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Comparison of Forecasting Volatility in the Czech Republic Stock Market

Author

Listed:
  • Eleftherios I. Thalassinos
  • Erginbay Ugurlu
  • Yusuf Muratoglu

Abstract

The aim of this paper is to examine different GARCH models with three different distributions in order to compare their forecasting power in terms of volatility existing in the returns of the Czech Stock Market and more specific in the PX index, for the period 08.01.2001-20.07.2012. We have employed GARCH, GJR-GARCH and EGARCH models against normal, student-t and generalized error distributions. Then, we have forecasted stock market volatility for the Czech Republic by its returns using the same models, GARCH, GJR-GARCH and EGARCH comparing their forecasting performance. The results show that return volatility can be characterized by significant persistence and asymmetric effects. We have estimated the corresponding variances for all models for the full sample period using static forecasts. After comparing the forecasting performance of all nine models it was found that the EGARCH model has the best forecasting performance compared to others. JEL classification: G15, G17

Suggested Citation

  • Eleftherios I. Thalassinos & Erginbay Ugurlu & Yusuf Muratoglu, 2015. "Comparison of Forecasting Volatility in the Czech Republic Stock Market," Applied Economics and Finance, Redfame publishing, vol. 2(1), pages 11-18, February.
  • Handle: RePEc:rfa:aefjnl:v:2:y:2015:i:1:p:11-18
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    Cited by:

    1. Lukasz Zieba, 2021. "Some Selected Determinants of Stock Exchange Development: Evidence from Greece," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 4), pages 260-268.
    2. Erginbay UGURLU, 2014. "Forecasting Volatility: Evidence from the Bucharest Stock Exchange," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 1(1), pages 302-310, December.
    3. Alexander Mikhailovich Batkovskiy & Viktor Antonovich Nesterov & Olga Olegovna Reshetova & Elena Georgievna Semenova & Alena Vladimirovna Fomina, 2017. "Dynamic Model of Optimal Production Control in a Hysteretic Behaviour of Economic Agents," European Research Studies Journal, European Research Studies Journal, vol. 0(2A), pages 355-379.
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    7. Ali Fayyaz Munir & Shahrin Saaid Shaharuddin & Mohd Edil Abd. Sukor, 2020. "Long-Term, Short-Term and Time-Varying Profitability of Reversals: The Role of Market State and Volatility," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 501-520.
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    16. Dr Ireneusz Zuchowski, 2015. "Management Styles of Polish Managers," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 38-53.
    17. Natalya Aleksandrovna Rubtsova & Anna Vitalievna Baychik & Sergey Borisovich Nikonov & Natalia Vladimirovna Bakirova & Tatiana Valerievna Belenkova, 2017. "Structural Models of the Consumer Goods Industry in China, Turkey and Italy," European Research Studies Journal, European Research Studies Journal, vol. 0(4A), pages 632-650.
    18. Kirsneh Alemu Kebede, 2024. "The Effect of Availability of Foreign Exchange and Devaluation of BIRR on the Performance of Companies in Ethiopia (Instance of Sample Company)," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 99-117.

    More about this item

    Keywords

    GARCH models; stock market volatility; forecasting performance;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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