Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various parametric and semiparametric GARCH-type models. For the latter the estimation of the nonparametric scale function is carried out by means of a data-driven smoothing approach. Model quality, in terms of forecasting VaR and ES, can be assessed by means of various backtesting methods such as the traffic light test for VaR and a newly developed traffic light test for ES. The approaches implemented in this package are described in e.g. Feng Y., Beran J., Letmathe S. and Ghosh S. (2020) <https://ideas.repec.org/p/pdn/ciepap/137.html> as well as Letmathe S., Feng Y. and Uhde A. (2021) <https://ideas.repec.org/p/pdn/ciepap/141.html>.
Package details |
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Author | Yuanhua Feng [aut] (Paderborn University, Germany), Xuehai Zhang [aut] (Former research associate at Paderborn University, Germany), Christian Peitz [aut] (Paderborn University, Germany), Dominik Schulz [aut] (Paderborn University, Germany), Shujie Li [aut] (Paderborn Universtiy, Germany), Sebastian Letmathe [aut, cre] (Paderborn University, Germany) |
Maintainer | Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de> |
License | GPL-3 |
Version | 1.0.7 |
URL | https://wiwi.uni-paderborn.de/en/dep4/feng/ |
Package repository | View on CRAN |
Installation |
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