Developing Financial Crisis Prediction Models for Ukrainian Insurance Companies by Using Logistic Regression

Anton Valeriiovych Lytvyn, National University of Kyiv-Mohyla Academy


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Abstract


The article discusses financial crisis prediction models developed for Ukrainian insurance companies by using conditional probability models, namely the logistic regression. The Superdiscretization procedure for the bankrupt insurers has been implemented in order to enhance the classification characteristics of the models. The paper introduces a criterion for selecting the most applicable logistic model.

 


Keywords


financial crisis; bankruptcy; prediction; insurance companies; economic-mathematical models; conditional probabilities models; logistic regression.

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References


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Citations

Cite this article in APA format:

Lytvyn, A. (2016). Developing Financial Crisis Prediction Models for Ukrainian Insurance Companies by Using Logistic Regression. Scientific Papers NaUKMA. Economics, 1(1), 101-105.

Cite this article in GOST format:

Lytvyn Anton. Developing Financial Crisis Prediction Models for Ukrainian Insurance Companies by Using Logistic Regression // Scientific Papers NaUKMA. Economics. - 2016. - Vol. 1, N. 1. - P. 101-105.

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ISSN: 2519-4747 (online); 2519-4739 (print)