Are acquirer stock price reactions to M&A announcements in any way predictable? A machine-learning analysis
研究利用机器学习方法检验收购方股票价格对并购公告的反应是否可预测，发现非参数模型有一定预测能力，而参数模型则不能，且收购方规模和交易规模是关键预测因子。
We examine whether acquirer stock price reactions to M&A deal announcements can be forecasted based on ex ante acquirer, target, deal, and macroeconomic characteristics. We employ machine learning methodologies with out-of-sample testing and standard cross-validation procedures to assess the forecasting accuracy of various parametric and nonparametric models. While overall predictability is low, nonparametric models exhibit some ability to forecast acquirer stock price reactions to M&A announcements, whereas parametric models do not. Feature importance analyses reveal that a handful of predictors, including acquirer size and (relative) deal size, contribute most to the predictions. Our findings have practical implications for corporate managers and various corporate stakeholders.