---
title: Identifying M&A Targets from Textual Disclosures
url: https://www.ml-quant.com/papers/ssrn/4707567/
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 4707567
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4707567
featured: 2024-01-30
citations: unknown
topic: LLMs & Text
---


# Identifying M&A Targets from Textual Disclosures

Textual information from firm disclosures, analyzed using a transformer neural network, can significantly enhance the predictability of corporate takeovers, a study reveals.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4707567
- Identifier: SSRN 4707567
- Released: 2023-03-04
- First featured: Quant Letter No. 35 (2024-01-30): https://www.ml-quant.com/issues/2024-01-30/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

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