---
title: LLM-Based Semantic Surprises in FOMC Communication: Asset Prices and Financial-Market Stress
url: https://www.ml-quant.com/papers/ssrn/7519200/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7519200
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7519200
featured: 2026-09-25
citations: unknown
topic: LLMs & Text
---


# LLM-Based Semantic Surprises in FOMC Communication: Asset Prices and Financial-Market Stress

Semantic surprises extracted from Federal Reserve statements predict subsequent financial-stress dynamics and reduce forecast error by up to 23%, particularly when initial stress is high or during recessions.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7519200
- Identifier: SSRN 7519200
- Released: 2026-09-24
- First featured: Quant Letter No. 132 (2026-09-25): https://www.ml-quant.com/issues/2026-09-25/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text
- Authors: Fengtian Yang, Manjiang Xing, Chenrui Zhang

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