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The Warsaw Stock Exchange Index WIG: Modelling and Forecasting

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  • Piotr Wdowinski
  • Aneta Zglinska-Pietrzak

Abstract

In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock indexes (DAX and FTSE) on the Warsaw Stock Exchange index WIG within a framework of a GARCH model. By applying a procedure of checking predictive quality of econometric models as proposed by Fair and Shiller (1990), we have found that the NYSE market has relatively more power than European markets in explaining the WSE index WIG.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2005/wp-cesifo-2005-10/cesifo1_wp1570.pdf
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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1570.

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Date of creation: 2005
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Handle: RePEc:ces:ceswps:_1570

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Keywords: Warsaw Stock Exchange; stock index; GARCH model; forecasting;

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References

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  1. Monica Billio & Domenico Sartore & Carlo Toffano, 2000. "Combining forecasts: some results on exchange and interest rates," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 126-145.
  2. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  4. Bracker, Kevin & Koch, Paul D., 1999. "Economic determinants of the correlation structure across international equity markets," Journal of Economics and Business, Elsevier, vol. 51(6), pages 443-471.
  5. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
  6. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
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Cited by:
  1. Konrad, Kai A & Skaperdas, Stergios, 1999. "The Market for Protection and the Origin of the State," CEPR Discussion Papers 2173, C.E.P.R. Discussion Papers.

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