Описание потребности в ликвидности со стороны российской банковской системы на основе статистики оборотов
On the basis of statistical balances and turnovers subaccounts Russian banking system built description liquidity needs of banks. Initial accounts combined into 35 units (which include loans and deposits by macroeconomic agents) are ranked by the rate of turnover. Based on this classification, there is a group of units that characterize the level of liquidity in the banking system . It is shown that the use of information about the turnover of aggregates can significantly extend the class of models needs of the banking system 's liquidity. Econometric model is presented describing both balances and transactions liquidity. The model is calibrated on monthly data from January 2007 to June 2013. The observed pattern previously linking volume of loans granted by the banking system, and accepted deposits can be explained by balancing units having turnover rate of the same order.
The aim of our research is to present an approach to systemic liquidity management of the company. We study patterns of liquidity management that reflect the requirements of the relationship between strategic and current financial management, the interaction of liquidity risk and profitability as the core of added value creation, as well as the tools for their implementation. The econometric toolkit was aimed at identifying threshold points in the joint dynamics of liquidity and profitability with the identification of ranges of positive and negative nature of their interaction. The result of theoretical research was tested on the example of Russian metallurgical industry. The analysis revealed that metallurgical industry is characterized by a lower liquidity threshold, as well as profitability. However, in the framework of this study, all the tasks have been accomplished. A possible direction for future research in this field is the use of comprehensive approach to the study of liquidity management in order to understand which combination of tactic and strategic action enables liquidity management to be expedient for the company.
This article presents an engineering approach to estimating market resiliency based on analysis of the dynamics of a liquidity index. The method provides formal criteria for defining a “liquidity shock” on the market and can be used to obtain resiliency-related statistics for further research and estimation of this liquidity aspect. The developed algorithm uses the results of a spline approximation for observational data and allows a theoretical interpretation of the results. The method was applied to real data resulting in estimation of market resiliency for the given period.
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.
The article gives an overview of influence of stock market discrimination on market value of companies in China. There are two types of shares on Chinese stock market: class A shares, which are available for domestic investors, and class B shares, which are available for foreign investors. Such market structure is not a unique Chinese market's feature. It is also used in such countries as Finland, Singapore, Switzerland, Thailand, etc. What differs Chinese market from markets with similar structure is the fact that class B shares are traded with substantial discount to class A shares. Such a situation is explained by such factors informational asymmetry between domestic and foreign investors; different liquidity of different classes of shares; diversification effect, connected with investment in Chinese stock market; size of companies; ratio of amounts of shares of different classes; stock exchange where company's shares are traded.
Liquidity is an important characteristic for any bond, but now in the literature there are no models for estimating the liquidity premium. Moreover, there is not even an exact definition of this notion. There are many facts proving the existence of the liquidity premium in the bond market. One of such fact, for example, is the difference between values of the bond spread and the credit default swap (CDS) premium. Following the Longstaff (2005) study, often, in practice, CDS data are used for the estimation of the pure credit risk of the underlying bond and henc for the separation of the bond risk premium from the liquidity premium and credit risk premium. However, the fact that CDS premium can be used for the pure credit risk measurement is a disputable proposition. The purpose of this paper is to make recommendations on the applicability of such approach for assessing liquidity premium. In this paper the risks associated with CDS transactions will be considered.Also, different approaches for assessing the liquidity bond premium and liquidity CDS premium will be reviewed as well as the correlation of these quantitites. We will see that the CDS premium does not measure the pure credit component of the bond spread.
Argentina, the second largest country in Latin America, hardly recovered form the recession of the year 2001, faces the crisis again in 2008. First of all, the crisis affected the credit and banking sphere of the country, reducing the volumes of credit and deposit. But during the crisis, Argentina managed to carry out the restructuring of the financial system. The Global financial and economic crisis has shown the importance of the investors' confidence.
The bond market is a key securities market and emerging economies present exciting, new investment opportunities. This timely book provides insights into these emerging bond markets through empirical models and analytical databases, i.e. Bloomberg, Eikon Refinitiv and the Russian Cbonds.
The book looks at the dynamics of the development of emerging bond markets, their competitiveness, features and patterns using macro and micro level data. It also takes into consideration various securities type i.e. government, corporate, sub-federal and municipal bonds, to identify respective challenges and risks. The book also analyses factors that may inhibit or stimulate a well-balanced financial market. It includes case studies of Asian, Latin American and Russian bond markets, as also as cross-country comparisons.
It will be a useful reference for anyone who is interested to learn more of the bond market and the modelling techniques for critical data analysis.
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.