An Analysis of Ratings of Russian Banks

Since the recent financial crisis, both the Russian business community and foreign investors have started to make more and more use of ratings of the reliability of Russian banks, i.e., their ability to meet interest and repayment commitments to the investors.In response to this, the number of rating agencies has increased over the past few years.In this paper, existing ratings are analyzed and compared using ordered probit models that explain bank ratings from bank characteristics such as size indicators and financial ratios characterizing profitability, or default risk on loans given.Moreover, on the basis of a survey among financial experts, models for expert ratings are constructed and results are compared to those for the agency ratings.We find that agency and expert ratings of virtual banks are largely in line with each other, but there are also some differences.For example, liquidity measures are important for agency ratings but insignificant for the expert ratings.Moreover, we find some surprising differences between expert ratings of real banks and expert ratings of virtual banks.While overdue loans are important for the virtual banks, they play no role in either the agency ratings or the expert ratings of real banks.An explanation may be that banks manage to mask the actual number of overdue loans.

What factors drive the Russian banks license withdrawal

The binary and multinomial logit models are applied for prediction of the Russian banks defaults (license withdrawals) using data from bank balance sheets and macroeconomic indicators. Significantly different models correspond to the two main grounds for license withdrawal: financial insolvency and money laundering. Analysis of data for the period 2005.2–2008.4 for accurate prediction of a bank’s financial insolvency, which is the focus of interest for the Russian Deposit Insurance Agency, demonstrates that the multinomial model doesn’t outperform the binary model

Models for Moody’s bank ratings

The paper presents an econometric study of the two bank ratings assigned by Moody's Investors Service. According to Moody’s methodology, foreign-currency long-term deposit ratings are assigned on the basis of Bank Finan-cial Strength Ratings (BFSR), taking into account “external bank support factors” (joint-default analysis, JDA). Models for the (unobserved) external support are presented, and we find that models based solely on public infor-mation can approximate the ratings reasonably well. It appears that the ob-served rating degradation can be explained by the growth of the banking sys-tem as a whole. Moody’s has a special approach for banks in developing countries in general and for Russia in particular. The models help reveal the factors that are important for external bank support

Sandwiched women: Health behavior, health, and life satisfaction

This paper studies the impact of sandwich generation caregiving on the health behavior, self-assessed health and life satisfaction of Russian women. It presents evidence that sandwich generation caregiving reduces the likelihood of medical examinations, and regular meals. Alcohol consumption and likelihood of smoking are reduced. The like­lihood of obesity increases, the proportion of chronic diseases decreases, and self-assessed health improves. The proportion of depression decreases. These effects may be the result of an inattentive attitude to one’s health and a consciousness of the social significance of fulfilling one’s duty. These effects vary with socio-demographic characteristics

Models for Moody’s bank ratings

The paper presents an econometric study of the two bank ratings assigned by Moody's Investors Service. According to Moody’s methodology, foreign-currency long-term deposit ratings are assigned on the basis of Bank Finan-cial Strength Ratings (BFSR), taking into account “external bank support factors” (joint-default analysis, JDA). Models for the (unobserved) external support are presented, and we find that models based solely on public infor-mation can approximate the ratings reasonably well. It appears that the ob-served rating degradation can be explained by the growth of the banking sys-tem as a whole. Moody’s has a special approach for banks in developing countries in general and for Russia in particular. The models help reveal the factors that are important for external bank support

Моделирование рейтингов российских банков

The paper presents econometric analysis of the of Russian banks ratings, and the experts’ opinion based on a survey, designed in a framework of the project. From the ratings and the survey we derived the factors that in the experts’ opinion and in the rating agencies’ opinion are most important for bank reliability. The models of the ratings and experts’ opinions were designed for real and virtual banks. We constructed the model ratings of the Russian banks. These models use only publicly available information and hence could be used as an early warning system of the current bank reliability