This work develops a predictive model to identify potential targets of activist investment funds, which strategically acquire significant corporate stakes to drive operational and strategic improvements and enhance shareholder value. Predicting these targets is crucial for companies to mitigate intervention risks, for activists to select optimal targets, and for investors to capitalize on associated stock price gains. Our analysis utilizes data from the Russell 3000 index from 2016 to 2022. We tested 123 variations of models using different data imputation, oversampling, and machine learning methods, achieving a top AUC-ROC of 0.782. This demonstrates the model's effectiveness in identifying likely targets of activist funds. We applied the Shapley value method to determine the most influential factors in a company's susceptibility to activist investment. This interpretative approach provides clear insights into the driving forces behind activist targeting. Our model offers stakeholders a strategic tool for proactive corporate governance and investment strategy, enhancing understanding of the dynamics of activist investing.

翻译：本研究开发了一个预测模型，用于识别维权投资基金可能的目标——这些基金通过战略性获取公司大额股权，推动运营与战略改进以提升股东价值。预测此类目标对于企业降低干预风险、维权基金选择最优目标以及投资者获取相关股价上涨收益均至关重要。我们的分析采用2016年至2022年罗素3000指数数据，通过数据插补、过采样和机器学习方法测试了123种模型变体，最终获得0.782的最高AUC-ROC值，验证了模型识别维权基金潜在目标的有效性。我们运用沙普利值法确定了影响公司易受维权投资影响的核心因素，这种可解释性方法清晰揭示了维权目标选择背后的驱动机制。本模型为利益相关者提供了企业主动治理与投资策略的战略工具，深化了对维权投资动态机制的理解。