Department of Economics and Business Economics

Downside Risk Evaluation with the R Package GAS

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • David Ardia, Swaziland
  • Kris Boudt, Vrije Universiteit Brussel, Belgium and VU University Amsterdam, Netherlands
  • Leopoldo Catania
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
JournalThe R Journal
Volume10
Issue2
Pages (from-to)410-421
ISSN2073-4859
DOIs
Publication statusPublished - 2018

See relations at Aarhus University Citationformats

ID: 146338823