Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/13834
Title: Insolvency prediction for assessing corporate financial health
Authors: Simić, Dragan 
Kovačević, Ivana 
Simić S.
Issue Date: 1-Jun-2012
Journal: Logic Journal of the IGPL
Abstract: The prediction of corporate financial failure, crucial for the prevention and mitigation of economic downturns in a national economy, requires the categorization of healthy and unhealthy companies. This study examines the case of Serbia and applies multivariant statistical methods and specific artificial neural network architectures-the self-organizing map (SOM)-to assess the corporate financial health of various companies. Financial ratios drawn from corporate balance sheets become the independent variables in a multivariate discriminant analysis (MDA). These financial ratios and the discriminant Z-score in the MDA form the input for the SOM, which creates a hybrid MDA-SOM model that is capable of predicting corporate financial insolvency. The experimental results of this research correctly estimate company financial health in 95% of cases. These are reliable predictions that are comparable with similar studies in other countries. © The Author 2011. Published by Oxford University Press. All rights reserved.
URI: https://open.uns.ac.rs/handle/123456789/13834
ISSN: 13670751
DOI: 10.1093/jigpal/jzr009
Appears in Collections:PMF Publikacije/Publications

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