2025/12/05 by T. Ramalingeswara Rao, Hou, Yuhan, Rao, Tianji +13
Computer Science · Decision Sciences · Social Sciences · #Artificial Intelligence (cs.AI) #Computational and Text Analysis Methods #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Economics and business #General Finance (q-fin.GN) #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2512.15728
openalex publication_date 2025/12/05 · openalex created_date 2025/12/21 · openalex updated_date 2026/07/28
The Federal Open Market Committee (FOMC) sets the federal funds rate, shaping monetary policy and the broader economy. We introduce FedSight AI, a multi-agent framework that uses large language models (LLMs) to simulate FOMC deliberations and predict policy outcomes. Member agents analyze structured indicators and unstructured inputs such as the Beige Book, debate options, and vote, replicating committee reasoning. A Chain-of-Draft (CoD) extension further improves efficiency and accuracy by enforcing concise multistage reasoning. Evaluated at 2023-2024 meetings, FedSight CoD achieved accuracy of 93.75% and stability of 93.33%, outperforming baselines including MiniFed and Ordinal Random Forest (RF), while offering transparent reasoning aligned with real FOMC communications.