Generalized Autoregressive Score Models in R: The GAS Package

Journal of Statistical Software, Forthcoming

26 Pages Posted: 21 Aug 2016 Last revised: 1 Jun 2018

See all articles by David Ardia

David Ardia

University of Neuchatel - Institute of Financial Analysis

Kris Boudt

Vrije Universiteit Brussel; Vrije Universiteit Amsterdam

Leopoldo Catania

Aarhus University - School of Business and Social Sciences; Aarhus University - CREATES

Date Written: August 17, 2016

Abstract

This paper presents the R package GAS for the analysis of time series under the Generalized Autoregressive Score (GAS) framework of Creal et al. (2013) and Harvey (2013). The distinctive feature of the GAS approach is the use of the score function as the driver of time{variation in the parameters of nonlinear models. The GAS package provides functions to simulate univariate and multivariate GAS processes, estimate the GAS parameters and to make time series forecasts. We illustrate the use of the GAS package with a detailed case study on estimating the time-varying conditional densities of a set of financial assets.

Keywords: GAS, Time Series Models, Score Models, Dynamic Conditional Score, R Software

JEL Classification: C01, C22, C32, C53

Suggested Citation

Ardia, David and Boudt, Kris and Catania, Leopoldo, Generalized Autoregressive Score Models in R: The GAS Package (August 17, 2016). Journal of Statistical Software, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2825380 or http://dx.doi.org/10.2139/ssrn.2825380

David Ardia (Contact Author)

University of Neuchatel - Institute of Financial Analysis ( email )

Rue A.-L. Breguet 2
Neuchatel, CH-2000
Switzerland

Kris Boudt

Vrije Universiteit Brussel ( email )

Pleinlaan 2
http://www.vub.ac.be/
Brussels, 1050
Belgium

Vrije Universiteit Amsterdam ( email )

De Boelelaan 1105
Amsterdam, ND North Holland 1081 HV
Netherlands

Leopoldo Catania

Aarhus University - School of Business and Social Sciences ( email )

Fuglesangs Allé 4
Aarhus V, DK-8210
Denmark
+4587165536 (Phone)

HOME PAGE: http://pure.au.dk/portal/en/leopoldo.catania@econ.au.dk

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Register to save articles to
your library

Register

Paper statistics

Downloads
1,064
rank
18,235
Abstract Views
5,730
PlumX