Identifying and Treating Outliers in Finance

Vincenzo Verardi, John Adams, Darren Hayunga, Sattar Mansi, David Reeb

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Résumé

Outliers represent a fundamental challenge in the empirical finance research. We investigate whether the routine techniques used in finance research to identify and treat outliers are appropriate for the data structures we observe in practice. Specifically, we propose a multivariate identification strategy that can effectively detect outliers. We also introduce an estimator that minimizes the bias outliers caused in both cross-sectional and panel regressions and provide outlier mitigation guidance. Using replications of four recently published studies in premier finance journals, we show how adjusting for multivariate outliers can lead to significantly different results.

langue originaleAnglais
Pages (de - à)345-384
Nombre de pages40
journalFinancial Management
Volume48
Numéro de publication2
Les DOIs
Etat de la publicationPublié - 1 juin 2019

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