Probability of default models of Russian banks

This paper presents results from an econometric analysis of Russian bank defaults during the period 1997–2003, focusing on the extent to which publicly available information from quarterly bank balance sheets is useful in predicting future defaults. Binary choice models are estimated to construct the probability of default model. We find that preliminary expert clustering or automatic clustering improves the predictive power of the models and incor-poration of macrovariables into the models is useful. Heuristic criteria are suggested to help compare model performance from the perspectives of investors or banks supervision authorities. Russian banking system trends after the crisis 1998 are analyzed with rolling regressions.banks; Russia; probability of default model; early warning systems

How To Easily Adopt A Plant-Based Diet For Weight Loss And Health Promotion

The Healthy Defaults How-To Pamphlet is intended to provide guidance and healthy defaults to assist individuals in adopting a plant-based diet. Tips on how to transition, save time in the kitchen, plant-based swaps, how to set up a power plate, omit oil when cooking and resources such as phone applications for meal plans and recipes, books and documentaries will be discussed.https://dune.une.edu/an_studedres/1051/thumbnail.jp

Impacts of Homeownership Education and Counseling on Homebuyer Purchasing Power: Summary of Findings

In addition to reducing defaults and foreclosures, homeownership education and counseling is often claimed to help families achieve homeownership in the first place by helping them to navigate the homebuying process, improve their credit, and access favorable financing products. This study tests an approach to quantifying this benefit by estimating the amount of increased purchasing power that results from homeownership education and counseling. While the results are preliminary, they provide early suggestive evidence that high-performing homeownership education and counseling agencies may provide quantifiable benefits that exceed their costs of assistance. The study also makes recommendations for how data could be collected on a more systematic basis to track and assess these benefits

What If Fiduciary Obligations Are Like Contractual Ones?

This essay, to appear in Contract, Status, and Fiduciary Law (Miller & Gold, 2016), explores three ways fiduciary obligations might be like contractual ones: in the methods lawmakers use or should use to determine the content of the obligation; in the private voluntary acts that generate the obligation; and in the fact that the obligation is a default that parties have the power to alter. The thesis is that to the extent that these similarities exist, they are not especially revealing. Theorists who emphasize the similarities commonly treat contract law as a private power-conferring rule, then analogize the law of fiduciary obligations to it. In fact, the law of contract is more complex and serves a broader range of purposes than just giving private parties the ability to undertake legal obligations when they choose. Contract obligations are sometimes imposed for reasons other than party choice, and contract defaults and altering rules can be designed to serve other social purposes. A more nuanced understanding of the functions and design of contract law suggests that structural similarities between fiduciary obligations and contractual ones tell us less about the fiduciary obligations than we might have hoped. The explanation of why that is so, however, reveals important features both of contract law and of the law of fiduciary obligations

Modelling Credit Defaults Using Support Vector Machine And Binary Logistic Models

Defaulting on a loan essentially occurs when an individual has stopped making payments on a loan or credit card according to the account's terms. A default model is constructed by financial institutions to determine default probabilities on credit obligations by a corporation or sovereign entity. A probability of default model uses multivariate analysis and examines multiple characteristics or variables of the borrower, and it will usually account for credit or business cycles by either incorporating current financial data into the generation of the model or by including economic adjustments. Modelling loan default allows financial institutions to determine typical features and patterns of behavior that lead to a future inability to make debt repayments. This modelling helps to assess the probability of future default for each client. The focus of this study was to apply the support vector machine and binary logistic models to model credit defaults. The process involved identification of the predictors that could be associated with credit defaults as well as comparison of the performance of the prediction models on their statistical power to model credit defaults. The analysis was done using R statistical software. The results showed that variables; credit amount, marital status, credit history and location of property used as security were significant predictors of credit defaults. The results also showed that the binary logistic model had a better performance that the support vector machine model in terms of F1 score and accuracy of predicting credit defaults. The logistic model had the accuracy of 0.826087 and an F1 score of 0.8809524. The support vector machine had the accuracy of 0.7826087 and an F1 score of 0.8554913. From the study findings, it was concluded that, the accuracy of the prediction models in modelling of credit defaults was dependent on the variables considered. Different set of variables would yield different accuracies for the prediction models

Political institutions and debt crises

This paper shows that political institutions matter in explaining defaults on external and domestic debt obligations. We explore a large number of political and macroeconomic variables using a non-parametric technique to predict safety from default. The advantage of this technique is that it is able to identify patterns in the data that are not captured in standard probit analysis. We find that political factors matter, and do so in different ways for democratic and non-democratic regimes, and for domestic and external debt. In democracies, a parliamentary system or sufficient checks and balances almost guarantee the absence of default on external debt when economic fundamentals or liquidity are sufficiently strong. In dictatorships, high stability and tenure play a similar role for default on domestic debt

Using a bootstrap approach to rate the raters

This paper compares the accuracy of credit ratings of Moody s and Standard&Poors. Based on 11,428 issuer ratings and 350 defaults in several datasets from 1999 to 2003 a slight advantage for the rating system of Moody s is detected. Compared to former research the robustness of the results is increased by using nonparametric bootstrap approaches. Furthermore, robustness checks are made to control for the impact of Watchlist entries, staleness of ratings and the effect of unsolicited ratings on the results