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| LEADER |
01582nam a2200217Ia 4500 |
| 001 |
10.3390-econometrics7030034 |
| 008 |
220511s2019 CNT 000 0 und d |
| 020 |
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|a 22251146 (ISSN)
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| 245 |
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|a Optimal multi-step-ahead prediction of ARCH/GARCH models and NoVaS transformation
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| 260 |
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|b MDPI AG
|c 2019
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| 856 |
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|z View Fulltext in Publisher
|u https://doi.org/10.3390/econometrics7030034
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|a 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.i.d 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. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
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|a Bootstrap
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|a GARCH(1, 1)
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| 650 |
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|a L1 and L2 measures
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|a Monte Carlo simulation
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|a Multi-step prediction
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|a NoVaS transformation
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| 700 |
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|a Chen, J.
|e author
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|a Politis, D.N.
|e author
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| 773 |
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|t Econometrics
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