ЛОГІТ-МОДЕЛЬ ПРОГНОЗУВАННЯ ЙМОВІРНОСТІ БАНКРУТСТВА БАНКІВ
Journal Title: Вісник Академії праці, соціальних відносин і туризму - Year 2018, Vol 4, Issue
Abstract
The study reviews the peculiarities of European, world and Ukrainian practice of constructing models for forecasting the probability of banks bankruptcy. For prediction of the probability of bankruptcy of banks, logit regression has been chosen, because its advantages are the possibility of obtaining a quantitative estimation of the probability in an explicit form and its high stability.We completed all stages of the algorithm for making the logit-model: selection of 27 liquidated and 27 stable banks; selection and calculation of economic indicators which were necessary for use in the process of constructing a model; checking the significance of the factors by using two selective F-tests for dispersions; evaluation of the correlation between the selected parameters. The initial array consisted of 37 bank performance indicators of liquidity, solvency and financial stability, profitability, business activity, as well as specific indicators. Authors using a Farrar-Globard algorithm and a matrix of pair coefficients of correlation, selected predictors for constructing the model. As a result, we obtained the logit regression equation by the STATISTICA program and checked the quality of the model. The percentage of forecasted bankruptcy and stable financial state according to our logit-model is 100%, which indicates its high quality. Therefore, logistic regression has been mentioned can be used to predict the financial state of banking institutions in Ukraine.
Authors and Affiliations
Viktoriia Kremen, Tetiana Bochkarova
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