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...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2020
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| 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 |
MARC
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| 520 | |a 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). | ||
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