---
title: Large Language Models and Information Frictions in Corporate Bonds
url: https://www.ml-quant.com/papers/ssrn/7577906/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-09
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7577906
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7577906
featured: 2026-10-09
citations: unknown
topic: LLMs & Text
---


# Large Language Models and Information Frictions in Corporate Bonds

Shows that large-language-model scores of default risk from earnings calls predict bond rating migration one year ahead where analysts disagreed, capturing information not yet priced in spreads.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7577906
- Identifier: SSRN 7577906
- Released: 2026-10-07
- First featured: Quant Letter No. 134 (2026-10-09): https://www.ml-quant.com/issues/2026-10-09/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text
- Authors: Moazzam Khoja

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