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Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?

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  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

  • Juan-Angel Jimenez-Martin

    (Department of Quantitative Economics, Complutense University of Madrid)

  • Teodosio Perez-Amaral

    (Department of Quantitative Economics, Complutense University of Madrid)

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 sensibly from a variety of risk models, discuss the selection of optimal risk models, consider combining alternative risk models, discuss the choice between a conservative and aggressive risk management strategy, and evaluate the effects of the Basel II Accord on risk management. We also examine how risk management strategies performed during the 2008-09 financial crisis, evaluate how the financial crisis affected risk management practices, forecasting VaR and daily capital charges, and discuss alternative policy recommendations, especially in light of the financial crisis. These issues are illustrated using Standard and Poor's 500 Index, with an emphasis on how risk management practices were monitored and encouraged by the Basel II Accord regulations during the financial crisis.

Suggested Citation

  • Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-643, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2009cf643
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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf643.pdf
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    References listed on IDEAS

    as
    1. Massimiliano Caporin & Michael McAleer, 2010. "The Ten Commandments For Managing Investments," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 196-200, February.
    2. Terui, Nobuhiko & van Dijk, Herman K., 2002. "Combined forecasts from linear and nonlinear time series models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 421-438.
    3. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(02), pages 280-310, April.
    4. Michael McAleer & Les Oxley, 2005. "The Ten Commandments for Academics," Journal of Economic Surveys, Wiley Blackwell, vol. 19(5), pages 823-826, December.
    5. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    6. Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2009. "The Ten Commandments For Managing Value At Risk Under The Basel Ii Accord," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 850-855, December.
    7. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(03), pages 722-729, June.
    8. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    9. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    10. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CARF F-Series CARF-F-156, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    12. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2008. "A decision rule to minimize daily capital charges in forecasting value-at-risk," Econometric Institute Research Papers EI 2008-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    14. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    15. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    16. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    17. Michael McAleer, 2009. "The Ten Commandments For Optimizing Value-At-Risk And Daily Capital Charges," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 831-849, December.
    18. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
    19. 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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    Citations

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    Cited by:

    1. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    2. McAleer, Michael & Jimenez-Martin, Juan-Angel & Perez-Amaral, Teodosio, 2013. "GFC-robust risk management strategies under the Basel Accord," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 97-111.
    3. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    4. Casarin, Roberto & Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio, 2013. "Risk management of risk under the Basel Accord: A Bayesian approach to forecasting Value-at-Risk of VIX futures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 183-204.
    5. Chia-lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "Risk management of risk under the Basel Accord: forecasting value-at-risk of VIX futures," Managerial Finance, Emerald Group Publishing, vol. 37(11), pages 1088-1106, September.
    6. 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.
    7. 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.
    8. Chia-Lin Chang & Michael Mcaleer, 2009. "Daily Tourist Arrivals, Exchange Rates and Voatility for Korea and Taiwan," Korean Economic Review, Korean Economic Association, vol. 25, pages 241-267.
    9. 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.
    10. Michael McAleer, 2009. "The Ten Commandments For Optimizing Value-At-Risk And Daily Capital Charges," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 831-849, December.
    11. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & McAleer, Michael & Amaral, Teodosio Perez, 2013. "The rise and fall of S&P500 variance futures," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 151-167.
    12. Costa Cabral, Nazare, 2010. "Breve guia temático e bibliográfico sobre o estudo da actual crise financeira e económica
      [Short thematic guide to the study of current financial and economic crisis]
      ," MPRA Paper 20743, University Library of Munich, Germany.
    13. repec:syb:wpbsba:03/2011 is not listed on IDEAS
    14. da Veiga, B. & Chan, F. & McAleer, M.J., 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," Econometric Institute Research Papers EI 2009-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2009. "Optimal Risk Management Before, During and After the 2008-09 Financial Crisis," Documentos de Trabajo del ICAE 2009-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    16. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "What Happened to Risk Management During the 2008-09 Financial Crisis?," CARF F-Series CARF-F-155, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    17. Mateusz Buczyński & Marcin Chlebus, 2017. "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(," Working Papers 2017-29, Faculty of Economic Sciences, University of Warsaw.

    More about this item

    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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