The effect of sentiment on cross-border M&A performance
Purpose This research examines how sentiment influences the performance of mergers and acquisitions (M&As), with a focus on cross-border deals. Design/methodology/approach This study employs a quantitative analysis of US public acquirers engaging in domestic and cross-border mergers and acquisitions between 2019 and 2023. It integrates sentiment measures from Twitter and macro-level political risk indicators into regression models to assess their impact on short-term deal performance. By comparing domestic and cross-border contexts, the study bridges behavioral finance with institutional theory, controlling for deal characteristics and firm-specific factors. Findings The analysis reveals that positive sentiment significantly enhances domestic M&A outcomes, while its effect is weaker in cross-border transactions due to heightened uncertainty and complexity. Twitter-derived sentiment proves to be a reliable predictor of deal performance in both contexts. Political risk is found to dampen cross-border deal success, highlighting the importance of policy stability in international transactions. These findings demonstrate that sentiment and institutional context jointly influence M&A results, offering practical implications for firms engaging in global expansion. Originality/value This study uniquely combines behavioral and institutional frameworks to examine how sentiment and political risk jointly influence M&A performance, with a focus on differences between domestic and cross-border deals. By leveraging real-time Twitter sentiment and recent political risk data from 2019 to 2023, it provides fresh insights into the nuanced role of public mood and policy uncertainty in shaping deal outcomes. The findings offer actionable guidance for corporate managers and investors, especially those involved in international M&A, by highlighting the importance of monitoring sentiment dynamics and geopolitical conditions in strategic decision-making.
Authors
- Feng Dong (ORCID: https://orcid.org/0000-0002-3068-3100)
- Niklas Weigand
Institutions
- Elon University (US)
Publication Details
- Journal
- Review of Behavioral Finance
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1108/rbf-04-2025-0166
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00