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2013 | Zastosowanie metod ilościowych w zarządzaniu ryzykiem w działalności inwestycyjnej | 140--151
Tytuł artykułu

Using quantitative methoda on credit risk management in the process of banking capital investment

Warianty tytułu
Języki publikacji
EN
Abstrakty
In the article we have introduced the possibility of using quantitative methods to manage credit risk in the process of effective banking capital investments. The hypotheses that appropriate use of quantitative methods in credit risk management in a commercial bank leads to optimal banking capital investments has been supported. Commercial banks have the opportunity to achieve additional return on equity by means of equity savings which allow them to accelerate lending. With estimated equity saving of 30%, use of appropriate approach might significantly increase the return on capital (approximately 13%) depending on the volume and structure of assets as well as other parameters. Developed methodology for additional return on bank equity calculations using suitable approach with respect to the selected bank's portfolio of active deals allows management to optimally adjust performance parameters, manage the quality of loan portfolio and risk of banking transactions. Criticism of the 1RS models is focused on various aspects of their activities. Several studies have shown that perfect rating systems do not exist, their explanatory ability in relation to capital requirements calculations and evaluation of the client's risk profile quality being significantly limited. Quality and explanatory ability of different types of the 1RS vary. Models used to measure risk are imperfect, providing unreliable results and contributing to procyclical trends in the banking system. In this context, it will be necessary to tune fundamental aspects of building adequate performance, stability and security of the international banking sector. (fragment tekstu)
Twórcy
  • Tomas Bata University in Zlín, Czech Republic
  • Tomas Bata University in Zlín, Czech Republic
Bibliografia
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  • Basel Committee on Banking Supervision: Studies on the Validation of Internal Rating Système, Working Paper No. 14. Basel: Bank for International Settlements, 2005.
  • Belás J. a kol., Management komercnÿch bank, bankovÿch obchodov a operácií, Georg, Zilina 2010.
  • Boegelein L., Validation of Internal Rating and Scoring Models. Prezentácia, Ernst & Young, 2010, http://www.crc.man.ed.ac.uk/conference/archive/2005/presen tations/Boegalain-Leif.pdf
  • Danielson J. a kol., An Academic Response to Basel II. Special paper No. 130, Financial Markets Group, 2001.
  • Deutsche Bundesbank: Approaches to the validation of internal rating system, Monthly Report. September 2003, http://www.bundesbank.de/download/volks wirtschaft/mba/2003/200309_en_rating.pdf
  • Kráf M., Bankovnictvi a jeho produkty, Georg, Zilina 2009.
  • Mitchell J., Van Roy P., Failure prediction models: performance, disagreements and internal rating systems, Brussels, National Bank of Belgium, 2007.
  • NBS: Opatrenie NBS c. 4/2007 o vlastnÿch zdrojoch fmancovania bank a poziadavkách na vlastné zdroje fmancovania bánk, Bratislava, 2007.
  • Oesterreichische Nationalbank, Guidelines on credit risk management. Rating models and validation. Vienna, OeNB Printing Office, 2004.
  • Ozdemir B., Validating Internal Rating systems, The RMA Journal, 2009, http:// www2.standardandpoors.com/spf/pdf/media/RMA_Validating_IRS_Bogie_Ozdem r_01_06_09.pdf
  • www.cnb.cz/miranda2/export/sites/www.cnb.cz/cs/dohled_fmancni_trh/legislativni _zakladna/ stanoviska_cnb/download/ stanovisko_EC_CRD_IV.pdf
  • International Convergence of Capital Measurement and Capital Standards: A Revised Framework - Comprehensive Version. Basel: Bank for International Settlements, 2006, available from :< http://www.bis.org/publ/bcbsll8.pdf>
  • Risk Management - Uni Credit: consolidated financial statements. UNI CREDIT. Unicreditgroup.eu, http://www.arl0.unicreditgroup.eu/bilancio.php?area==area05& page=05_269&ln=en
  • R Development Core Team, A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna 2011, http://www.R-project.org/
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171278089

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