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Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region

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  • Chebbi, Ali
  • Hedhli, Amel
Abstract
The aim of this study is twofold. First, it aims to show how to overcome some of the shortcomings of the standard risk measurement methods using value-at-risk (VaR) in the context of extreme events and propose an alternative empirical method. Second, it aims to fill the research gap in analysis of risk in the Middle East and North Africa (MENA) region. In this regard, for six daily stock indices in the MENA region, from January 3, 2005 to December 31, 2014, we employ a vine copula-based generalized autoregressive conditional heteroskedastic (GARCH) method and the extreme value theory (EVT) to model the dependence between the marginal distributions of returns and forecast the VaR. Based on backtesting, we assess the efficiency of the standard risk measurement models from the following families—the exponentially weighted moving average, the historical simulation, and the GARCH. By implementing the GARCH-EVT-C-vine method in the MENA region, we find that, empirically, standard methods overestimate (underestimate) the violation ratio, implying an underestimation (overestimation) of the risk, and therefore a misallocation of the capital covering the risk. The method also provides better VaR estimates for the MENA stock markets than that of the standard methods. We also verify that the greater the openness of the capital accounts and the flexibility of the exchange rate regimes, the greater will be the conditional dependence of the MENA countries on the developed markets. Finally, the empirical method we propose has an important implication for the MENA countries in that it can be adopted by these countries to forecast VaR effectively.

