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dc.contributor.supervisor Nelson, Toni Kwasitsu, Deliah Leonie University of Lethbridge. Faculty of Management 2008-02-28T21:50:17Z 2008-02-28T21:50:17Z 2004
dc.description xi, 73 leaves ; 29 cm. en
dc.description.abstract The current study is designed to develop a model to improve investors’ ability to identify firms that engage in financial statement misrepresentation by carefully analyzing published financial reports. Earnings management literature indicates that financial statement information is not fully utilized by investors and that fundamental analysis provides useful information about a firm’s financial performance. The study examines accruals and the components that firms commonly use to violate GAAP in order to develop a probit regression model as an early detector of financial misrepresentation. The analysis consists of a matched-paired sample of 30 U.S. fraud firms and 30 non-fraud firms extracted from the GAO and Compustat databases. The results show that an investor who is comparing two firms from the same industry may use the lower Z score of the model and improve the chances of avoiding a fraud firm by at least 23%. en
dc.language.iso en_US en
dc.publisher Lethbridge, Alta. : University of Lethbridge, Faculty of Management, 2004 en
dc.relation.ispartofseries Project (University of Lethbridge. Faculty of Management) en
dc.subject Misleading financial statements en
dc.subject Financial statements en
dc.subject Accounting fraud en
dc.subject Stockholders en
dc.title Financial statement misrepresentation : could investors detect it? en
dc.type Technical Report en
dc.publisher.faculty Management en

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