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Modelling And Forecasting The Volatility Of The Portuguese Stock Index Psi-20

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Author Info
Jorge Caiado () (Escola Superior de Ciências Empresariais -Instituto Politécnico de Setúbal - and CEMAPRE - ISEG-UTL)

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Abstract

The volatility clustering often seen in financial data has increased the interest of researchers in applying good models to measure and forecast stock returns. This paper aims to model the volatility for daily and weekly returns of the Portuguese Stock Index PSI-20. By using simple GARCH, GARCH-M, Exponential GARCH (EGARCH) and Threshold ARCH (TARCH) models, we find support that there are significant asymmetric shocks to volatility in the daily stock returns, but not in the weekly stock returns. We also find that some weekly returns time series properties are substantially different from properties of daily returns, and the persistence in conditional volatility is different for some of the sub-periods referred. Finally, we compare the forecasting performance of the various volatility models in the sample periods before and after the terrorist attack on September 11, 2001.

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Publisher Info
Article provided by ISEG, Technical University of Lisbon in its journal Portuguese Journal of Management Studies.

Volume (Year): IX (2004)
Issue (Month): 1 ()
Pages: 3-21
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Handle: RePEc:pjm:journl:v:ix:y:2004:i:1:p:3-21

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Related research
Keywords: EGARCH; forecasting; GARCH; GARCH-M; leverage effect; PSI-20 index; TARCH; volatility.;

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References listed on IDEAS
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    Other versions:
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    Other versions:
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  13. Tim Bollerslev & Jeffrey Wooldridge, 1992. "Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances," Econometric Reviews, Taylor and Francis Journals, vol. 11(2), pages 143-172. [Downloadable!] (restricted)
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