Scalable Data-Driven Framework for Identifying Companies Susceptible to Activist Investor Targeting Using Advanced Analytics and Cloud

Abstract

Activist investors target companies perceived to have untapped value or mismanaged resources, compelling firms to improve governance and performance.Identifying such companies is complex, often relying on fragmented data and manual analysis. This research introduces a comprehensive, cloud-enabled framework to predict company vulnerabilities using advanced analytics. By leveraging Capital IQ (CapIQ) for data, AWS for scalable processing, and Power BI for visualization, the framework employs machine learning models (e.g., Gradient Boosting, Logistic Regression) and Natural Language Processing (NLP) for prediction. Results reveal significant improvements in accuracy and scalability over traditional approaches, demonstrated via case studies and operational analysis. The paper highlights the framework's contribution and proposes future enhancements to integrate social media data and improve interpretability.