[{"publication_identifier":{"issn":["1437-8981"]},"publication_status":"published","year":"2025","page":"302-308","citation":{"chicago":"Sievers, Sönke, Reeyarn Li, Dominik Degen, Jens Kengelbach, and Francesca Pietrogrande. <i>Beer, Cars &#38; Fundamentals: Predicting German M&#38; A Activity</i>. Vol. Heft 11-12/2025. Corporate Finance, 2025. <a href=\"https://doi.org/CFCF1480783\">https://doi.org/CFCF1480783</a>.","ieee":"S. Sievers, R. Li, D. Degen, J. Kengelbach, and F. Pietrogrande, <i>Beer, Cars &#38; Fundamentals: Predicting German M&#38; A activity</i>, vol. Heft 11-12/2025. 2025, pp. 302–308.","bibtex":"@book{Sievers_Li_Degen_Kengelbach_Pietrogrande_2025, series={Corporate Finance}, title={Beer, Cars &#38; Fundamentals: Predicting German M&#38; A activity}, volume={Heft 11-12/2025}, DOI={<a href=\"https://doi.org/CFCF1480783\">CFCF1480783</a>}, author={Sievers, Sönke and Li, Reeyarn and Degen, Dominik and Kengelbach, Jens and Pietrogrande, Francesca}, year={2025}, pages={302–308}, collection={Corporate Finance} }","short":"S. Sievers, R. Li, D. Degen, J. Kengelbach, F. Pietrogrande, Beer, Cars &#38; Fundamentals: Predicting German M&#38; A Activity, 2025.","mla":"Sievers, Sönke, et al. <i>Beer, Cars &#38; Fundamentals: Predicting German M&#38; A Activity</i>. 2025, pp. 302–08, doi:<a href=\"https://doi.org/CFCF1480783\">CFCF1480783</a>.","ama":"Sievers S, Li R, Degen D, Kengelbach J, Pietrogrande F. <i>Beer, Cars &#38; Fundamentals: Predicting German M&#38; A Activity</i>. Vol Heft 11-12/2025.; 2025:302-308. doi:<a href=\"https://doi.org/CFCF1480783\">CFCF1480783</a>","apa":"Sievers, S., Li, R., Degen, D., Kengelbach, J., &#38; Pietrogrande, F. (2025). <i>Beer, Cars &#38; Fundamentals: Predicting German M&#38; A activity: Vol. Heft 11-12/2025</i> (pp. 302–308). <a href=\"https://doi.org/CFCF1480783\">https://doi.org/CFCF1480783</a>"},"date_updated":"2026-04-09T07:42:58Z","volume":"Heft 11-12/2025","author":[{"first_name":"Sönke","id":"46447","full_name":"Sievers, Sönke","last_name":"Sievers"},{"first_name":"Reeyarn","full_name":"Li, Reeyarn","id":"102450","last_name":"Li"},{"full_name":"Degen, Dominik","last_name":"Degen","first_name":"Dominik"},{"first_name":"Jens","last_name":"Kengelbach","full_name":"Kengelbach, Jens"},{"first_name":"Francesca","last_name":"Pietrogrande","full_name":"Pietrogrande, Francesca"}],"date_created":"2026-04-09T07:42:13Z","title":"Beer, Cars & Fundamentals: Predicting German M& A activity","doi":"CFCF1480783","type":"working_paper","abstract":[{"lang":"eng","text":"This paper introduces a predictive model for German mergers and acquisitions (M& A) activity leveraging deep feedforward neural networks (DFNN) incorporating well-established traditional variables (also known as features), along with a ChatGPT-based M& A sentiment score (MASS) and unconventional predictors such as beer sales and weather data. We demonstrate that the inclusion of sentiment and non-traditional variables enhances predictive performance. Our findings provide an important empirical foundation for understanding near-term fluctuations in German M& A activity and offer a forecasting tool relevant to both practitioners and researchers."}],"status":"public","_id":"65383","department":[{"_id":"275"}],"user_id":"115848","series_title":"Corporate Finance","language":[{"iso":"eng"}]}]