ALRIGHT: Asymmetric LaRge-Scale (I)GARCH with Hetero-Tails

34 Pages Posted: 22 Jun 2010 Last revised: 7 Dec 2018

See all articles by Marc S. Paolella

Marc S. Paolella

University of Zurich - Department of Banking and Finance; Swiss Finance Institute

Pawel Polak

Stevens Institute of Technology, Department of Mathematical Sciences

Date Written: November 1, 2013

Abstract

It is well-known in empirical nance that virtually all asset returns, whether monthly, daily, or intraday, are heavy-tailed and, particularly for stock returns, are mildly but often signi cantly negatively skewed. However, the tail indices, or maximally existing moments of the returns, can di er markedly across assets. To accommodate these stylized facts when modeling the joint distribution of asset returns, an asymmetric extension of the metaelliptical t distribution is proposed. While the likelihood is tractable, for high dimensions it will be impractical to use for estimation. To address this, a fast, two-step estimation procedure is developed, based on a saddlepoint approximation to the noncentral Student's t distribution. The model is extended to support a CCC-(I)GARCH structure and demonstrated by modeling and forecasting the return series comprising the DJIA. The techniques of shrinkage, time-varying tail dependence, and weighted likelihood are employed to further enhance the forecasting performance of the model with no added computational burden.

Keywords: Asymmetry, Copula, Density Forecasting, Empirical Finance, Fat Tails, GARCH, Integrated GARCH, Multivariate Distribution, Saddlepoint Approximation, Shrinkage Estimation, Weighted Likelihood

JEL Classification: C13, C32, G11

Suggested Citation

Paolella, Marc S. and Polak, Pawel, ALRIGHT: Asymmetric LaRge-Scale (I)GARCH with Hetero-Tails (November 1, 2013). Swiss Finance Institute Research Paper No. 10-27, Available at SSRN: https://ssrn.com/abstract=1628146 or http://dx.doi.org/10.2139/ssrn.1628146

Marc S. Paolella (Contact Author)

University of Zurich - Department of Banking and Finance

Plattenstr. 14
Z├╝rich, 8032
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Pawel Polak

Stevens Institute of Technology, Department of Mathematical Sciences ( email )

Hoboken, NJ 07030
United States

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