The back side of banking in Russia: forecasting bank failures with negative capital
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 In addition, we make available previously unpublished banking data for Russia
The pace of global recovery remains weak. More than twelve months since the G-20 summit in Los Cabos, G-20 members are laboring their way towards “Strong, Sustainable and Balanced Growth” in a clouded world economic outlook, with the eurozone in a state of recession, a combination of policy stalemate and across the board fiscal consolidation constraining growth in the U.S., and emerging markets and developing countries experiencing a clear slowdown compared to their rapid pre-crisis expansion. A durable recovery that creates good jobs, which G-20 leaders agreed to cooperate for in September 2009, proves to be an elusive objective. Fiscal consolidation acts as a drag on economic recovery and the G-20’s capacity to deliver on the growth and jobs agenda is questioned by its citizens. This calls for the G-20 members’ commitment to a balanced and coordinated mix of policies and instruments, reflective of the state of their economies, which would gradually strengthen economic growth and promote macroeconomic stability. Responding to global and domestic priorities, Russia has placed growth and jobs at the core of the G-20 agenda within the fundamental question of what should be the main macroeconomic and financial policy requirements for growth.
The manual is given a general description of the methods and the Principles of accounting, as well as the main topics of financial accounting with examples. In the fourth part of the work presented prac-cal objectives for the course, as well as complex tasks and a test. The manual is intended for students majoring in "Economics" and "Management", studying accounting course. Also, benefits may be useful to managers and financiers, who are faced with accounting and reporting systems in the enterprise, as well as for anyone interested in the issues of accounting.
The cornerstone of retail banking risk management is the estimation of the expected losses when granting a loan to the borrower. The key driver for loss estimation is probability of default (PD) of the borrower. Assessing PD lies in the area of classification problem. In this paper we apply FCA query-based classification techniques to Kaggle open credit scoring data. We argue that query based classification allows one to achieve higher classification accuracy as compared to applying classical banking models and still to retain interpretability of model results, whereas black-box methods grant better accuracy but diminish interpretability.
Combination of the offered volume on the REPO auction with the Bank of Russia and the demand for it produce powerful signaling mechanism for the interbank money market. In order to have a possibility to emit an unintended signal there is a need for a robust estimator of the demand. This paper proposes an approach to produce such an estimator through an ensemble of logistic and linear regression models. This estimator successfully emulates many of the key features of the process.
In the paper some prominent features of a modern financial system are studied using the model of leverage dynamics. Asset securitization is considered as a major factor increasing aggregate debt and hence systems uncertainty and instability. A simple macrofinancial model includes a logistic equation of leverage dynamics that reveals origins of a financial bubble, thus corresponding closely to the Minsky financial instability hypothesis. Using ROA, ROE, and the interest rate as parameters, the model provides wide spectrum of leverage and default probability trajectories for the short and long run.