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
Englisch

Bibliographic citation
Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 7 ; Year: 2019 ; Issue: 3 ; Pages: 1-23 ; Basel: MDPI

Classification
Wirtschaft
Subject
L1 and L2
bootstrap
GARCH(1,1)
Monte Carlo simulation
multi-step prediction
NoVaS transformation

Event
Geistige Schöpfung
(who)
Chen, Jie
Politis, Dimitris N.
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2019

DOI
doi:10.3390/econometrics7030034
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Chen, Jie
  • Politis, Dimitris N.
  • MDPI

Time of origin

  • 2019

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