Downside Risk Evaluation with the R Package GAS

R Journal, Forthcoming

12 Pages Posted: 17 Nov 2016 Last revised: 4 Sep 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: November 17, 2016

Abstract

Financial risk managers routinely use non-linear time series models to predict the downside risk of the capital under management. They also need to evaluate the adequacy of their model using so-called backtesting procedures. The latter involve hypothesis testing and evaluation of loss functions. This paper shows how the R package GAS can be used for both the dynamic prediction and the evaluation of downside risk. Emphasis is given to the two key financial downside risk measures: Value-at-Risk (VaR) and Expected Shortfall (ES). High-level functions for: (i) prediction, (ii) backtesting, and (iii) model comparison are discussed, and code examples are provided. An illustration using the series of log-returns of the Dow Jones Industrial Average constituents is reported.

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

JEL Classification: C01, C11, C22, C24, C32, C52, C53, C58

Suggested Citation

Ardia, David and Boudt, Kris and Catania, Leopoldo, Downside Risk Evaluation with the R Package GAS (November 17, 2016). R Journal, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2871444 or http://dx.doi.org/10.2139/ssrn.2871444

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

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