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Paraconsistent and fuzzy logic applied to company profitability analysis

Listed author(s):
  • Rodrigo P. Dill

    ()

    (Federal University of South Frontier (UFFS))

  • Newton Da Costa Jr.

    ()

    (Federal University of Santa Catarina (UFSC))

  • André A. P. Santos

    ()

    (Federal University of Santa Catarina (UFSC))

This study proposes an application of two models based on non-classical logic, the paraconsistent logic and the fuzzy logic, in company profitability analysis. We conduct interviews with market specialists in order to identify the main explanatory variables related to company profitability and apply the paraconsistent model in order to classify the data and to attribute a degree of favorable evidence and of contrary evidence to each profitability ratio. In the fuzzy model, the collected data is analyzed and classified using inference rules and membership functions, thus assigning a qualitative variable to each profitability index. The empirical implementation indicates that both models can be used as tools for assistance and validation of opinions of specialists in the analysis of a company's profitability.

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File URL: http://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I2-P127.pdf
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Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 33 (2013)
Issue (Month): 2 ()
Pages: 1348-1360

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Handle: RePEc:ebl:ecbull:eb-13-00129
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  1. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, 09.
  2. Syau, Yu-Ru & Hsieh, Hai-Teh & Lee, E Stanley, 2001. "Fuzzy Numbers in the Credit Rating of Enterprise Financial Condition," Review of Quantitative Finance and Accounting, Springer, vol. 17(4), pages 351-360, December.
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