Short-Term Modeling and Forecasting in the Banking Sector

Student: Polovyan Alexander

Educational Programme: Applied Economics (Master)

Year of Graduation: 2019

The research is dedicated to the development of probability of default model of Russian banks. This study is quite useful from both theoretial and practical perspective. First, rating and scoring model development based on constantly changing data from open sources is a crutial practical problem for various economic agents. On the one hand, for the Central Bank it is important to identify risky banks in order to take measures to stabilise their financial position, on the other hand, commercial banks themselves could control their financial stability. Second, logit regression paired with WOE-transformation and machine learning algorithms is a rare approach to the modelling in this segment

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