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An Application of the Garch-t Model on Central European Stock Returns

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  • Miloslav Vošvrda
  • Filip Žikeš

Abstract

The purpose of this paper is to investigate the time-series and distributional properties of Central European stock returns. We test the random walk hypothesis and then consider an alternative to random walk - the ARIMA model for stock prices. The behavior of volatility of returns over time is studied using the GARCH-t model which also allows us to learn more about the distribution properties of stock returns. We employ the BDS test to assess the ability of the estimated GARCH-t model to capture all nonlinearities in stock returns. Our empirical findings reveal that the Czech and Hungarian stock market indices are predictable from the time series of historical prices, whereas that of Poland is not. The returns on all three indices are conditionally heteroskedastic and non-normal. The estimated number of degrees of freedom ranges from 18 to 4.

Suggested Citation

  • Miloslav Vošvrda & Filip Žikeš, 2004. "An Application of the Garch-t Model on Central European Stock Returns," Prague Economic Papers, University of Economics, Prague, vol. 2004(1), pages 26-39.
  • Handle: RePEc:prg:jnlpep:v:2004:y:2004:i:1:id:229:p:26-39
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    References listed on IDEAS

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    1. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    2. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    3. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    4. Connolly, Robert A., 1989. "An Examination of the Robustness of the Weekend Effect," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(02), pages 133-169, June.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    7. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    8. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    9. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78 World Scientific Publishing Co. Pte. Ltd..
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    1. repec:rjr:romjef:v::y:2017:i:3:p:37-53 is not listed on IDEAS

    More about this item

    Keywords

    conditional heteroskedasticity; GARCH; leptokurtosis; market efficiency;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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