Original Research
Predicting financial distress using financial and non-financial variables
Journal of Economic and Financial Sciences | Vol 8, No 1 | a93 |
DOI: https://doi.org/10.4102/jef.v8i1.93
| © 2015 Francois Van Der Colff, Frans Vermaak
| This work is licensed under CC Attribution 4.0
Submitted: 21 December 2017 | Published: 30 April 2015
Submitted: 21 December 2017 | Published: 30 April 2015
About the author(s)
Francois Van Der Colff, University of Pretoria, South AfricaFrans Vermaak, University of Pretoria, South Africa
Full Text:
PDF (280KB)Abstract
This study attempts to clarify whether using a hybrid model based on non-financial variables and financial variables is able to provide a more accurate company financial distress prediction model than using a model based on financial variables only. The relationship between the model test results and the De la Rey K-Score for the subject companies is tested, employing Cramer’s V statistical test. A movement towards a Cramer’s V value of one indicates a strengthening relationship, and a movement towards zero is an indication of a weakening relationship. Against this background, further empirical research is proposed to prove that a model combining financial variables with true non-financial variables provides a more accurate company distress prediction than a financial variable-only model. The limited evidence of a strengthening relationship found is insufficient to establish the superiority of the proposed model beyond reasonable doubt.
Keywords
financial distress prediction; non-financial variables; financial distress continuum; neural networks
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