Can AI Boost Market Returns?

AI presents both opportunities and challenges for boosting market returns, particularly in asset management. While AI can enhance efficiency and unlock alternative data insights, its use in generating unique investment advantages remains uncertain due to technical limitations.

 

Copyright: investmentexecutive.com – “Can AI Boost Market Returns?”

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Artificial intelligence (AI) evangelists promise a revolution for the economy. However, deploying AI to gain an edge in financial markets and generate excess investment returns is increasingly in doubt.

A paper published by the International Monetary Fund in November 2023 said financial sector spending on AI is projected to more than double to US$97 billion by 2027, rising at a 29% compound annual growth rate.

And recent research from Statistics Canada singled out financial sector professionals as the cohort most exposed to AI disruption, alongside computer programmers and IT professionals.

“A broader segment of the labour force could be affected in an era when sophisticated large language models such as ChatGPT increasingly excel at performing non-routine and cognitive tasks typically done by highly skilled workers,” StatCan’s paper said.

Even as the financial sector appears ripe for AI disruption, the feasibility of companies replacing human workers with AI-powered technology is unclear. StatCan noted there are legal, financial and institutional barriers to replacing educated professionals with tech.

Further, the promised payoff from AI for financial firms will probably be limited.

In a report, analysts with Moody’s Investors Service Inc. point out that “harnessing AI is fraught with technical and organizational challenges.”

While the technology can automate routine tasks and enable portfolio managers to process data — and potentially glean novel investment insights — practical constraints mean AI deployment is unlikely to drive vastly improved investment performance.

According to the Moody’s report, generative AI tools aren’t particularly useful for uncovering investment signals.

“Using large language models to identify investment opportunities is tempting, but this approach faces several problems,” Moody’s said.[…]

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