Downside risk evaluation with the R package GAS

David Ardia, Kris Boudt, Leopoldo Catania*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)410-421
Number of pages12
JournalR Journal
Volume10
Issue number2
Early online date8 Dec 2018
DOIs
Publication statusPublished - Dec 2018

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