Abstract
Using a multi-objective linear programming, we develop an approach to set the decision power for the multiple fuzzy rules, properly in a highly fuzziness event and earnings manipulation, whose degree of membership is difficult to observe. We use the proposed method to detect the uncovered earnings manipulators during the period 2001–2010 from the companies listed at Shanghai Stock Exchange and Shenzhen Stock Exchange. The recognition rate for in-sample test is 78.4 %, and the corresponding rate for out-of-sample test is 76.9 %.
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Li, S., Liang, H. (2014). Detection of Earnings Manipulation with Multiple Fuzzy Rules. In: Sun, F., Li, T., Li, H. (eds) Foundations and Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37829-4_32
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DOI: https://doi.org/10.1007/978-3-642-37829-4_32
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