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Using Fundamental Analysis to Assess Earnings Quality: Evidence from the Center for Financial Research and Analysis

We document postevent negative abnormal returns to the (implicit) sell recommendations of a group of fundamental analysts. We also find statistically significant deterioration in the financial performance of the identified firms in the year after the recommendations. Together the results are consist...

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Bibliographic Details
Published in:Journal of Accounting, Auditing & Finance Auditing & Finance, 2001-10, Vol.16 (4), p.273-295
Main Authors: Fairfield, Patricia M., Whisenant, J. Scott
Format: Article
Language:English
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Summary:We document postevent negative abnormal returns to the (implicit) sell recommendations of a group of fundamental analysts. We also find statistically significant deterioration in the financial performance of the identified firms in the year after the recommendations. Together the results are consistent with the claim of fundamental analysts that they are able to identify firms that are successfully masking operational problems with aggressive accounting. The sample in this study comprises 373 firms identified over a four-year period by the Center for Financial Research and Analysis (CFRA). The CFRA offers to subscribers a monthly report identifying approximately 10 firms that CFRA claims are experiencing operational problems and particularly those that employ unusual or aggressive accounting practices to mask the problems. The CFRA analysts rely on traditional techniques of fundamental analysis, including mechanical screens and more time-consuming analyses of footnotes and other public disclosures. Their data sources include only publicly available information, primarily SEC filings. We conclude that CFRA's apparent success in identifying firms with deteriorating performance provides evidence about the usefulness of traditional financial statement analysis. The results also provide a strong rationale for future research to identify specific techniques of fundamental analysis that can be employed to detect operational problems masked by aggressive accounting practices.
ISSN:0148-558X
2160-4061
DOI:10.1177/0148558X0101600403