Chris Pulman

Global Merger-Arbitrage Forecasting with Language Models

Prior work on judgmental forecasting with large language models (LLMs) has focused on broad, mixed‑topic question banks and shallow context (e.g., short news snippets). We study a specialized, high‑stakes financial setting: forecasting M\&A outcomes for merger arbitrage. Using rich textual evidence,…