Predicting Material Accounting Misstatements *

Predicting Material Accounting Misstatements * 1. Introduction What causes managers to misstate their financial statements? How best can investors, auditors, financial analysts, and regulators detect misstatements? Addressing these questions is of critical importance to the efficient functioning of capital markets. For an investor it can lead to improved returns, for an auditor it can mean avoiding costly litigation, for an analyst it can mean avoiding a damaged reputation, and for a regulator it can lead to enhanced investor protection and fewer investment debacles. Our research has two objectives. First, we develop a comprehensive database of financial misstatements. Our objective is to describe this database and make it broadly available to other researchers to promote research on earnings misstatements. Second, we analyze the financial characteristics of misstating firms and develop a model to predict misstatements. The output of this analysis is a scaled probability ( F ‐score) that can be used as a red flag or signal of the likelihood of earnings management or misstatement. We compile our database through a detailed examination of firms that have been subject to enforcement actions by the U.S. Securities and Exchange Commission (SEC) for allegedly misstating their financial statements. Since 1982, the SEC has issued Accounting and http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Accounting Research Wiley

Predicting Material Accounting Misstatements *

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Publisher
Wiley
Copyright
© 2011 The Canadian Academic Accounting Association
ISSN
0823-9150
eISSN
1911-3846
D.O.I.
10.1111/j.1911-3846.2010.01041.x
Publisher site
See Article on Publisher Site

Abstract

1. Introduction What causes managers to misstate their financial statements? How best can investors, auditors, financial analysts, and regulators detect misstatements? Addressing these questions is of critical importance to the efficient functioning of capital markets. For an investor it can lead to improved returns, for an auditor it can mean avoiding costly litigation, for an analyst it can mean avoiding a damaged reputation, and for a regulator it can lead to enhanced investor protection and fewer investment debacles. Our research has two objectives. First, we develop a comprehensive database of financial misstatements. Our objective is to describe this database and make it broadly available to other researchers to promote research on earnings misstatements. Second, we analyze the financial characteristics of misstating firms and develop a model to predict misstatements. The output of this analysis is a scaled probability ( F ‐score) that can be used as a red flag or signal of the likelihood of earnings management or misstatement. We compile our database through a detailed examination of firms that have been subject to enforcement actions by the U.S. Securities and Exchange Commission (SEC) for allegedly misstating their financial statements. Since 1982, the SEC has issued Accounting and

Journal

Contemporary Accounting ResearchWiley

Published: Mar 1, 2011

References

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