Value-at-risk forecasting based on Gaussian mixture ARMA–GARCH model
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Publication:4914961
DOI10.1080/00949651003752320zbMath1432.62306OpenAlexW1966557480MaRDI QIDQ4914961
Publication date: 16 April 2013
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949651003752320
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)
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Cites Work
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- Testing the stable Paretian assumption
- Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
- Stationarity and moment structure for Box-Cox transformed threshold GARCH(1,1) processes
- Mixture Densities, Maximum Likelihood and the EM Algorithm
- A Comparison of Minimum Distance and Maximum Likelihood Estimation of a Mixture Proportion
- On a Mixture Autoregressive Conditional Heteroscedastic Model
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