R package rugarch: Univariate GARCH Models. ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.
Keywords for this software
References in zbMATH (referenced in 10 articles )
Showing results 1 to 10 of 10.
- Bee, Marco; Dickson, Maria Michela; Santi, Flavio: Likelihood-based risk estimation for variance-gamma models (2018)
- Fan, Jianqing; Yao, Qiwei: The elements of financial econometrics (2017)
- Chan, Stephen; Nadarajah, Saralees; Afuecheta, Emmanuel: An R package for value at risk and expected shortfall (2016)
- Gurgul, Henryk; Machno, Artur: Modeling dependence structure among European markets and among Asian-Pacific markets: a regime switching regular vine copula approach (2016)
- Ranković, Vladimir; Drenovak, Mikica; Urosevic, Branko; Jelic, Ranko: Mean-univariate GARCH VaR portfolio optimization: actual portfolio approach (2016)
- Wang, Chuan-Sheng; Zhao, Zhibiao: Conditional Value-at-Risk: semiparametric estimation and inference (2016)
- Ehlert, Andree; Fiebig, Ulf-Rainer; Janßen, Anja; Schlather, Martin: Joint extremal behavior of hidden and observable time series with applications to GARCH processes (2015)
- Schmitt, Thilo A.; Schäfer, Rudi; Dette, Holger; Guhr, Thomas: Quantile correlations: uncovering temporal dependencies in financial time series (2015)
- Elatraby, Amr Ibrahim Abdelrahman; Elwaqdy, Ahmed Fathy Abdelaal: Suggested statistical model for describing the fluctuations in the conditional variation with application on the general index of the Egyptian capital market (2014)
- Mauro Bernardi, Leopoldo Catania: The Model Confidence Set package for R (2014) arXiv