Systemic Risk in Europe: deciphering leading measures, common patterns and real effects
The paper studies salient features of systemic risk in a sample of 22 European (EU and non-EU) countries during January 2010–March 2016. Building on a novel dataset and conducting an empirical horse race, we determine pivotal systemic risk measures for the sample countries. SRISK and volatility indicator tend to lead other metrics, followed by leverage. In contrast to the conventional wisdom, composite systemic risk measures aggregated with the aid of principal and independent component analysis perform worse. The leading systemic risk measures exhibit a high degree of connectedness. The VIX index, TED spread, the Composite Index of Systemic Stress (CISS) and long-term interest rates underlie their dynamics. Two clusters within the sample are identified, with CISS and long-term interest rates being crucial to distinguish between them. There is only scarce evidence for causal linkages between systemic risk and industrial production in the sample countries, based on the concurring results of standard and nonparametric Granger causality tests.
We present a complex analysis of business models for large, medium and small Russian commercial banks from 2006 to 2009. The Russian banks are grouped based on homogeneity criteria of their financial and operational outcomes. The banks’ structure of assets and liabilities, profitability and liquidity ratio are taken into account. The results show how the banks are adjusted their business models before and after the financial turmoil taken place in 2008. In addition, the prevailing banking business models observed for the leading banks in Russia are defined. The banks often changing their business models are found and analyzed.
Data Correcting Algorithms in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.
The goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high-dimensional feature vectors are nowadays produced by convolutional neural networks. The methods to aggregate the features generated for each video frame are used to process the video sequences. A novel hierarchical recognition algorithm is proposed. In contrast to known approaches our algorithm seeks the nearest neighbors only among reference images of most reliable classes selected at the preceding stage to carry out the sequential analysis of a more detailed description level (with a greater dimensionality of the feature vector). At each stage principal components are compared, the number of the components being chosen according to a given portion of explained variations. Datasets like Labeled Faces in the Wild, YouTubeFaces, IAPRA, Jenus Benchmark C and different neural-net face descriptors are used to compare the algorithm with other methods. In contrast with the conventional nearest-neighbor method, the proposed approach is shown to allow a 2- to 16-times reduction of the classifier running time.
The analysis of region differentiation of microentrepreneurship development and indexes of judicial statistics based on the current data of statistical recording are given in the article. The capabilities of cluster analysis for revelation of typological groups of the Russian region depending on the level of entrepreneurial activities and the results of law enforcement practice are represented.
This paper presents a pattern behavioral analysis of 100 largest Russian commercial banks by total assets during an eight- year period: from the first quarter of 1999 to the second quarter of 2007. Bank performance indicators are analyzed. Structural similarities in the development of the banks are examined. A cluster analysis is applied to determine banks with a similar structure of operations. This analysis allows to estimate how the structure of the Russian banking system has been changing over time. In particular, it allows to identify prevailing patterns in the behavior of Russian commercial banks and to analyze the stability of their position in a particular pattern.
The problem of non-invasive preoperative localization of motor areas in human cortex has not been solved yet. In clinical practice, localization of the hand representation in the primary motor cortex often becomes one of the main goals of the pre-surgical evaluation. In healthy subjects the area of the motor hand representation usually corresponds to certain standard anatomical landmarks (hand knob in the precentral gyrus), which can be easily found in sMRI images. Unfortunately, in patients with various brain lesions these landmarks may be absent or not corresponding to the area of the motor cortex. In such cases, location of irreplacable areas must be determined according to their functional and/or temporal dynamical characteristics.
It might become a promising method of localizing primary motor area by way of taking into account the characteristic properties of the primary motor cortex temporal dynamics during movement preparation.
How seriously does the degree of trust in basic social and political institutions for people from different countries depend on their individual characteristics? To answer this question, three types of models have been estimated using the data of the fifth wave of the World Value Survey: the first one based on the assumption about a generalized relationship for all countries, the second one taking into account heterogeneity of countries (using introduction of the country-level variables), the third type applying a preliminary subdivision of countries into five clusters. The obtained results have been used for suggestion of possible actions to increase public confidence in the basic institutions.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.