AI-Driven M&A Forecasting: Singular Spectrum Analysis Model in the EDA Industry

Mergers and acquisitions (M&A) in the Electronic Design Automation (EDA) industry are mainly motivated by technological change and economic reasons. Accurate forecasting of M&A activities is very important for the stakeholders who are seeking to understand the dynamics of the competition. This paper proposes a robust AI-driven forecasting model based on Singular Spectrum Analysis (SSA) to track and forecast the trends of M&A activities in the EDA industry. The methodology breaks up historical data into its elements, then constructs them again and predicts the future market consolidation activities with high accuracy. Furthermore, this study incorporates disruptive technological milestones into the SSA forecasting model to improve the SSA application for technology-intensive markets.