Artikel
Volatility forecast in crises and expansions
We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 8 ; Year: 2015 ; Issue: 3 ; Pages: 311-336 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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volatility forecast
non-linear time series models
- Event
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Geistige Schöpfung
- (who)
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Pypko, Sergii
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2015
- DOI
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doi:10.3390/jrfm8030311
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Pypko, Sergii
- MDPI
Time of origin
- 2015
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