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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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    7. 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.
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    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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