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Modeling Probability of Enterprises Bankruptcy: Comparative Analysis of Methods

Student: Kartashova Marina

Supervisor: Marina V. Radionova

Faculty: Faculty of Economics, Management, and Business Informatics

Educational Programme: Economics (Bachelor)

Year of Graduation: 2019

This project refers to some critical concepts pertaining to the sphere of corporate bankruptcy. At present hundreds of Small and Medium Enterprises (SME’s) are falling a victim to the harsh realities of a volatile financial sector. The central question is what exactly involves company’s insolvency. The purpose of this study is to develop a model for bankruptcy prediction, which most accurately estimate the enterprise’ failure. To define the strongest predictive model it is supposed to use a sample consisting of both financial and non-financial indicators from 2014 to 2018, which influence to bankruptcy probability. During the study, a logistic regression model and a two-layer neural network model were developed. At first glance, the results are similar to previous studies, however the uncertainty still remain.

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