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Estimation of the Russian Banks Default Probability

Student: Vlasov Nikita

Supervisor: Vladimir Sokolov

Faculty: International College of Economics and Finance

Educational Programme: Double degree programme in Economics of the NRU HSE and the University of London (Bachelor)

Year of Graduation: 2017

This paper is dedicated to the analysis of the default probability of banks in Russian Federation. I use the most recent data about bank’s accounting information to structure logistic regression model that will be able to predict the probability of default for Russian banks. This research is aimed at constructing, using publically available accounting data, the model that will have adequate predictive power. Several microeconomic and macroeconomic variables are used as predictors in the models. I will test the regressions with different combination of macroeconomic and macroeconomic factors to determine the model with highest predictive power. This research will discuss and examine in detail what are significant factors and how they influence on the default probability of Russian banks and present the results of several logistic regressions.

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