Estimating GARCH-type models with symmetric stable innovations : indirect inference versus maximum likelihood

Calzolari, Giorgio; Chiriac, Roxana; Parrini, Alessandro

Estimating GARCH-type models with symmetric stable innovations : indirect inference versus maximum likelihood

Dateien

Calzolari_290148.pdfGröße: 138.59 KBDownloads: 423

Datum

2014

Autor:innen

Calzolari, Giorgio

Chiriac, Roxana

Parrini, Alessandro

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Wirtschaftswissenschaften
Zukunftskolleg

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Computational Statistics & Data Analysis. 2014, 76, pp. 158-171. ISSN 0167-9473. eISSN 1872-7352. Available under: doi: 10.1016/j.csda.2013.07.028

Zusammenfassung

Financial returns exhibit conditional heteroscedasticity, asymmetric responses of their volatility to negative and positive returns (leverage effects) and fat tails. The αα-stable distribution is a natural candidate for capturing the tail-thickness of the conditional distribution of financial returns, while the GARCH-type models are very popular in depicting the conditional heteroscedasticity and leverage effects. However, practical implementation of αα-stable distribution in finance applications has been limited by its estimation difficulties. The performance of the indirect inference approach using GARCH models with Student’s tt distributed errors as auxiliary models is compared to the maximum likelihood approach for estimating GARCH-type models with symmetric αα-stable innovations. It is shown that the expected efficiency gains of the maximum likelihood approach come at high computational costs compared to the indirect inference method.

Fachgebiet (DDC)

330 Wirtschaft

Schlagwörter

Symmetric α-stable distribution, GARCH-type models, Indirect inference, Maximum likelihood, Leverage effects, Student’s t distribution

Zitieren

ISO 690

CALZOLARI, Giorgio, Roxana CHIRIAC, Alessandro PARRINI, 2014. Estimating GARCH-type models with symmetric stable innovations : indirect inference versus maximum likelihood. In: Computational Statistics & Data Analysis. 2014, 76, pp. 158-171. ISSN 0167-9473. eISSN 1872-7352. Available under: doi: 10.1016/j.csda.2013.07.028

BibTex

@article{Calzolari2014Estim-29014,
  year={2014},
  doi={10.1016/j.csda.2013.07.028},
  title={Estimating GARCH-type models with symmetric stable innovations : indirect inference versus maximum likelihood},
  volume={76},
  issn={0167-9473},
  journal={Computational Statistics & Data Analysis},
  pages={158--171},
  author={Calzolari, Giorgio and Chiriac, Roxana and Parrini, Alessandro}
}

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