Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F23%3A39920761" target="_blank" >RIV/00216275:25410/23:39920761 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0275531922002495?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0275531922002495?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ribaf.2022.101863" target="_blank" >10.1016/j.ribaf.2022.101863</a>
Alternative languages
Result language
angličtina
Original language name
Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network
Original language description
This paper aims to develop an artificial neural network-based forecasting model employing a nonlinear focused time-delayed neural network (FTDNN) for energy commodity market forecasts. To validate the proposed model, crude oil and natural gas prices are used for the period 2007-2020, including the Covid-19 period. Empirical findings show that the FTDNN model outperforms existing baselines and artificial neural network-based models in forecasting West Texas Intermediate and Brent crude oil prices and National Balancing Point and Henry Hub natural gas prices. As a result, we demonstrate the predictability of energy commodity prices during the volatile crisis period, which is attributed to the flexibility of the model parameters, implying that our study can facilitate a better understanding of the dynamics of commodity prices in the energy market.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Research in International Business and Finance
ISSN
0275-5319
e-ISSN
1878-3384
Volume of the periodical
64
Issue of the periodical within the volume
January
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
15
Pages from-to
101863
UT code for WoS article
000916569300001
EID of the result in the Scopus database
2-s2.0-85144919650