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Has the Basel Accord Improved Risk Management During the Global Financial Crisis?

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Abstract

The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. In this paper we define risk management in terms of choosing from a variety of risk models, and discuss the selection of optimal risk models. A new approach to model selection for predicting VaR is proposed, consisting of combining alternative risk models, and we compare conservative and aggressive strategies for choosing between VaR models. We then examine how different risk management strategies performed during the 2008-09 global financial crisis. These issues are illustrated using Standard and Poor’s 500 Composite Index.

Suggested Citation

  • Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez Amaral, 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Documentos de Trabajo del ICAE 2012-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Oct 2012.
  • Handle: RePEc:ucm:doicae:1226
    Note: For financial support, the first author wishes to thank the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science. The second and third authors acknowledge the financial support of the Ministerio de Ciencia y Tecnología and Comunidad de Madrid, Spain.
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    References listed on IDEAS

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    Cited by:

    1. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    2. Chia-Lin Chang & Allen, David & McAleer, Michael, 2013. "Recent developments in financial economics and econometrics: An overview," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 217-226.
    3. 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.
    4. Hu, Jin-Li & Yu, Hsueh-E, 2014. "Risk management in life insurance companies: Evidence from Taiwan," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 185-199.
    5. Chia-Lin Chang & Michael McAleer & Chien-Hsun Wang, 2017. "An Econometric Analysis of ETF and ETF Futures in Financial and Energy Markets Using Generated Regressors," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 6(1), pages 1-24, December.
    6. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    7. Chang, Chia-Lin & Jiménez-Martín, Juan-Ángel & Maasoumi, Esfandiar & Pérez-Amaral, Teodosio, 2015. "A stochastic dominance approach to financial risk management strategies," Journal of Econometrics, Elsevier, vol. 187(2), pages 472-485.
    8. Giulioni, Gianfranco, 2015. "Policy interest rate, loan portfolio management and bank liquidity," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 52-74.
    9. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
    10. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Measuring risks in the extreme tail: The extreme VaR and its confidence interval," Documents de travail du Centre d'Economie de la Sorbonne 16034rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jan 2017.
    11. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michel McAleer & Teodosio Pérez-Amaral, 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Tinbergen Institute Discussion Papers 15-133/III, Tinbergen Institute.
    12. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
    13. Hunzinger, Chadd B. & Labuschagne, Coenraad C.A., 2014. "The Cox, Ross and Rubinstein tree model which includes counterparty credit risk and funding costs," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 200-217.
    14. Feria-Domínguez, José Manuel & Jiménez-Rodríguez, Enrique & Sholarin, Ola, 2015. "Tackling the over-dispersion of operational risk: Implications on capital adequacy requirements," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 206-221.
    15. repec:eee:revfin:v:34:y:2017:i:c:p:86-98 is not listed on IDEAS
    16. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    17. Liow, Kim Hiang, 2015. "Volatility spillover dynamics and relationship across G7 financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 328-365.
    18. Dang-Nguyen, Stéphane & Le Caillec, Jean-Marc & Hillion, Alain, 2014. "The deterministic shift extension and the affine dynamic Nelson–Siegel model," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 402-417.

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    Keywords

    Value-at-Risk (VaR); daily capital charges; violation penalties; optimizing strategy; risk forecasts; aggressive or conservative risk management strategies; Basel Accord; global financial crisis.;

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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