IDEAS home Printed from https://ideas.repec.org/a/rze/efinan/v8y2012i4p15-29.html
   My bibliography  Save this article

The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins

Author

Listed:
  • Agata Gemzik-Salwach

    (University of Information Technology and Mangement in Rzeszow)

Abstract

The article describes the use of a Value at Risk measure to analyze the effectiveness of a bank. Among various existing possibilities of using this measure, the use of a new method has been proposed, namely, correcting various indicators of bank interest margins by using the Value at Risk measure. The newly established measures were then subjected to empirical tests, whose main objective was to test the capacity of the information resulting from the recourse to the proposed indicators. Using the data from financial statements of banks listed on the Stock Exchange in Warsaw in the years 1998-2012, two types of risk-adjusted bank interest margins were calculated, which provided a way to set the minimum levels that can be expected with the probability assumed in the calculation. The way in which these values are formed over time was then analyzed and they were finally compared with the typical values.

Suggested Citation

  • Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.
  • Handle: RePEc:rze:efinan:v:8:y:2012:i:4:p:15-29
    as

    Download full text from publisher

    File URL: http://www.e-finanse.com/artykuly_eng/232.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:uts:ppaper:v:1:y:2007:i:1:p:55-75 is not listed on IDEAS
    2. Buch, Arne & Dorfleitner, Gregor & Wimmer, Maximilian, 2011. "Risk capital allocation for RORAC optimization," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 3001-3009, November.
    3. Kiani, Khurshid M., 2011. "Relationship between portfolio diversification and value at risk: Empirical evidence," Emerging Markets Review, Elsevier, vol. 12(4), pages 443-459.
    4. Daniel Roesch & Harald Scheule, 2007. "Stress-testing credit risk parameters: An application to retail loan portfolios," Published Paper Series 2007-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Michael Chak‐sham Wong & Yat‐fai Lam, 2008. "Macro stress tests and history‐based stressed PD: the case of Hong Kong," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 16(3), pages 251-260, July.
    6. Farshid Jamshidian & Yu Zhu, 1996. "Scenario Simulation: Theory and methodology (*)," Finance and Stochastics, Springer, vol. 1(1), pages 43-67.
    7. Darryll Hendricks & Beverly Hirtle, 1997. "Bank capital requirements for market risk: the internal models approach," Economic Policy Review, Federal Reserve Bank of New York, vol. 3(Dec), pages 1-12.
    8. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    9. Palomba, Giulio & Riccetti, Luca, 2012. "Portfolio frontiers with restrictions to tracking error volatility and value at risk," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2604-2615.
    10. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    11. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    12. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
    13. Jon Danielsson, 1997. "Extreme Returns, Tail Estimation, and Value-at-Risk," FMG Discussion Papers dp273, Financial Markets Group.
    14. William Fallon, 1996. "Calculating Value-at-Risk," Center for Financial Institutions Working Papers 96-49, Wharton School Center for Financial Institutions, University of Pennsylvania.
    15. J. S. Butler & Barry Schachter, 1996. "Improving Value-At-Risk Estimates By Combining Kernel Estimation With Historical Simulation," Finance 9605001, University Library of Munich, Germany.
    16. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiongwei Ju & Neil D. Pearson, 1998. "Using Value-at-Risk to Control Risk Taking: How Wrong Can you Be?," Finance 9810002, University Library of Munich, Germany.
    2. Jose A. Lopez, 1996. "Regulatory Evaluation of Value-at-Risk Models," Center for Financial Institutions Working Papers 96-51, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Pérignon, Christophe & Smith, Daniel R., 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 362-377, February.
    4. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
    5. Packham, N. & Woebbeking, F., 2023. "Correlation scenarios and correlation stress testing," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 55-67.
    6. McNeil, Alexander J. & Smith, Andrew D., 2012. "Multivariate stress scenarios and solvency," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 299-308.
    7. Packham, N. & Woebbeking, C.F., 2019. "A factor-model approach for correlation scenarios and correlation stress testing," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 92-103.
    8. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    9. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    10. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    11. Karagiannidis, Iordanis & Sykes Wilford, D., 2015. "Modeling fund and portfolio risk: A bi-modal approach to analyzing risk in turbulent markets," Review of Financial Economics, Elsevier, vol. 25(C), pages 19-26.
    12. Dissem, Sonia & Lobez, Frederic, 2020. "Correlation between the 2014 EU-wide stress tests and the market-based measures of systemic risk," Research in International Business and Finance, Elsevier, vol. 51(C).
    13. Abdelaziz Rouabah & John Theal, 2010. "Stress testing: The impact of shocks on the capital needs of the Luxembourg banking sector," BCL working papers 47, Central Bank of Luxembourg.
    14. Pawel Siarka, 2012. "Implementation of the Stress Test Methods in the Retail Portfolio," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 2(6), pages 1-2.
    15. Amira Dridi & Mohamed El Ghourabi & Mohamed Limam, 2012. "On monitoring financial stress index with extreme value theory," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 329-339, March.
    16. Chenglu Jin & Thomas Conlon & John Cotter, 2023. "Co-Skewness across Return Horizons," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1483-1518.
    17. Dionne, Georges & Pacurar, Maria & Zhou, Xiaozhou, 2015. "Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 202-219.
    18. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    19. repec:zbw:bofitp:2011_007 is not listed on IDEAS
    20. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    21. Martin, Anna D. & Mauer, Laurence J., 2003. "Exchange rate exposures of US banks: A cash flow-based methodology," Journal of Banking & Finance, Elsevier, vol. 27(5), pages 851-865, May.

    More about this item

    Keywords

    VaR; risk management; net interest margin Least Squares Method;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:rze:efinan:v:8:y:2012:i:4:p:15-29. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pawel Bochenek (email available below). General contact details of provider: https://edirc.repec.org/data/igwsipl.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.