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Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo

Author

Listed:
  • Mohamed Ali Houfi

    (Sciences Juridiques, Economiques et de Gestion de Jendouba, Tunisie)

  • Ghassen El Montasser

    (Ecole Supérieure de Commerce de Tunis, Tunisie)

Abstract

Dans ce papier, nous avons étudié l’impact de la correction des points aberrants sur les tests de normalité et de linéarité. A cet égard, la double correction en niveau et en rendement des séries journalières des cours des titres composants l’indice de Nikkei 225 a généré des améliorations plus pertinentes de ces tests. En tenant compte de la non linéarité des séries corrigées selon les trois approches (correction en niveau, correction en rendement et double correction en niveau et en rendement), la spécification FIGARCH du processus de volatilité engendre des meilleurs effets sur les tests de normalité et de linéarité ainsi qu’elle améliore la qualité de prévision des séries considérées.

Suggested Citation

  • Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
  • Handle: RePEc:rej:journl:v:13:y:2010:i:36:p:15-51
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    References listed on IDEAS

    as
    1. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.
    2. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun.
    3. Van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 217-235, April.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Bollerslev, Tim & Engle, Robert F, 1993. "Common Persistence in Conditional Variances," Econometrica, Econometric Society, vol. 61(1), pages 167-186, January.
    6. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-235, April.
    7. 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.
    8. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    9. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    10. Franses, Philip Hans & Ghijsels, Hendrik, 1999. "Additive outliers, GARCH and forecasting volatility," International Journal of Forecasting, Elsevier, vol. 15(1), pages 1-9, February.
    11. Balke, Nathan S. & Fomby, Thomas B., 1991. "Shifting trends, segmented trends, and infrequent permanent shocks," Journal of Monetary Economics, Elsevier, vol. 28(1), pages 61-85, August.
    12. Nelson, Daniel B., 1990. "Stationarity and Persistence in the GARCH(1,1) Model," Econometric Theory, Cambridge University Press, vol. 6(3), pages 318-334, September.
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    More about this item

    Keywords

    outliers; coefficients de normalité; volatilité; non linéarité; FIGARCH; out of sample;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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