Sector index selection in securities litigation event studies: R-squared and model stability

Revision requested, Journal of Legal Economics

An event study regression estimates the return a stock would have generated in the absence of company-specific news. The sector index in the regression model can affect the predicted return and thus the measured abnormal return and statistical significance. In a securities litigation context, the sector choice can thus affect determinations of market efficiency, price impact, loss causation, and damages. We examine one narrow selection rule: choosing from a set of candidate sector indices the model with the highest in-sample R-squared, a measure of fit. We compare that choice with the sector designation made by S&P Dow Jones Indices, which serves as an external benchmark (though not a uniquely “correct” event-study control).

For 30 Dow Jones Industrial Average firms, the R-squared-maximizing index differs from the S&P Dow Jones-designated index for 15 firms in 2023 and 18 firms in 2024. Restricting the comparisons to each firm’s designated index and just one predetermined, plausible alternate reduces disagreement, and the same candidate has higher R-squared in both years for 25 of 30 firms. By contrast, when the candidate set comprises all ten sector indices, the index with the highest R-squared changes between years for 18 firms, and is unstable across repeated random holdout periods. These results show that, while R-squared can be an informative metric, it should not be relied upon exclusively. A defensible process should emphasize economic reasoning. When fit is considered, the candidate set should be limited and disclosed, mechanical own-stock contamination should be removed, and the fit should be evaluated out-of-sample and for stability.

Revision requested, Journal of Legal Economics.
Feinstein, S.P., Stein, L.C.D., Villanueva, O.M., 2026. Sector index selection in securities litigation event studies: R-squared and model stability (Working Paper No. 7228058). SSRN.
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