This paper introduces a structural model to analyze how AI trading agents' similar information processing can destabilize financial markets. The research distinguishes between agents having similar internal representations of market states and producing similar predictions, showing that the former can lead to synchronized beliefs and actions. The findings suggest that increased representation homogeneity among AI agents can amplify volatility, liquidity stress, and tail risk, potentially leading to market collapses. AI
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IMPACT Highlights potential systemic risks in financial markets due to AI homogeneity, suggesting a need for macroprudential policies focused on AI information processing diversity.
RANK_REASON This is a research paper published on arXiv concerning AI's impact on financial markets.