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GFC-Robust Risk Management Strategies under the Basel Accord

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Abstract
A risk management strategy is proposed as being robust to the Global Financial Crisis (GFC) by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast is based on the median of the point VaR forecasts of a set of conditional volatility models. This risk management strategy is GFC-robust in the sense that maintaining the same risk management strategies before, during and after a financial crisis would lead to comparatively low daily capital charges and violation penalties. The new method is illustrated by using the S&P500 index before, during and after the 2008-09 global financial crisis. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria. The median VaR risk management strategy is GFC-robust as it provides stable results across different periods relative to other VaR forecasting models. The new strategy based on combined forecasts of single models is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.

Suggested Citation

  • Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez-Amaral, 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Working Papers in Economics 10/63, University of Canterbury, Department of Economics and Finance.
    • Handle: RePEc:cbt:econwp:10/63
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    File URL: https://repec.canterbury.ac.nz/cbt/econwp/1063.pdf
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Chia-Lin Chang & David E. Allen & Michael McAleer & Ju-Ting Tang & Teodosio Pérez Amaral, 2013. "Risk Modelling and Management: An Overview," Documentos de Trabajo del ICAE 2013-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    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. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.
    4. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019. "Choosing expected shortfall over VaR in Basel III using stochastic dominance," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 95-113.
    5. Xiaochun Liu, 2017. "An integrated macro‐financial risk‐based approach to the stressed capital requirement," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 86-98, September.
    6. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    7. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    8. 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.
    9. Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015. "Forecasting Value-at-Risk using block structure multivariate stochastic volatility models," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
    10. McAleer, Michael & Jimenez-Martin, Juan-Angel & Perez-Amaral, Teodosio, 2013. "Has the Basel Accord improved risk management during the global financial crisis?," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 250-265.
    11. 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.
    12. Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014. "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 59-85.
    13. 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.
    14. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
    15. Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.
    16. Bouwman, Kees & Buis, Boyd & Pieterse-Bloem, Mary & Tham, Wing Wah, 2015. "A practical approach to constructing price-based funding liquidity factors," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 90-97.
    17. Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.
    18. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
    19. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2015. "Preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the Global Financial Crisis," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 204-216.
    20. Noorshanaaz Khodabaccus & Aslam A. E. F. Saib, 2024. "volatilityforecastingpackage: A Financial Volatility Package in Mathematica," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2307-2324, June.
    21. Liao, Shuyu & Sojli, Elvira & Tham, Wing Wah, 2015. "Managing systemic risk in The Netherlands," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 231-245.
    22. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.

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    More about this item

    Keywords

    Value-at-Risk (VaR); daily capital charges; robust forecasts; violation penalties; optimizing strategy; aggressive risk management strategy; conservative risk management strategy; Basel II Accord; global financial crisis;
    All these keywords.

    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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