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It Pays to Violate: How Effective are the Basel Accord Penalties?

Author

Listed:
  • Bernardo da Veiga

    (School of Economics and Finance, Curtin University of Technology)

  • Felix Chan

    (School of Economics and Finance, Curtin University of Technology)

  • 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)

Abstract

The internal models amendment to the Basel Accord allows banks to use internal models to forecast Value-at-Risk (VaR) thresholds, which are used to calculate the required capital that banks must hold in reserve as a protection against negative changes in the value of their trading portfolios. As capital reserves lead to an opportunity cost to banks, it is likely that banks could be tempted to use models that underpredict risk, and hence lead to low capital charges. In order to avoid this problem the Basel Accord introduced a backtesting procedure, whereby banks using models that led to excessive violations are penalised through higher capital charges. This paper investigates the performance of five popular volatility models that can be used to forecast VaR thresholds under a variety of distributional assumptions. The results suggest that, within the current constraints and the penalty structure of the Basel Accord, the lowest capital charges arise when using models that lead to excessive violations, thereby suggesting the current penalty structure is not severe enough to control risk management. In addition, an alternative penalty structure is suggested to be more effective in aligning the interests of banks and regulators.

Suggested Citation

  • Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CARF F-Series CARF-F-186, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  • Handle: RePEc:cfi:fseres:cf186
    as

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    File URL: http://www.carf.e.u-tokyo.ac.jp/pdf/workingpaper/fseries/192.pdf
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    References listed on IDEAS

    as
    1. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Pérez-Amaral, 0000. "Has the Basel II Accord Encouraged Risk Management during the 2008-09 Financial Crisis?," Tinbergen Institute Discussion Papers 09-039/4, Tinbergen Institute.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.
    8. 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.
    9. 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.
    10. 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.
    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.
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    Cited by:

    1. David Allen & Robert Faff, 2012. "The Global Financial Crisis: some attributes and responses," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 52(1), pages 1-7, March.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • 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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