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Misspecification Testing for the Conditional Distribution Model in GARCH-Type Processes

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  • Matteo Grigoletto
  • Corrado Provasi
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    Abstract

    In this article, we study goodness of fit tests for some distributions of the innovations which are usually adopted to explain the behavior of financial time series. Inference is developed in the context of GARCH-type models. Functional bootstrap tests are employed, assuming that the conditional means and variances of the model are correctly specified. The performances of the functional tests are assessed with a Monte Carlo experiment, based on some of the most common distributions adopted in the financial framework. The results of an application to the series of squared residuals from a PARCH(1,1) model fitted to a series of foreign exchange rates returns are also shown.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/07474930802388033
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    Bibliographic Info

    Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

    Volume (Year): 28 (2009)
    Issue (Month): 1-3 ()
    Pages: 209-224

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    Handle: RePEc:taf:emetrv:v:28:y:2009:i:1-3:p:209-224

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    Related research

    Keywords: Bootstrap; Functional tests; GARCH model; Goodness of fit;

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