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Estimation of Value-at-Risk by extreme value and conventional methods: a comparative evaluation of their predictive performance

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  • Bekiros, Stelios D.
  • Georgoutsos, Dimitris A.

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  • Bekiros, Stelios D. & Georgoutsos, Dimitris A., 2005. "Estimation of Value-at-Risk by extreme value and conventional methods: a comparative evaluation of their predictive performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 209-228, July.
  • Handle: RePEc:eee:intfin:v:15:y:2005:i:3:p:209-228
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    1. Danielsson, Jon & Morimoto, Yuji, 2000. "Forecasting Extreme Financial Risk: A Critical Analysis of Practical Methods for the Japanese Market," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 25-48, December.
    2. 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.
    3. 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.
    4. 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.
    5. Tae-Hwy Lee & Yong Bao & Burak Saltoglu, 2006. "Evaluating predictive performance of value-at-risk models in emerging markets: a reality check," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 101-128.
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    Cited by:

    1. 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.
    2. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    3. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2014. "Energy portfolio risk management using time-varying extreme value copula methods," Economic Modelling, Elsevier, vol. 38(C), pages 470-485.
    4. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    5. Sonia Benito Muela & Mª Ángeles Navarro, 2018. "Assessing the importance of the choice threshold in quantifying market risk under the POT method (EVT)," Documentos de Trabajo del ICAE 2018-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    6. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    7. Sonia Benito & Carmen López-Martín & Mª Ángeles Navarro, 2023. "Assessing the importance of the choice threshold in quantifying market risk under the POT approach (EVT)," Risk Management, Palgrave Macmillan, vol. 25(1), pages 1-31, March.
    8. Shi Bo & Minheng Xiao, 2022. "Data-Driven Risk Measurement by SV-GARCH-EVT Model," Papers 2201.09434, arXiv.org, revised Jul 2024.
    9. Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.
    10. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    11. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    12. Stelios Bekiros & Nikolaos Loukeris & Iordanis Eleftheriadis & Christos Avdoulas, 2019. "Tail-Related Risk Measurement and Forecasting in Equity Markets," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 783-816, February.
    13. Muteba Mwamba, John W. & Hammoudeh, Shawkat & Gupta, Rangan, 2017. "Financial tail risks in conventional and Islamic stock markets: A comparative analysis," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 60-82.
    14. Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
    15. George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
    16. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    17. Chuangchid, Kantaporn & Sriboonchitta, Songsak & Rahman, Sanzidur & Wiboonpongse, Aree, 2013. "Predicting Malaysian palm oil price using Extreme Value Theory," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 2(2), pages 1-9, January.
    18. Georgios Fatouros & Georgios Makridis & Dimitrios Kotios & John Soldatos & Michael Filippakis & Dimosthenis Kyriazis, 2023. "DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks," Digital Finance, Springer, vol. 5(1), pages 29-56, March.
    19. Muteba Mwamba, John & Mhlanga, Isaah, 2013. "Extreme conditional value at risk: a coherent scenario for risk management," MPRA Paper 64387, University Library of Munich, Germany.
    20. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    21. Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.

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