The R Journal: article published in 2018, volume 10:2

Downside Risk Evaluation with the R Package GAS
David Ardia, Kris Boudt and Leopoldo Catania , The R Journal (2018) 10:2, pages 410-421.

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.

Received: 2018-05-01; online 2018-12-08, supplementary material, (3.9 KiB)
CRAN packages: GAS, cubature
CRAN Task Views implied by cited CRAN packages: NumericalMathematics, TimeSeries

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-064,
  author = {David Ardia and Kris Boudt and Leopoldo Catania},
  title = {{Downside Risk Evaluation with the R Package GAS}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-064},
  url = {https://doi.org/10.32614/RJ-2018-064},
  pages = {410--421},
  volume = {10},
  number = {2}
}