Much has been heard about the potential of artificial intelligence (AI) to transform economies and societies. But there are growing doubts about whether the reality will match the hype, not least in the world of hedge-fund management.
Has artificial intelligence’s impact on hedge funds been overhyped?
Hedge funds and family offices have invested heavily in AI to boost portfolio management and operational efficiency. Around 86% of hedge-fund managers, for example, grant their staff access to various generative AI tools to bolster their work, “representing a widespread embrace of this transformative technology”, according to the Alternative Investment Management Association (AIMA).1 The organisation adds that generative AI tools “are demonstrating their versatility within hedge funds to enhance marketing materials, carry out general research tasks, and support their coding endeavours”.
AI also has the potential to optimise portfolio management, according to a number of analysts. That’s because AI assists in selecting the best combination of assets and strategies to align with investment objectives while efficiently managing risk, says Arootah, which describes itself as an alt investment advisory service. It cites the example of BlackRock, which deploys an AI technology known as Aladdin Portfolio Guard to optimise hedge-fund portfolios, using it to evaluate correlations, risks and returns across current holdings. Aladdin analyses billions of potential portfolio combinations to construct an ideal composition aligned with market regimes.2
AI developed as a significant investment theme in 2023 and 2024, with many analysts predicting that its impact on economies and societies could prove transformative. The tripling in the share price of the leading AI-chip supplier Nvidia in 2023 was emblematic of the surge in investor interest in the theme.
Investors turn sceptical
However, doubts are growing about whether AI really will have a transformative impact – not just on hedge-fund management but on the wider economy and society. Bloomberg reported in June 2024, for example, that Wall Street investors are growing impatient to see clear payoffs from Big Tech’s heavy spending on AI hardware, development and talent. A series of once-high-flying AI startups have either implemented layoffs or are the subject of takeover speculation that could herald a wave of consolidation.3
In July, Goldman Sachs issued a report arguing that the reality may not match the hype. The asset manager said that “tech giants and beyond are set to spend over $1tn on AI capex in coming years, with so far little to show for it”. Goldman’s Jim Covello, head of global equity research, asked “What trillion-dollar problem will Al solve?” and noted that “replacing low-wage jobs with tremendously costly technology is basically the polar opposite of the prior technology transitions I’ve witnessed in my thirty years of closely following the tech industry”. Covello also questioned whether models trained on historical data would ever be able to replicate humans’ most valuable capabilities.4
Heavy costs weigh on performance
The real-world performance of hedge funds that use AI is also concerning. Consider the performance of the Eurekahedge AI Hedge Fund Index, which “is designed to provide a broad measure of the performance of underlying hedge fund managers who utilize artificial intelligence and machine learning theory in their trading processes”, according to its creator. From December 2009 to July 2024, the index produced a 9.8% annualised return, versus 13.7% for the S&P 500.
Figure 1: Hedge fund using AI underperforms S&P 500 index
That underperformance shouldn’t surprise. Active funds in general are likely to underperform an index, given the burden of management fees and transaction costs. Add in the huge cost of investing in and deploying AI, and managers are at a significant disadvantage to trackers.
Moreover, Lawrence Tint, who was involved in the creation of iShares (now part of BlackRock), adds that even assuming that some AI managers will be able to beat the market, their job will become progressively harder as more and more active managers use the same technology, and there will be fewer managers on the other side of the trade who don’t also use AI. The inevitable conclusion is that eventually AI’s likelihood of beating the market may largely disappear.5
Learning lessons?
But what is particularly concerning for those who argue that AI is able to learn from its mistakes and thus constantly improve is that the Eurekahedge AI Hedge Fund Index recorded better relative performance in the first half of the sample than the second.6
Regulatory doubts
There are also concerns about the deployment of AI from a regulatory perspective. A report from the US Department of Homeland Security & Governmental Affairs, released in June 2024, for example, found that use of AI by hedge funds poses unique risks and amplifies traditional risks. It expressed concern that bad actors could “intentionally target the AI systems used by hedge funds, and other investment vehicles, and create market instability”. Furthermore, the report warned that the use of AI could amplify the risk of market manipulation through its speed and ability “to unfairly distort information and prices relating to financial instruments or transactions”.
AI increases the risk of herding behaviour, whereby a large number of investors act in a similar manner, according to the report. Moreover, AI’s risk of lack of explainability enhances the traditional risk of inadequate disclosures to clients. The report explains: “If an investment advisor is unable to fully explain the AI systems it uses, it calls into question whether clients can understand the systems’ decision sufficiently to assess whether they consent to the investment advisor’s work.”7
Overall, therefore, while AI undoubtedly has huge potential across a range of hedge-fund operations, from generating marketing content to swiftly analysing billions of data points and thereby assisting in portfolio construction, there do appear to be growing doubts about whether the costs involved will be justified. And then, of course, there are also those regulatory issues.
Sources
1 https://www.aima.org/article/press-release-getting-in-pole-position-how-hedge-funds-are-leveraging-gen-ai-to-get-ahead.html
2 https://arootah.com/blog/hedge-fund-and-family-office/risk-management/how-ai-is-changing-hedge-funds/
3 https://www.bloomberg.com/news/newsletters/2024-08-08/tech-founders-and-investors-confront-a-wave-of-ai-skepticism
4 https://www.goldmansachs.com/images/migrated/insights/pages/gs-research/gen-ai--too-much-spend%2C-too-little-benefit-/TOM_AI%202.0_ForRedaction.pdf
5 https://www.marketwatch.com/story/some-hedge-funds-thought-ai-would-help-them-beat-the-market-then-things-got-real-e3aae97f
6 https://www.marketwatch.com/story/some-hedge-funds-thought-ai-would-help-them-beat-the-market-then-things-got-real-e3aae97f
7 https://media.regcompliancewatch.com/uploads/2024/06/2024.06.11-Hedge-Fund-Use-of-AI-Report.pdf
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