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\iteman{io-port 06072923}
\itemau{Simi\'c, Dragan; Kova\v{c}evi\'c, Ilija; Simi\'c, Svetlana}
\itemti{Insolvency prediction for assessing corporate financial health.}
\itemso{Log. J. IGPL 20, No. 3, 536-549 (2012).}
\itemab
Summary: 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.
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\itemcc{}
\itemut{corporate financial health; corporate insolvency; multivariate discriminant analysis; self-organized maps}
\itemli{doi:10.1093/jigpal/jzr009}
\end