am confident that AQR will continue to succeed for decades to come,” Mr. Lopez de Prado, a principal at the firm, said in an email.

Mr. Kelly has been with Greenwich, Connecticut-based AQR for three years. He has a doctorate from NYU’s Stern School of Business and worked as an analyst at Morgan Stanley (MS). Last year he co-authored a paper on asset pricing and machine learning, and has researched topics including volatility, market efficiency and hedge fund returns.