This open access book offers a clear, research oriented guide to event study methodology across corporate finance, asset pricing, and financial econometrics. Covering the full empirical workflow, from event identification and window design to models for expected returns and statistical inference, the book situates abnormal returns and cumulative abnormal returns within market, multifactor, and buy and hold frameworks. It reviews classical and non parametric tests; examines specification and power through simulation; and treats empirical challenges such as cross sectional dependence, volatility dynamics, and estimation window contamination via portfolio, regression, ARCH/GARCH, and Markov switching approaches. Cross sectional regressions, selection issues, and the interface with modern causal inference - including difference in differences and synthetic DiD - are developed with applications to mergers and acquisitions, regulatory changes, and technological shocks.
The volume also contains insights for litigation and policy by explaining how event studies are deployed in securities fraud, antitrust, and regulatory contexts, including class certification standards and damages analysis.