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Modelling of Stock Returns Time-Series
[Modelování časových řad akciových výnosů]

Author

Listed:
  • Jiří Trešl
  • Dagmar Blatná

Abstract

In the study submitted, selected methods of financial time-series analysis are applied to daily returns of the most liquid stocks at Czech capital market. In most cases, symmetric GARCH(1,1) models are quite satisfactory. Further, ARFIMA models enabling to catch "long memory" of underlying processes are suitable for the modelling both absolute values of returns and their volatility. Alternative posibility is to employ bilinear models, which prove to be suitable namely for returns. Hurst exponents computed signalize some tendency to cycles creation in some cases (ČEZ, Unipetrol).

Suggested Citation

  • Jiří Trešl & Dagmar Blatná, 2007. "Modelling of Stock Returns Time-Series [Modelování časových řad akciových výnosů]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2007(1), pages 114-120.
    • Handle: RePEc:prg:jnlaop:v:2007:y:2007:i:1:id:44:p:114-120
    DOI: 10.18267/j.aop.44
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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    More about this item

    Keywords

    financial time-series; stock returns; GARCH models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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