No. 150: Large Language Models and M&A: Can ChatGPT help forecast M&A activity?

This paper employs ChatGPT on firms’ earnings conference calls transcripts to extract managers’ so far private information regarding their sentiment and expectations concerning (future) mergers and acquisitions (M&A) activity. We aggregate these firm-level scores to a market wide ChatGPTbased M&A sentiment score (MASS) and successfully perform various construct validity checks including employing M&A experts and back testing. Our main results suggest that M&A sentiment has strong forecasting power for future M&A activity and adds additional explanatory power to established sentiment indices and fundamental drivers. The predictability holds for both in-sample and out-of-sample tests. Overall, our novel index will be useful to further understand M&A patterns, to predict future M&A activity, and for practitioners to evaluate and benchmark their own M&A activities.