Downside Risk Evaluation with the R Package GAS
R Journal, Vol. 10, Issue 2, pp. 410-421, 2018
12 Pages Posted: 17 Nov 2016 Last revised: 27 Feb 2019
Date Written: November 17, 2016
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: Suggested Citation