Publication: Density and Risk Prediction with Non-Gaussian COMFORT Models
Density and Risk Prediction with Non-Gaussian COMFORT Models
Date
Date
Date
Citations
Paolella, M. S., & Polak, P. (2023). Density and Risk Prediction with Non-Gaussian COMFORT Models. Annals of Financial Economics, 18(01), 2250033. https://doi.org/10.1142/s2010495222500336
Abstract
Abstract
Abstract
The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called COMFORT model class, which is the CCC-GARCH model but endowed with multivariate generalized hyperbolic innovations. The novelty of the model is that parameter estimation is conducted by joint maximum likelihood, of all model parameters, using an E
Metrics
Views
Additional indexing
Creators (Authors)
- Polak, Paweł
Volume
Volume
Volume
Number
Number
Number
Page Range
Page Range
Page Range
Item Type
Item Type
Item Type
In collections
Keywords
Scope
Scope
Scope
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
Additional Information
Additional Information
Additional Information
OA Status
OA Status
OA Status
Publisher DOI
Other Identification Number
Other Identification Number
Other Identification Number
Related URLs
Related URLs
Related URLs
Metrics
Views
Citations
Paolella, M. S., & Polak, P. (2023). Density and Risk Prediction with Non-Gaussian COMFORT Models. Annals of Financial Economics, 18(01), 2250033. https://doi.org/10.1142/s2010495222500336