IDEAS home Printed from https://ideas.repec.org/a/eee/finsta/v8y2012i4p303-319.html
   My bibliography  Save this article

Value-at-Risk models and Basel capital charges

Author

Listed:
  • Rossignolo, Adrian F.
  • Fethi, Meryem Duygun
  • Shaban, Mohamed

Abstract

In the wake of the subprime crisis of 2007 which uncovered shortfalls in capital levels of most financial institutions, the Basel Committee planned to strengthen current regulations contained in Basel II. While maintaining the Internal Model Approach based on Value-at-Risk, a stressed VaR calculated over highly strung periods is to be added to present directives to constitute Minimum Capital Requirements. Consequently, the adoption of the appropriate VaR specification remains a subject of paramount importance as it determines the financial condition of the firm. In this article I explore the performance of several models to compute MCR in the context of Emerging and Frontier stock markets within the present and proposed capital structures. Considering the evidence gathered, two major contributions arise: (a) heavy-tailed distributions – particularly Extreme Value (EV) ones-, reveal as the most accurate technique to model market risks, hence preventing huge capital deficits under current measures; (b) the application of such methods could allow slight modifications to present mandate and simultaneously avoid sVaR or at least reduce its scope, thus mitigating the impact regarding the enhancement of capital base. Therefore, I suggest that the inclusion of EV in planned supervisory accords should reduce development costs and foster healthier financial structures.

Suggested Citation

  • Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.
    • Handle: RePEc:eee:finsta:v:8:y:2012:i:4:p:303-319
    DOI: 10.1016/j.jfs.2011.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1572308911000581
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jfs.2011.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    2. Thomas J. Linsmeier & Neil D. Pearson, 1996. "Risk Measurement: An Introduction to Value at Risk," Finance 9609004, University Library of Munich, Germany.
    3. H. F. Coronel-Brizio & A. R. Hernandez-Montoya, 2004. "On fitting the Pareto-Levy distribution to stock market index data: selecting a suitable cutoff value," Papers cond-mat/0411161, arXiv.org.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 53-89.
    6. Young-Hye Cho & Robert F. Engle, 1999. "Time-Varying Betas and Asymmetric Effect of News: Empirical Analysis of Blue Chip Stocks," NBER Working Papers 7330, National Bureau of Economic Research, Inc.
    7. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
    8. Andersen, Henrik, 2011. "Procyclical implications of Basel II: Can the cyclicality of capital requirements be contained?," Journal of Financial Stability, Elsevier, vol. 7(3), pages 138-154, August.
    9. Danielsson, Jon & Zigrand, Jean-Pierre, 2006. "On time-scaling of risk and the square-root-of-time rule," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2701-2713, October.
    10. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    11. Linsmeier, Thomas J. & Pearson, Neil D., 1996. "Risk measurement: an introduction to value at risk," ACE Reports 14796, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    12. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    13. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    14. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    15. Viviana Fernandez, 2003. "Extreme Value Theory and Value at Risk," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 18(1), pages 57-85, June.
    16. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    17. Bekiros, Stelios D. & Georgoutsos, Dimitris A., 2005. "Estimation of Value-at-Risk by extreme value and conventional methods: a comparative evaluation of their predictive performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 209-228, July.
    18. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    19. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 75, European Central Bank.
    20. Stolz, Stéphanie & Wedow, Michael, 2011. "Banks' regulatory capital buffer and the business cycle: Evidence for Germany," Journal of Financial Stability, Elsevier, vol. 7(2), pages 98-110, June.
    21. Chris Brooks & Gita Persand & Andrew D. Clare, 2000. "An EVT Approach to calculating Risk Capital Requirements," ICMA Centre Discussion Papers in Finance icma-dp2000-07, Henley Business School, University of Reading.
    22. Matthew Pritsker, 2001. "The hidden dangers of historical simulation," Finance and Economics Discussion Series 2001-27, Board of Governors of the Federal Reserve System (U.S.).
    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. Rossignolo, Adrián F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2013. "Market crises and Basel capital requirements: Could Basel III have been different? Evidence from Portugal, Ireland, Greece and Spain (PIGS)," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1323-1339.
    2. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    3. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Nieto, María Rosa, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Adrián F. Rossignolo & Víctor A. Álvarez, 2015. "Has the Basel Committee Got it Right? Evidence from Commodity Positions in Turmoil," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 10(1), pages 1-38, Enero-Jun.
    6. Adrián F. Rossignolo & Víctor A. Álvarez, 2015. "Has the Basel Committee Got it Right? Evidence from Commodity Positions in Turmoil," Remef - The Mexican Journal of Economics and Finance, Instituto Mexicano de Ejecutivos de Finanzas. Remef, March.
    7. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    8. Bakshi, Gurdip & Panayotov, George, 2010. "First-passage probability, jump models, and intra-horizon risk," Journal of Financial Economics, Elsevier, vol. 95(1), pages 20-40, January.
    9. Hartz, Christoph & Mittnik, Stefan & Paolella, Marc, 2006. "Accurate value-at-risk forecasting based on the normal-GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2295-2312, December.
    10. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    11. Adrián F. Rossignolo, 2021. "The New Standardised Approach as a Credible Fallback," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(TNEA), pages 1-27, Septiembr.
    12. 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.
    13. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    14. George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
    15. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.
    16. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    17. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    18. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    19. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
    20. Shige Peng & Shuzhen Yang & Jianfeng Yao, 2018. "Improving Value-at-Risk prediction under model uncertainty," Papers 1805.03890, arXiv.org, revised Jun 2020.

    More about this item

    Keywords

    Value-at-Risk; Extreme Value Theory; Emerging and Frontier markets; Capital Requirements; Stressed VaR;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

    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:eee:finsta:v:8:y:2012:i:4:p:303-319. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jfstabil .

    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.