Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Faycal Mraihi
In this study, we try to develop a model for predicting corporate default based on a logistic regression (logit) and applied to the case of Tunisia. Our sample consists of 212 companies in the various industries (106 companies ‘healthy’ and 106 companies “distressed”) over the period 2005-2010. The results of the use of a battery of 87 ratios showed that 12 ratios can build the model and that liquidity and solvency have more weight than profitability and management in predicting the distress. Both on the original sample and the control one, these results are good either in terms of correct percentage of classification or in terms of stability of discriminating power over time (on, two and three years before the distress) and space.
Faycal Mraihi. 2015. \u201cDistressed Company Prediction using Logistic Regression: Tunisians Case\u201d. Global Journal of Management and Business Research - C: Finance GJMBR-C Volume 15 (GJMBR Volume 15 Issue C3): .
Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
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Total Score: 101
Country: Tunisia
Subject: Global Journal of Management and Business Research - C: Finance
Authors: Faycal Mraihi (PhD/Dr. count: 0)
View Count (all-time): 163
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Publish Date: 2015 04, Wed
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Neural Networks and Rules-based Systems used to Find Rational and
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In this study, we try to develop a model for predicting corporate default based on a logistic regression (logit) and applied to the case of Tunisia. Our sample consists of 212 companies in the various industries (106 companies ‘healthy’ and 106 companies “distressed”) over the period 2005-2010. The results of the use of a battery of 87 ratios showed that 12 ratios can build the model and that liquidity and solvency have more weight than profitability and management in predicting the distress. Both on the original sample and the control one, these results are good either in terms of correct percentage of classification or in terms of stability of discriminating power over time (on, two and three years before the distress) and space.
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