Financial Architecture in the Different Life Cycle Stages
In this article, we consider the relation between capital structure, corporate governance, ownership structure and performance of a company depending on its life cycle stages. The central aim of this study is to define the most sustainable and effective types of financial architecture by using the cluster and regression analysis. This study describes the three stages of the life cycle of a company: the first stage is growth, followed by maturity and finally the stage of decline, but for our research we only examine companies in the maturity stage. The research includes 11 countries from emerging markets and the primary sample includes 4,675 non-financial companies from 2011 to 2015. As the measure of a company’s performance, we used Tobin’s Q coefficient and total shareholder return. The primary sample was divided into the 3 life cycle stages by using the approach of comparing the growth rates of revenues at the average rate of revenue growth in the industry (Cao, 2010); however, we did not consider the earlier stages of the life cycle due to the specificity of the sample. A cluster analysis was performed on the sample for the growth and maturity stages in order to show the difference between the clusters that depends on the life cycle stages. We analyzed the clusters’ sustainability by regression analysis in each cluster. We described the influence of the financial architecture component on market performance. The results indicate more than one sustainable cluster and demonstrate the influence of the ownership structure, capital structure and the board characteristics on the company’s efficiency depending on the stage of the life cycle, which proves there is a need to take into account the issues of the life cycle. The managers and directors of a company can use results of this study when developing a company’s strategy, especially during the transition period from one life cycle to another.
Current article is dedicated to the relationship between effectiveness of usage of intellectual capital and capital structure of firms in Russia in 2005-2007. Current research showed that effectiveness of usage of intellectual capital of firms has a positive influence over the level of financial leverage. The result of the research has showed that the more effective usage of intellectual capital makes a company more attractive for the credit organizations and opens more sources to obtain financing. There were also revealed some specific features of relationship between the effectiveness of utilization of intellectual capital and corporate financial decisions in Russia. The result is consistent with the results from the similar researches from the developed markets.
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.
The paper explores theoretical approaches to the company IPO underpricing and analyzes capital structure impact on the underpricing of the Russian issuers.
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.
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.
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.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.