WFRF:(Sahamkhadam Maziar)
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Enhancing the predictability of crude oil markets with hybrid wavelet approaches
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- Uddin, Gazi Salah (author)
- Linköpings universitet,Nationalekonomi,Filosofiska fakulteten
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- Gencay, Ramazan (author)
- Simon Fraser Univ, Canada
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- Bekiros, Stelios (author)
- European University Institute, Italy;Athens University of Economics and Business, Greece,EUI, Italy; AUEB, Greece
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- (creator_code:org_t)
- Elsevier, 2019
- 2019
- English.
- In: Economics Letters. - : Elsevier. - 0165-1765 .- 1873-7374. ; 182, s. 50-54
- Journal article (peer-reviewed)
Abstract
Subject headings
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- We explore the robustness, efficiency and accuracy of the multi-scale forecasting in crude oil markets. We adopt a novel hybrid wavelet auto-ARMA model to detect the inherent nonlinear dynamics of crude oil returns with an explicitly defined hierarchical structure. Entropic estimation is employed to calculate the optimal level of the decomposition. The wavelet-based forecasting method accounts for the chaotic behavior of oil series, whilst captures drifts, spikes and other non-stationary effects which common frequency-domain methods miss out completely. These results shed new light upon the predictability of crude oil markets in nonstationary settings. (C) 2019 Elsevier B.V. All rights reserved.
Subject headings
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- Wavelet decomposition
- Forecasting
- Crude oil
- Economy
- Ekonomi
Publication and Content Type
- ref (subject category)
- art (subject category)
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