Financial Stability Implications of Generative AI: Taming the Animal Spirits

Seung Jung Lee and Anne Lundgaard Hansen
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Anne Lundgaard Hansen: https://www.richmondfed.org/banking/qsr/hansen

No 2025-090, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: This paper investigates the impact of the adoption of generative AI on financial stability. We conduct laboratory-style experiments using large language models to replicate classic studies on herd behavior in investment decisions. Our results show that AI agents make more rational decisions than humans, relying predominantly on private information over market trends. Increased reliance on AI-powered investment advice could therefore potentially lead to fewer asset price bubbles arising from animal spirits that trade by following the herd. However, exploring variations in the experimental settings reveals that AI agents can be induced to herd optimally when explicitly guided to make profit-maximizing decisions. While optimal herding improves market discipline, this behavior still carries potential implications for financial stability. In other experimental variations, we show that AI agents are not purely algorithmic, but have inherited some elements of human conditioning and bias.

Keywords: Herd behavior; Large language models; AI-powered traders; Financial markets; Financial stability (search for similar items in EconPapers)
JEL-codes: C90 D82 G11 G14 G40 (search for similar items in EconPapers)
Pages: 71 p.
Date: 2025-09-26
New Economics Papers: this item is included in nep-ain and nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2025-90

DOI: 10.17016/FEDS.2025.090

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