Faculty of Management Projects (Master's)

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Financial statement misrepresentation : could investors detect it?
(Lethbridge, Alta. : University of Lethbridge, Faculty of Management, 2004, 2004) Kwasitsu, Deliah Leonie; University of Lethbridge. Faculty of Management; Nelson, Toni
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%.