IDEAS home Printed from https://ideas.repec.org/p/icr/wpmath/12-2008.html
   My bibliography  Save this paper

Dynamic Analysis of the Behavioural Patterns of the Largest Commercial Banks in the Russian Federation

Author

Listed:
  • Fuad Aleskerov

    ()

  • V. Belousova

    ()

  • M. Serdyuk

    ()

  • V. Solodkov

    ()

Abstract

This paper presents a pattern behavio ral 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.

Suggested Citation

  • Fuad Aleskerov & V. Belousova & M. Serdyuk & V. Solodkov, 2008. "Dynamic Analysis of the Behavioural Patterns of the Largest Commercial Banks in the Russian Federation," ICER Working Papers - Applied Mathematics Series 12-2008, ICER - International Centre for Economic Research.
  • Handle: RePEc:icr:wpmath:12-2008
    as

    Download full text from publisher

    File URL: http://www.biblioecon.unito.it/biblioservizi/RePEc/icr/wp2008/ICERwp12-08.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Алескеров Ф. Т. & Солодков В. М. & Челнокова Д. С., 2006. "Динамический Анализ Паттернов Поведения Коммерческих Банков России," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 10(1), pages 48-62.
    2. Fuad Aleskerov & C. Emre Alper, 2000. "A Clustering Approach to Some Monetary Facts: A Long-Run Analysis of Cross-Country Data," The Japanese Economic Review, Japanese Economic Association, vol. 51(4), pages 555-567, December.
    3. Caner S. & Kontorovich V., 2004. "Efficiency of the banking sector in the Russian Federation with international comparison," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 8(3), pages 357-375.
    4. Alexis Derviz & JiÅí Podpiera, 2008. "Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(1), pages 117-130, January.
    5. Cole, Rebel A. & Gunther, Jeffery W., 1995. "A CAMEL rating's shelf life," MPRA Paper 24693, University Library of Munich, Germany, revised 01 Nov 2008.
    6. Otchere, Isaac & Chan, Janus, 2003. "Intra-industry effects of bank privatization: A clinical analysis of the privatization of the Commonwealth Bank of Australia," Journal of Banking & Finance, Elsevier, vol. 27(5), pages 949-975, May.
    7. James B. Thomson, 1991. "Predicting bank failures in the 1980s," Economic Review, Federal Reserve Bank of Cleveland, issue Q I, pages 9-20.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aysan, Ahmet Faruk & Ertek, Gurdal & Ozturk, Secil, 2009. "Assessing the adverse effects of interbank funds on bank efficiency through using semiparametric and nonparametric methods," MPRA Paper 38113, University Library of Munich, Germany.
    2. Белоусова В. Ю., 2009. "Эффективность Издержек Однородных Российских Коммерческих Банков: Обзор Проблемы И Новые Результаты," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 13(4), pages 489-519.

    More about this item

    Keywords

    Bank; dynamic pattern analysis; cluster analysis;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:icr:wpmath:12-2008. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Simone Pellegrino). General contact details of provider: http://edirc.repec.org/data/icerrit.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.