Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247534 
Year of Publication: 
2019
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 7 [Issue:] 3 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-23
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
L1 and L2
bootstrap
GARCH(1,1)
Monte Carlo simulation
multi-step prediction
NoVaS transformation
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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