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

DOI10.1016/J.CSDA.2013.07.028zbMath1506.62032OpenAlexW1970123062MaRDI QIDQ1623518

Roxana Halbleib, Giorgio Calzolari, Alessandro Parrini

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-290148

zbMATH Keywords

maximum likelihoodindirect inferenceStudent's \(t\) distributionleverage effectsGARCH-type modelssymmetric \(\alpha\)-stable distribution

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Point estimation (62F10)

Related Items (8)

Indirect inference for locally stationary ARMA processes with stable innovations ⋮ A two-step estimation procedure for locally stationary ARMA processes with tempered stable innovations ⋮ Maximum likelihood estimation for \(\alpha\)-stable double autoregressive models ⋮ Markov regime-switching autoregressive model with tempered stable distribution: simulation evidence ⋮ Fractionally integrated GARCH model with tempered stable distribution: a simulation study ⋮ Estimating stable latent factor models by indirect inference ⋮ Estimation of time-varying autoregressive stochastic volatility models with stable innovations ⋮ Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH models

Uses Software

• STABLE

Cites Work

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