The Impact of Terrorist Attacks on European Financial Markets

This thesis explores how European financial markets respond to the immediate shock of terrorist incidents by combining a traditional event study with predictive machine learning. Analyzing a final sample of 1,148 events from the Global Terrorism Database over the period 2010 to 2021, the baseline results point to a clear null average effect, showcasing a remarkable degree of aggregate market resilience across national indices. However, moving past these macromeasures, reveals distinct, descriptively visible sectoral and financial center patterns, with mobility-dependent industries like Travel & Leisure having the most of the negative impact. When testing whether these localized dynamics can be forecasted, both linear regressions and non-linear ensemble models suggest limited predictability, operating close to random guessing. Ultimately, these findings suggest that while terrorism risk triggers sharp structural reallocations between industries, its cumulative footprint is rapidly disappearing, and systematically predicting its impact remains challenging.