Statistics, Department of
The R Journal
Date of this Version
12-2018
Document Type
Article
Citation
The R Journal (December 2018) 10(2); Editor: John Verzani
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.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2018, The R Foundation. Open access material. License: CC BY 4.0 International