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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.

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  • Miloslav Vošvrda & Filip Žikeš, 2004. "An Application of the Garch-t Model on Central European Stock Returns," Prague Economic Papers, Prague University of Economics and Business, vol. 2004(1), pages 26-39.
    • Handle: RePEc:prg:jnlpep:v:2004:y:2004:i:1:id:229:p:26-39
    DOI: 10.18267/j.pep.229
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    Cited by:

    1. Krzysztof DRACHAL, 2017. "Volatility Clustering, Leverage Effects and Risk-Return Tradeoff in the Selected Stock Markets in the CEE Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-53, September.

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    More about this item

    Keywords

    conditional heteroskedasticity; GARCH; leptokurtosis; market efficiency;
    All these keywords.

    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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