Artikel
Optimal multi-step-ahead prediction of ARCH/GARCH models and NoVaS transformation
This paper gives a computer-intensive approach to multi-step-ahead prediction of volatility in financial returns series under an ARCH/GARCH model and also under a model-free setting, namely employing the NoVaS transformation. Our model-based approach only assumes i..id innovations without requiring knowledge/assumption of the error distribution and is computationally straightforward. The model-free approach is formally quite similar, albeit a GARCH model is not assumed. We conducted a number of simulations to show that the proposed approach works well for both point prediction (under L1 and/or L2 measures) and prediction intervals that were constructed using bootstrapping. The performance of GARCH models and the model-free approach for multi-step ahead prediction was also compared under different data generating processes.
- Language
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Englisch
- Bibliographic citation
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Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 7 ; Year: 2019 ; Issue: 3 ; Pages: 1-23 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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L1 and L2
bootstrap
GARCH(1,1)
Monte Carlo simulation
multi-step prediction
NoVaS transformation
- Event
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Geistige Schöpfung
- (who)
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Chen, Jie
Politis, Dimitris N.
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2019
- DOI
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doi:10.3390/econometrics7030034
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
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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
- Chen, Jie
- Politis, Dimitris N.
- MDPI
Time of origin
- 2019
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