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An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III

Author

Listed:
  • Katherine Uylangco

    (Newcastle Business School, University of Newcastle, Callaghan, NSW, Australia)

  • Siqiwen Li

    (College of Business, Law & Governance, James Cook University, Townsville, QLD, Australia
    Research Center of Catastrophe Risk Management, School of Finance, Yunnan University of Finance and Economics, Kunming, China)

Abstract
This study compares Value-at-Risk (VaR) measures for Australian banks over a period that includes the Global Financial Crisis (GFC) to determine whether the methodology and parameter selection are important for capital adequacy holdings that will ultimately support a bank in a crisis period. VaR methodology promoted under Basel II was largely criticised during the GFC for its failure to capture downside risk. However, results from this study indicate that 1-year parametric and historical models produce better measures of VaR than models with longer time frames. VaR estimates produced using Monte Carlo simulations show a high percentage of violations but with lower average magnitude of a violation when they occur. VaR estimates produced by the ARMA GARCH model also show a relatively high percentage of violations, however, the average magnitude of a violation is quite low. Our findings support the design of the revised Basel II VaR methodology which has also been adopted under Basel III.

Suggested Citation

  • Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
  • Handle: RePEc:sae:ausman:v:41:y:2016:i:4:p:699-718
    DOI: 10.1177/0312896214557837
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    References listed on IDEAS

    as
    1. Christophe Hurlin & Sessi Tokpavi, 2006. "Backtesting Value at Risk Accuracy : A New Simple Test," Post-Print halshs-00257520, HAL.
    2. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value‐at‐Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, June.
    3. Pesaran, Bahram & Pesaran, M. Hashem, 2010. "Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash," Economic Modelling, Elsevier, vol. 27(6), pages 1398-1416, November.
    4. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    5. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    6. Weng, Haijie & Trück, Stefan, 2011. "Style analysis and Value-at-Risk of Asia-focused hedge funds," Pacific-Basin Finance Journal, Elsevier, vol. 19(5), pages 491-510, November.
    7. Pérignon, Christophe & Deng, Zi Yin & Wang, Zhi Jun, 2008. "Do banks overstate their Value-at-Risk?," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 783-794, May.
    8. Kim, Young Shin & Rachev, Svetlozar T. & Bianchi, Michele Leonardo & Mitov, Ivan & Fabozzi, Frank J., 2011. "Time series analysis for financial market meltdowns," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1879-1891, August.
    9. Fatima Alali & Silvia Romero, 2013. "Characteristics of failed U.S. commercial banks: an exploratory study," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(4), pages 1149-1174, December.
    10. Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
    11. David E Allen & Robert Powell, 2012. "The fluctuating default risk of Australian banks," Australian Journal of Management, Australian School of Business, vol. 37(2), pages 297-325, August.
    12. Michael McAleer & Juan‐Ángel Jiménez‐Martín & Teodosio Pérez‐Amaral, 2013. "International Evidence on GFC‐Robust Forecasts for Risk Management under the Basel Accord," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 267-288, April.
    13. Pérignon, Christophe & Smith, Daniel R., 2010. "Diversification and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 55-66, January.
    14. 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.
    15. Yun, Jaeho & Moon, Hyejung, 2014. "Measuring systemic risk in the Korean banking sector via dynamic conditional correlation models," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 94-114.
    16. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    17. Pesaran, M.H., 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market," Cambridge Working Papers in Economics 1025, Faculty of Economics, University of Cambridge.
    18. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    19. Kerkhof, Jeroen & Melenberg, Bertrand & Schumacher, Hans, 2010. "Model risk and capital reserves," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 267-279, January.
    20. D. E. Allen & A. K. Singh & R. Powell, 2012. "A Gourmet's delight: CAViaR and the Australian stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1493-1498, October.
    21. David E. Allen & Robert Powell, 2009. "Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(3), pages 425-444, September.
    22. Kerkhof, Jeroen & Melenberg, Bertrand, 2004. "Backtesting for risk-based regulatory capital," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1845-1865, August.
    23. Alexander, Gordon J. & Baptista, Alexandre M., 2006. "Does the Basle Capital Accord reduce bank fragility? An assessment of the value-at-risk approach," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1631-1660, October.
    24. Xin Zhao & Carl Scarrott & Les Oxley & Marco Reale, 2010. "Extreme value modelling for forecasting market crisis impacts," Applied Financial Economics, Taylor & Francis Journals, vol. 20(1-2), pages 63-72.
    25. Wang, Jying-Nan & Yeh, Jin-Huei & Cheng, Nick Ying-Pin, 2011. "How accurate is the square-root-of-time rule in scaling tail risk: A global study," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1158-1169, May.
    26. Haq, Mamiza & Faff, Robert & Seth, Rama & Mohanty, Sunil, 2014. "Disciplinary tools and bank risk exposure," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 37-64.
    27. Boyle, Phelim P., 1977. "Options: A Monte Carlo approach," Journal of Financial Economics, Elsevier, vol. 4(3), pages 323-338, May.
    28. Gupta, Anurag & Liang, Bing, 2005. "Do hedge funds have enough capital? A value-at-risk approach," Journal of Financial Economics, Elsevier, vol. 77(1), pages 219-253, July.
    29. Vlaar, Peter J. G., 2000. "Value at risk models for Dutch bond portfolios," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1131-1154, July.
    30. Lucas, Andre, 2001. "Evaluating the Basle Guidelines for Backtesting Banks' Internal Risk Management Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 33(3), pages 826-846, August.
    31. Cuoco, Domenico & Liu, Hong, 2006. "An analysis of VaR-based capital requirements," Journal of Financial Intermediation, Elsevier, vol. 15(3), pages 362-394, July.
    32. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    Value-at-Risk (VaR); parametric VaR; Monte Carlo simulation; Basel Accords;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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