Crystal Kim
2 min read
“Hey AI, maximize my portfolio returns,” is a prompt that has moved from speculative fiction to Wall Street.
Last week, BlackRock, the world’s largest asset manager, unveiled an AI research platform called “Asimov” at the company’s investor day in New York. Chief Operating Officer Rob Goldstein described the research platform as a “virtual investment analyst” that can scan text in research notes, regulatory filings and emails to produce “portfolio insights.”
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BlackRock isn’t the first, nor will it be the last, asset manager to pick up AI tools as Wall Street firms jockey for a competitive edge.
Systematic hedge fund manager Man Group AHL, which has been using machine learning techniques for over a decade, described how the firm was using it to be more productive in a July 2024 report.
Man AHL was developing chatbots that could understand the firm’s internally developed code. It involved testing processes in which ChatGPT scans the intricate 200-page offering circulars of catastrophe bonds and inputs relevant information in a template that another person would check. ChatGPT could also answer investor queries, extracting relevant information from company documents including fact sheets, presentations, and investment commentaries. AI might also analyze macroeconomic data at the level of a junior quantitative analyst.
Others have deployed AI for portfolio construction:
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Bridgewater Associates CEO Nir Bar Dea stated at a Bloomberg Invest conference earlier this year that a fund launched in 2024, which utilizes machine learning to make decisions, delivered performance comparable to its human-led counterparts.
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Researchers at Stanford Graduate School of Business built an AI analyst that bested humans, beating 93% of human fund managers over 30 years by an average of 600%. The bot was fed portfolio data from about 3,300 actively managed US stock mutual funds between 1990 and 2020 and nosed out alpha by tweaking fund holdings once every quarter.
*AI Alpha: The academic exercise showed that, in hindsight, publicly available information wasn’t fully exploited. Though Stanford’s AI analyst was able to shoot the lights out in hindsight, it wouldn’t necessarily outperform in today’s market. And here’s the rub: “If every investor were using this tool, then much of the advantage would go away,” Suzie Noh, assistant professor of accounting, said in an interview with the university.
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