Original Research
Predicting financial distress using financial and non-financial variables
Francois Van Der Colff, Frans Vermaak
About the author(s)
Francois Van Der Colff, University of Pretoria, South Africa
Frans Vermaak, University of Pretoria, South Africa
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
Metrics
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Crossref Citations
1. K-score categorisation of JSE listed sectors under the financial distress continuum theory: A quantitative approach
Navitha Singh Sewpersadh, David McMillan
Cogent Economics & Finance vol: 8 issue: 1 first page: 1748969 year: 2020
doi: 10.1080/23322039.2020.1748969
2. Corporate Governance, Professional Education, and Employee Bonus in High-Tech Industry- Evidence from Taiwan
Lin Wen Hsiang
EURASIA Journal of Mathematics, Science and Technology Education vol: 13 issue: 9 year: 2017
doi: 10.12973/eurasia.2017.01065a