Event Study Methodology

An abnormal return is the firm's actual return on a single day minus the return predicted by its normal-return benchmark, so it captures the event-related surprise on that day. A cumulative abnormal return (CAR) sums those daily abnormal returns over the event window to give the total value effect of the event for that firm. MacKinlay treats aggregation over the window as essential because the market's reaction often spans several days through anticipation and delayed adjustment; averaging CARs across firms then yields the typical response to a class of events and is the quantity most strategy studies report and test.

Raw returns mix the event's effect with market-wide movements that have nothing to do with the firm's decision. The market model regresses the firm's return on a market index over a clean estimation window, learning how the stock normally co-moves with the market, and then subtracts that expected co-movement from the event-window return. MacKinlay notes this removes a major source of variance and so increases the power to detect the event's true effect relative to the constant-mean or market-adjusted alternatives. The abnormal return that remains is the part of the return attributable to firm-specific, event-related news.

When many sample firms experience the event on or near the same calendar date -- common for regulatory or macro shocks -- their abnormal returns are correlated through shared market conditions. Brown and Warner showed that standard tests assuming cross-sectional independence then understate the true standard error, so the test statistic is too large and CARs look significant when they are not. The remedy is to use standardized cross-sectional statistics, portfolio or calendar-time approaches, or nonparametric tests that account for the dependence, rather than treating clustered events as independent observations.