A new non-parametric classifier to predict small-business failures in Italy via performance ratios

Francesca Di Donato and Luciano Nieddu

International Journal of Information and Decision Sciences, 2018, vol. 10, issue 1, 57-76

Abstract: We considered the case of small-medium enterprises (SMEs) in Italy introducing a new classifier to predict bankruptcy up to eight years prior to failure. We considered a stratified random sample of 100 non-listed Italian SMEs, 50 of which filed for bankruptcy during the years 2000 to 2011. Results suggest that the proposed method more than holds its own when compared with standard non-parametric classification techniques. The performance of the proposed method based on recognition rate, sensitivity and specificity shows that the proposed technique is effective in predicting the failure of a firm up to eight years prior to the event. The high specificity makes the proposed technique very effective as a warning signal to determine if a firm is in distress with a sufficient enough time to take proper actions. The performance assessment has been achieved via cross-validation to get unbiased estimates of the performances.

Keywords: constrained k -means; bankruptcy prediction; discriminant analysis; performance ratios; small-medium enterprises; SMEs; Italy. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=90669 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:10:y:2018:i:1:p:57-76

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().