Indirect Estimation of α-Stable Garch Models

Giorgio Calzolari, Roxana Halbleib () and Alessandro Parrini ()

No 2012-31, Working Paper Series of the Department of Economics, University of Konstanz from Department of Economics, University of Konstanz

Abstract: It is a well-known fact that financial returns exhibit conditional heteroscedasticity and fat tails. While the GARCH-type models are very popular in depicting the conditional heteroscedasticity, the α-stable distribution is a natural candidate for the conditional distribution of financial returns. The α-stable distribution is a generalization of the normal distribution and is described by four parameters, two of which deal with tail-thickness and asymmetry. However, practical implementation of α-stable distribution in finance applications has been limited by its estimation difficulties. In this paper, we propose an indirect approach of estimating GARCH models with α-stable innovations by using as auxiliary models GARCH-type models with Student's t distributed innovations. We provide comprehensive empirical evidence on the performance of the method within a series of Monte Carlo simulation studies and an empirical application to financial returns.

Keywords: Indirect Inference; α-stable Distribution; GARCH Models; Student's t Distribution (search for similar items in EconPapers)
Pages: 22 pages
Date: 2012-11-23
New Economics Papers: this item is included in nep-ecm and nep-ets
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Related works:
Journal Article: Estimating GARCH-type models with symmetric stable innovations: Indirect inference versus maximum likelihood (2014)
Working Paper: Estimating Stable Factor Models By Indirect Inference (2014)
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