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Fourier--type estimation of the power garch model with stable--paretian innovations

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  • Francq, Christian
  • Meintanis, Simos

Abstract

We consider estimation for general power GARCH models under stable--Paretian innovations. Exploiting the simple structure of the conditional characteristic function of the observations driven by these models we propose minimum distance estimation based on the empirical characteristic function of corresponding residuals. Consistency of the estimators is proved, and we obtain a singular asymptotic distribution which is concentrated on a hyperplane. Efficiency issues are explored and finite--sample results are presented as well as applications of the proposed procedures to real data from the financial markets. A multivariate extension is also considered.

Suggested Citation

  • Francq, Christian & Meintanis, Simos, 2012. "Fourier--type estimation of the power garch model with stable--paretian innovations," MPRA Paper 41667, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:41667
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    References listed on IDEAS

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    More about this item

    Keywords

    GARCH model; Minimum distance estimation; Heavy--tailed distribution; Empirical characteristic function;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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