IDEAS home Printed from https://ideas.repec.org/a/rfe/zbefri/v27y2009i1p149-170.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.efri.uniri.hr/sites/efri.hr/files/cr-collections/2/aktan-2009-1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Ozun, Alper & Cifter, Atilla & Yilmazer, Sait, 2007. "Filtered Extreme Value Theory for Value-At-Risk Estimation," MPRA Paper 3302, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    3. 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.
    4. 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.
    5. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. repec:agr:journl:v:4(621):y:2019:i:4(621):p:201-218 is not listed on IDEAS
    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 / Editura Economica, 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, vol. 2(2), pages 1-15, May.
    2. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
    3. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    4. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
    5. Amira Akl Ahmed & Doaa Akl Ahmed, 2016. "Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange," Working Papers 1028, Economic Research Forum, revised Jul 2016.
    6. 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.
    7. Federico Botta & Helen Susannah Moat & H Eugene Stanley & Tobias Preis, 2015. "Quantifying Stock Return Distributions in Financial Markets," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-10, September.
    8. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    9. Rodríguez-Martínez, C.M. & Coronel-Brizio, H.F. & Hernández-Montoya, A.R., 2021. "A multi-scale symmetry analysis of uninterrupted trends returns in daily financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    10. Shin, Minseok & Kim, Donggyu & Fan, Jianqing, 2023. "Adaptive robust large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 237(1).
    11. Degiannakis, Stavros & Floros, Christos & Livada, Alexandra, 2012. "Evaluating Value-at-Risk Models before and after the Financial Crisis of 2008: International Evidence," MPRA Paper 80463, University Library of Munich, Germany.
    12. Laura Garcia-Jorcano & Alfonso Novales, 2020. "A dominance approach for comparing the performance of VaR forecasting models," Computational Statistics, Springer, vol. 35(3), pages 1411-1448, September.
    13. Coronel-Brizio, H.F. & Hernández-Montoya, A.R., 2010. "The Anderson–Darling test of fit for the power-law distribution from left-censored samples," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3508-3515.
    14. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    15. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
    16. Giuricich, Mario Nicoló & Burnecki, Krzysztof, 2019. "Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 498-513.
    17. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman, 2018. "A robust semi-parametric approach for measuring income inequality in Malaysia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1-13.
    18. C. M. Rodr'iguez-Mart'inez & H. F. Coronel-Brizio & A. R. Hern'andez-Montoya, 2019. "A multi-scale symmetry analysis of uninterrupted trends returns of daily financial indices," Papers 1908.11204, arXiv.org.
    19. Fujimoto, Shouji & Ishikawa, Atushi & Mizuno, Takayuki & Watanabe, Tsutomu, 2011. "A new method for measuring tail exponents of firm size distributions," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-20.
    20. Sasa Zikovic, 2011. "Measuring risk of crude oil at extreme quantiles," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 29(1), pages 9-31.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rfe:zbefri:v:27:y:2009:i:1:p:149-170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Danijela Ujcic (email available below). General contact details of provider: https://edirc.repec.org/data/efrijhr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.