The back side of banking in Russia: forecasting bank failures with negative capital Online publication date: Thu, 01-Dec-2016
by Alexander Karminsky; Alexander Kostrov
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 7, No. 1/2, 2017
Abstract: Since 2013, we have observed an increasing number of failed Russian banks with negative capital and falsified financial reporting. We use previously unavailable data for the period 2010-1H2015 to develop a logit model predicting the probability of bank failure with negative capital. In order to do so, we suggest solutions for the class imbalance and variable selection problems. The models chosen are confirmed to be robust and have longer forecasting horizons compared to previous research. Also, we implement a novel probability-based approach to the out-of-sample forecasting evaluation which confirms a good fit of the selected models to data. The model predicts bank failures in three quarters and finds 33% of actual failures among 5% of banks with the highest predicted probability to fail (out-of-sample). In addition, we make available previously unpublished banking data for Russia.
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