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A Functional Limit Theorem for weakly Dependent Processes and its Applications

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  • Jean-Marc Bardet

    (Crest)

  • Paul Doukhan

    (Crest)

  • José Rafael Leon_

    (Crest)

Abstract

We prove a general functional central limit theorem for weak dependent time series. Those probabilisticresults are for a large variety of models. For instance, ARCH(1) and bilinear processes, andtwo sided linear, bilinear and ARCH(1) processes.

Suggested Citation

  • Jean-Marc Bardet & Paul Doukhan & José Rafael Leon_, 2005. "A Functional Limit Theorem for weakly Dependent Processes and its Applications," Working Papers 2005-45, Center for Research in Economics and Statistics.
  • Handle: RePEc:crs:wpaper:2005-45
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    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Giraitis, Liudas & Surgailis, Donatas, 0. "ARCH-type bilinear models with double long memory," Stochastic Processes and their Applications, Elsevier, vol. 100(1-2), pages 275-300, July.
    3. Nze, Patrick Ango & Doukhan, Paul, 2004. "Weak Dependence: Models And Applications To Econometrics," Econometric Theory, Cambridge University Press, vol. 20(6), pages 995-1045, December.
    4. Paul Doukhan & Gabriel Lang, 2002. "Rates in the Empirical Central Limit Theorem for Stationary Weakly Dependent Random Fields," Statistical Inference for Stochastic Processes, Springer, vol. 5(2), pages 199-228, May.
    5. Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

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