Abstract
The global advertising industry is undergoing structural transformation amid rapid digital disruption and economic uncertainty. This study examines the impact of technological disruption including the adoption of artificial intelligence (AI), big data, and automated advertising systems and digital economy indicators on the stock volatility of three multinational advertising companies: WPP plc (UK), Omnicom Group Inc. (US), and Dentsu Group Inc. (Japan). Using monthly data from 2008 up to 2024, the research employs a hybrid econometric approach integrating the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to capture short-term volatility dynamics and the Vector Error Correction Model (VECM) to assess long-term equilibrium relationships among variables. Analyzed variables include technology indices (NASDAQ-100, FTSE Techmark, Nikkei-225), inflation (CPI), digital advertising expenditure, and revenue. The integrated GARCH-VECM model is evaluated against individual GARCH and VECM models using performance metrics such as MAE, RMSE, MAPE, confidence intervals, and cross-validation tests. Results show that technological disruption significantly increases stock volatility across all firms, while inflation effects vary depending on the country context. Sector-specific indicators, including digital advertising spending and revenue, exhibit limited short-term influence. Long-run cointegration is confirmed, particularly for WPP and Omnicom, indicating structural sensitivity to global digital transformation. The integrated GARCH-VECM model demonstrates superior predictive accuracy, stability, and robustness compared to single models. This study contributes novel empirical evidence and practical insights for effective risk management in the highly digitized and volatile advertising sector, benefiting policymakers, investors, and corporate strategists.