Оценка вероятностей дефолта российских банков: эмпирический анализ
We suggest an econometric model of probability of default based on regular financial disclosures of Russian banks. We also suggest a quantization of the continuous explanatory variables that allows to account for non-linear effects and to achieve superior accuracy compared with regression tree and Bayesian network models estimated over the same sample. The econometric estimates of probability of default are broadly consistent with the historical default frequencies of rated obligors and risk-neutral probabilities of default inferred from credit spreads in a reduced-form model.
The paper presents a review of stochastic framework for term structure modeling and shows comparative advantages of commonly used techniques. The main application of the research is coherent modeling of credit and interest rate risk for Euro zone issuers.
In our research, we examine what macroeconomic factors determine and influence the credit cycle. In addition, our study contains four sections with theoretical and empirical parts, in which we describe how to measure credit cycles for developed and developing countries, and then introduce an important measure of the credit gap. Our results show a comparative analysis of credit cycles between different countries with different economic growth, and we have created an econometric model, which shows us the impact of macroeconomic factors according to the credit cycles for developing and developed economies.
In textbook the main issues connected with organization of credit analysis in a commercial bank were considered. The role of credit analysis in risk management system is shown. The methodology and specific methods for assessing the creditworthiness of borrowers used by banks are set out by complex approach. The textbook includes international recommendations for introduction of internal credit risk assessment systems in banks. With the aim at presenting the material examples from the practice of commercial banks, analytical tables, diagrams and figures were used.
This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
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.
We examine the synergy of the credit rating agencies’ efforts. This question is important not only for regulators, but also for commercial banks if the implementation of the internal ratings and the advanced Basel Approach are discussed. We consider Russian commercial banks as a good example where proposal methods might be used. Firstly, a literature overview was supplemented with an analysis of the activities of rating agencies in Russia. Secondly, we discussed the methods and algorithms of the comparison of rating scales. The optimization task was formulated and the system of rating maps onto the basic scale was obtained. As a result we obtained the possibility of a comparison of different agencies’ ratings. We discussed not only the distance method, but also an econometric approach. The scheme of correspondence for Russian banks is presented and discussed. The third part of the paper presents the results of econometric modeling of the international agencies’ ratings, as well as the probability of default models for Russian banks. The models were obtained from previous papers by the author, but complex discussion and synergy of their systematic exploration were this paper’s achievement. We consider these problems using the example of financial institutions. We discuss the system of models and their implementation for practical applications towards risk management tasks, including those which are based on public information and a remote estimation of ratings. We expect the use of such a systemic approach to risk management in commercial banks as well as in regulatory borders.
The paper considers the financial choice of entrepreneurs at their initial stage of development as a key criterion of a new firm potential riskiness. The main objective of the research is the methodology elaboration aimed at the numerical estimation of the role of informal financial resources involved in the small business creation. Two fundamental considerations have been tested. The former implies that informal investment is a substitution for unavailable formal sources, including venture capital (because of the lack of essential networks and connections with business associations). The latter performs the opposite concept of negative effects: economic reasoning discouragement and inefficient resources allocation. A special technique is introduced in order to measure the credit quality of early entrepreneurial activity and to estimate its contingency with the financial strategy. The methodology validation is realised under Global Entrepreneurship Monitor conceptual framework. The results are received for 42 countries in 2006-2007, depicting the influence of informal support on potential losses under the second consideration. As a result, informal investments are inefficient when the concentration of credit risk in the economy is rather high. Investorsђ expectations about the entrepreneurial growth of the firm are pessimistic, anticipated returns on investments are too low to be economically reasonable. The outcome leads to the irrecoverable losses, both financial (short-received profitability) and nonfinancial (decreased output, the lack of innovativeness, flexibility, and inventiveness).