Two are better than one: volatility forecasting using multiplicative component GARCH‐MIDAS models

We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of generalized autoregressive conditional heteroskedasticity-mixed‐data sampling (GARCH‐MIDAS) models suggested in Engle, Ghysels, and Sohn (Review of Economics and Statistics, 201...

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Hauptverfasser: Conrad, Christian (VerfasserIn) , Kleen, Onno (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2020
In: Journal of applied econometrics
Year: 2019, Jahrgang: 35, Heft: 1, Pages: 19-45
ISSN:1099-1255
DOI:10.1002/jae.2742
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/jae.2742
Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/10.1002/jae.2742
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Verfasserangaben:Christian Conrad, Onno Kleen
Beschreibung
Zusammenfassung:We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of generalized autoregressive conditional heteroskedasticity-mixed‐data sampling (GARCH‐MIDAS) models suggested in Engle, Ghysels, and Sohn (Review of Economics and Statistics, 2013, 95, 776–797).
Beschreibung:First published: 02 November 2019
Gesehen am 18.01.2021
Beschreibung:Online Resource
ISSN:1099-1255
DOI:10.1002/jae.2742