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Global financial crisis and VaR performance in emerging markets: A case of EU candidate states - Turkey and Croatia

Author

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  • Sasa Zikovic

    (University of Rijeka, Faculty of Economics, Rijeka, Croatia)

  • Bora Aktan

    (Yasar University, Faculty of Economics and Administrative Sciences, Izmir, Turkey)

Abstract

We investigate the relative performance of a wide array of Value at Risk (VaR) models with the daily returns of Turkish (XU100) and Croatian (CROBEX) stock index prior to and during the ongoing financial crisis. In addition to widely used VaR models, we also study the behaviour of conditional and unconditional extreme value theory (EVT) and hybrid historical simulation (HHS) models to generate 95, 99 and 99.5% confidence level estimates. Results indicate that during the crisis period all tested VaR model except EVT and HHS models seriously underpredict the true level of risk, with EVT models doing so at a higher cost of capital com- pared to HHS model.

Suggested Citation

  • Sasa Zikovic & Bora Aktan, 2009. "Global financial crisis and VaR performance in emerging markets: A case of EU candidate states - Turkey and Croatia," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 27(1), pages 149-170.
    • Handle: RePEc:rfe:zbefri:v:27:y:2009:i:1:p:149-170
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    References listed on IDEAS

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    1. Ozun, Alper & Cifter, Atilla & Yilmazer, Sait, 2007. "Filtered Extreme Value Theory for Value-At-Risk Estimation," MPRA Paper 3302, University Library of Munich, Germany.
    2. Coronel-Brizio, H.F. & Hernández-Montoya, A.R., 2005. "On fitting the Pareto–Levy distribution to stock market index data: Selecting a suitable cutoff value," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 437-449.
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    Cited by:

    1. Nikola RADIVOJEVIĆ & Luka FILIPOVI & Тomislav D. BRZAKOVIĆ, 2020. "A New Semiparametric Mirrored Historical Simulation Value-At-Risk Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-21, March.
    2. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    3. repec:agr:journl:v:4(621):y:2019:i:4(621):p:201-218 is not listed on IDEAS
    4. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    5. Lidija Barjaktarović & Maja Paunović & Dejan Ječmenica, 2013. "Development of the Banking Sector in CEE Countries – Comparative Analysis," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 2(2), pages 93-114.
    6. Abad, Pilar & Benito, Sonia, 2013. "A detailed comparison of value at risk estimates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 258-276.
    7. Shcherba, Alexandr, 2012. "Market risk valuation modeling for the European countries at the financial crisis of 2008," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 20-35.
    8. Kakade, Kshitij & Jain, Ishan & Mishra, Aswini Kumar, 2022. "Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach," Resources Policy, Elsevier, vol. 78(C).
    9. Bucevska Vesna, 2013. "An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange," Business Systems Research, Sciendo, vol. 4(1), pages 49-64, March.
    10. Beata Zyznarska-Dworczak, 2018. "The Development Perspectives of Sustainable Management Accounting in Central and Eastern European Countries," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    11. Siva Kiran GUPTHA. K & Prabhakar RAO. R, 2019. "GARCH based VaR estimation: An empirical evidence from BRICS stock markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 201-218, Winter.
    12. Imed Gammoudi & Lotfi BelKacem & Mohamed El Ghourabi, 2014. "Value at Risk Estimation for Heavy Tailed Distributions," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 109-125.
    13. Goran Andjelic & Ivana Milosev & Vladimir Djakovic, 2010. "Extreme Value Theory In Emerging Markets," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 55(185), pages 63-106, April - J.
    14. Mirjana Miletić & Siniša Miletić, 2016. "Performance of VaR in Developed and CEE Countries during the Global Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 54-75, March.
    15. Julija Cerović & Vesna Karadžić, 2015. "Extreme Value Theory In Emerging Markets: Evidence From Montenegrin Stock Exchange," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 60(206), pages 87-116, July - Se.
    16. Cerović Julija & Lipovina-Božović Milena & Vujošević Saša, 2015. "A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro," Business Systems Research, Sciendo, vol. 6(1), pages 36-55, March.

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    More about this item

    Keywords

    financial crisis; emerging markets; Value at Risk; extreme value theory; hybrid historical simulation;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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