IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Article provided by AccessEcon in its journal Economics Bulletin.

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

in new window

Handle: RePEc:ebl:ecbull:eb-13-00129
Contact details of provider:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

in new window

  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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-13-00129. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (John P. Conley)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.