How Three Billionaire Investors Leveraged AI to Double Their Wealth in One Year

How do the academic backgrounds of the three founders influence AQR’s AI strategy?

After a tough period, investment firm AQR has maintained a strong momentum for five consecutive years with new investment strategies that incorporate AI and highly tax-efficient returns, successfully attracting financial advisors.

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Last year was a bumper year for many hedge funds and quantitative firms, and Applied Quantitative Research (AQR), based in Greenwich, Connecticut, was no exception. The company’s assets under management soared to $187 billion, an increase of $73 billion just in 2025. The net worth of its three billionaire founders also doubled.

AQR’s Chief Investment Officer, Cliff Asness, who holds a PhD, owns about 30% of the company and is the largest individual shareholder. His current net worth is $6.3 billion, ranking 664th on the global billionaire list. Co-founders John Liew and David Kabiller each saw their fortunes rise above $2 billion. These three founders previously worked together at Goldman Sachs Asset Management and founded AQR in 1998. They still invest heavily in their own funds, with personal wealth closely tied to company performance.

According to an anonymous source who shared non-public information, last year AQR’s core multi-strategy fund Apex, with $6.7 billion in assets, achieved a 19.4% return. Its Delphi long-short strategy fund, also with $6.7 billion in assets, returned 16.7%. The source added that over the past five years, these two funds averaged an annualized return of 16.6% (compared to the S&P 500’s 14.4%). AQR’s equity market-neutral fund, one of more than twenty open-end mutual funds, had $3.2 billion in assets, holding about 2,000 long and short positions, with a projected return of 26.5% in 2025. Over the past five years, its average annual return was 19.6%, far exceeding the typical 8% for similar funds.

If AQR can sustain last year’s growth trajectory, its assets could soon surpass the record high of $226 billion set in 2018. For a company that only four years ago struggled with poor performance, client attrition, and assets falling below $100 billion, this would be a remarkable comeback.

This turnaround coincides with AQR fully embracing AI and consciously expanding machine learning techniques in research and trading.

AQR is a factor investing firm that traditionally used valuation metrics like price-to-book or return on equity to identify over- or undervalued stocks, then manually set weights for different factors to drive stock selection. Now, machine learning is taking over—identifying complex interactions among factors, recalibrating weights in real-time, and mining massive datasets for predictive signals. Analysts are also leveraging NLP technologies like ChatGPT or Claude to sift through vast amounts of information to optimize their models.

Both founders, Asness and Liew, studied under Eugene Fama, a Nobel laureate in economics and proponent of the efficient market hypothesis, at the University of Chicago. Compared to peers like Renaissance Technologies and D.E. Shaw, AQR’s AI initiatives started later. The firm hired its first head of machine learning in 2018, but he left after just seven months. His successor, Yale finance professor Brian Kelly, made a significant impact. In December 2021, Kelly co-authored a 141-page academic paper titled “The Virtue of Complexity in Return Prediction,” concluding that more complex machine learning models outperform simpler ones in predicting stock returns and constructing portfolios. Several scholars responded, criticizing the narrow data set used in the study. AQR defended the paper and maintained its findings.

Recently, Asness has also taken on the role of AI evangelist.

He stated that AQR has “given more decision-making power to machines” and that even he might be replaced by AI in his work. While these claims sound sensational, insiders insist that human roles remain vital. One source said, “Machine learning and AI have indeed improved our processes, but they are an evolutionary step rather than a disruptive revolution.”

In fact, the real revolution seems to be happening in the less glamorous sales side. Financial advisors increasingly need tax-efficient funds for wealthy clients, and AQR is well-positioned to meet this demand. These investors—rather than traditional institutional clients like pension funds and endowments—are now the firm’s largest source of capital inflows. The CEO of Affiliated Managers Group, which holds a minority stake in AQR, said during last month’s earnings call that AQR’s financial advisor client base is “driving significant organic growth,” with net inflows of $51 billion in the past year primarily from AQR.

Particularly strong is AQR’s Flex separately managed account (SMA)—a multi-strategy long-short investment tool aimed at financial advisors and high-net-worth individuals. This tax-efficient portfolio buys stocks expected to rise and shorts those expected to fall, aiming to profit from both directions, reduce market volatility, and limit taxable dividends, thereby preserving more after-tax returns. According to their website, Flex’s assets were $23.2 billion a year ago. Nine months later, it nearly doubled to $45.4 billion. By the end of 2025, Flex will account for nearly a quarter of AQR’s total assets.

Justin deTray, a financial advisor at WealthSpire, which manages $580 billion in assets and is based in the Bay Area, said that Flex’s popularity among registered investment advisors (RIAs) is due to lower fees and greater “prestige” compared to newer entrants trying to break into this space. Additionally, long-term market prosperity has benefited new tech millionaires eager to lock in their wealth. DeTray noted, “Many potential clients have substantial unrealized gains in tech giants or large-scale companies. AQR has positioned itself very favorably as it enters this space.”

Can AQR maintain its momentum?

Market volatility often boosts hedge funds and quant trading firms (and under Trump, volatility was abundant), but whether AQR can continue its turnaround depends on whether its models can keep outperforming the market and how many other hedge funds are actively adopting AI-driven quantitative strategies.

This article is translated from:

Author: John Hyatt

Translation: Björn & Elaine

Proofreading: Lemin

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