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Estimation of stable distributions with indirect inference

Author

Listed:
  • Rene Garcia
  • Eric Renault
  • David Veredas

Abstract

This article deals with the estimation of the parameters of an α-stable distribution with indirect inference, using the skewed-t distribution as an auxiliary model. The latter distribution appears as a good candidate since it has the same number of parameters as the α-stable distribution, with each parameter playing a similar role. To improve the properties of the estimator in finite sample, we use constrained indirect inference. In a Monte Carlo study we show that this method delivers estimators with good properties in finite sample. We provide an empirical application to the distribution of jumps in the S&P 500 index returns. © 2010 Elsevier B.V. All rights reserved.

Suggested Citation

  • Rene Garcia & Eric Renault & David Veredas, 2011. "Estimation of stable distributions with indirect inference," ULB Institutional Repository 2013/136186, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:ulb:ulbeco:2013/136186
    Note: SCOPUS: ar.j
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    Citations

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    Cited by:

    1. Matteo Barigozzi & Roxana Halbleib & David Veredas, "undated". "Which model to match?," ULB Institutional Repository 2013/136240, ULB -- Universite Libre de Bruxelles.
    2. Calzolari, Giorgio & Halbleib, Roxana & Parrini, Alessandro, 2014. "Estimating GARCH-type models with symmetric stable innovations: Indirect inference versus maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 158-171.

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