Event studies play a central role in class action securities fraud litigation. Event studies are used to assess market efficiency, price impact, loss causation, and damages, all of which are essential elements of a securities fraud claim. However, a substantial increase in market-wide volatility, such as what happened in 2020 with the Covid-19 pandemic, can render the standard event study methodology unreliable. In these periods, the usual distributional assumptions for t-tests of significance produce too many false positives. In this paper, we examine the extent of the problem and propose a solution that employs the empirical distribution of the t-statistic during the Covid period to adjust the critical test statistic value. We demonstrate this methodology with an application using the 19 constituents of the consumer durables index S5CODU in PreCovid and Covid period samples, and with an evaluation of earnings announcement effects on stock prices. We show the methodology restores correct test size, eliminating excess spurious significance, while preserving substantial test power to correctly identify significant events in the Covid period.

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