Suggested Citation

  • Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.
    • Handle: RePEc:eee:quaeco:v:84:y:2022:i:c:p:430-445
    DOI: 10.1016/j.qref.2020.09.005
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    as
    1. Federico Pasquale Cortese, 2019. "Tail Dependence in Financial Markets: A Dynamic Copula Approach," Risks, MDPI, vol. 7(4), pages 1-14, November.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Belkhir, Mohamed & Boubakri, Narjess & Grira, Jocelyn, 2017. "Political risk and the cost of capital in the MENA region," Emerging Markets Review, Elsevier, vol. 33(C), pages 155-172.
    5. Gaysset, Isabelle & Lagoarde-Segot, Thomas & Neaime, Simon, 2019. "Twin deficits and fiscal spillovers in the EMU's periphery. A Keynesian perspective," Economic Modelling, Elsevier, vol. 76(C), pages 101-116.
    6. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    7. Barro, Robert J & Mankiw, N Gregory & Sala-i-Martin, Xavier, 1995. "Capital Mobility in Neoclassical Models of Growth," American Economic Review, American Economic Association, vol. 85(1), pages 103-115, March.
    8. 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.).
    9. Mandelbrot, Benoit B, 1971. "When Can Price Be Arbitraged Efficiently? A Limit to the Validity of the Random Walk and Martingale Models," The Review of Economics and Statistics, MIT Press, vol. 53(3), pages 225-236, August.
    10. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 773-816.
    11. Assaf, A., 2009. "Extreme observations and risk assessment in the equity markets of MENA region: Tail measures and Value-at-Risk," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 109-116, June.
    12. Umberto Cherubini & Elisa Luciano, 2001. "Value-at-risk Trade-off and Capital Allocation with Copulas," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 235-256, July.
    13. Neaime, Simon, 2012. "The global financial crisis, financial linkages and correlations in returns and volatilities in emerging MENA stock markets," Emerging Markets Review, Elsevier, vol. 13(3), pages 268-282.
    14. Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
    15. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    16. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    17. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
    18. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    19. James L. Butkiewicz & Halit Yanikkaya, 2008. "Capital Account Openness, International Trade, and Economic Growth: A Cross-Country Empirical Investigation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(2), pages 15-38, March.
    20. Roberto Rigobón & Kristin Forbes, 2001. "Contagion in Latin America: Definitions, Measurement, and Policy Implications," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 1-46, January.
    21. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    22. Bali, Turan G. & Neftci, Salih N., 2003. "Disturbing extremal behavior of spot rate dynamics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 455-477, September.
    23. Rene M. Stulz, 1999. "Globalization of Equity Markets and the Cost of Capital," NBER Working Papers 7021, National Bureau of Economic Research, Inc.
    24. Ali Chebbi & Raoudha Louafi & Amel Hedhli, 2014. "Financial fluctuations in the Tunisian repressed market context: a Markov-switching-GARCH approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 7(2), pages 284-302, September.
    25. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    26. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    27. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
    28. McMillan, David G. & Kambouroudis, Dimos, 2009. "Are RiskMetrics forecasts good enough? Evidence from 31 stock markets," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 117-124, June.
    29. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    30. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    31. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    32. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    33. Guyot, Alexis & Lagoarde-Segot, Thomas & Neaime, Simon, 2014. "Foreign shocks and international cost of equity destabilization. Evidence from the MENA region," Emerging Markets Review, Elsevier, vol. 18(C), pages 101-122.
    34. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    35. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
    36. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Documents de travail du Centre d'Economie de la Sorbonne 10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    37. Philippe Jorion, 2000. "Risk management lessons from Long‐Term Capital Management," European Financial Management, European Financial Management Association, vol. 6(3), pages 277-300, September.
    38. Neaime, Simon, 2016. "Financial crises and contagion vulnerability of MENA stock markets," Emerging Markets Review, Elsevier, vol. 27(C), pages 14-35.
    39. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    40. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    41. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    42. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    43. Turan G. Bali, 2003. "An Extreme Value Approach to Estimating Volatility and Value at Risk," The Journal of Business, University of Chicago Press, vol. 76(1), pages 83-108, January.
    44. Collins, Daryl & Abrahamson, Mark, 2006. "Measuring the cost of equity in African financial markets," Emerging Markets Review, Elsevier, vol. 7(1), pages 67-81, March.
    45. Mark Britten-Jones & Stephen M. Schaefer, 1999. "Non-Linear Value-at-Risk," Review of Finance, European Finance Association, vol. 2(2), pages 161-187.
    46. Giovanni Barone‐Adesi & Kostas Giannopoulos & Les Vosper, 1999. "VaR without correlations for portfolios of derivative securities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(5), pages 583-602, August.
    47. Thomas Lagoarde-Segot & Brian M. Lucey, 2006. "Equity Markets and Economic Development: What Do We Know," The Institute for International Integration Studies Discussion Paper Series iiisdp182, IIIS.
    48. Fernandez, Viviana, 2005. "Risk management under extreme events," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 113-148.
    49. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    50. Paul Embrechts & Sidney Resnick & Gennady Samorodnitsky, 1999. "Extreme Value Theory as a Risk Management Tool," North American Actuarial Journal, Taylor & Francis Journals, vol. 3(2), pages 30-41.
    51. Clarke, Kevin A., 2007. "A Simple Distribution-Free Test for Nonnested Model Selection," Political Analysis, Cambridge University Press, vol. 15(3), pages 347-363, July.
    52. Aktham I. Maghyereh & Haitham A. Al-Zoubi, 2006. "Value-at-risk under extreme values: the relative performance in MENA emerging stock markets," International Journal of Managerial Finance, Emerald Group Publishing, vol. 2(2), pages 154-172, July.
    53. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    54. Manner, H., 2007. "Estimation and model selection of copulas with an application to exchange rates," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    55. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Post-Print halshs-00492124, HAL.
    56. Giannopoulos, Kostas & Tunaru, Radu, 2005. "Coherent risk measures under filtered historical simulation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 979-996, April.
    57. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    58. Chun-Pin Hsu & Chin-Wen Huang & Wan-Jiun Chiou, 2012. "Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets," Review of Quantitative Finance and Accounting, Springer, vol. 39(4), pages 447-468, November.
    59. Koutmos, Gregory, 1998. "Asymmetries in the Conditional Mean and the Conditional Variance: Evidence From Nine Stock Markets," Journal of Economics and Business, Elsevier, vol. 50(3), pages 277-290, May.
    60. Patro, Dilip K. & Wald, John K., 2005. "Firm characteristics and the impact of emerging market liberalizations," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1671-1695, July.
    61. Calice, Pietro, 2014. "Predicting bank insolvency in the Middle East and North Africa," Policy Research Working Paper Series 6969, The World Bank.
    62. 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

    Extreme value theory; Vine copula; Value-at-risk; Backtesting; Stock indices; Violation ratio; MENA markets;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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