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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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Bibliographic Info

Article provided by University of Economics, Prague in its journal Prague Economic Papers.

Volume (Year): 2004 (2004)
Issue (Month): 1 ()
Pages: 26-39

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Handle: RePEc:prg:jnlpep:v:2004:y:2004:i:1:id:229:p:26-39

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Related research

Keywords: market efficiency; leptokurtosis; GARCH; conditional heteroskedasticity;

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References

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  1. Andrew W. Lo & Craig A. MacKinlay, . "An Econometric Analysis of Nonsyschronous-Trading," Rodney L. White Center for Financial Research Working Papers 19-89, Wharton School Rodney L. White Center for Financial Research.
  2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  3. 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.
  4. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
  5. 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 542-47, August.
  6. 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.
  7. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
  8. Andrew W. Lo & A. Craig MacKinlay, 1987. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
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