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• W4308183020 abstract "This study aims to explore the role of cryptocurrencies and the US dollar in predicting oil prices pre and during COVID-19 pandemic. The study uses three neural network models (i.e., Support vector machines, Multilayer Perceptron Neural Networks and Generalized regression neural networks (GRNN)) over the period from January 1, 2018, to July 5, 2021. Our results are threefold. First, our results indicate Bitcoin is the most influential in predicting oil prices during the bear and bull oil market before COVID-19 and during the downtrend during COVID-19. Second, COVID-19 variables became the most influential during the uptrend, especially the number of death cases. Third, our results also suggest that the most accurate model to predict the price of oil under the conditions of uncertainty that prevailed in the world during the bear and bull prices in the wake of COVID-19 is GRNN. Though the best prediction model under normal conditions before COVID-19 during an uptrend is SVM and during a downtrend is GRNN. Our results provide crucial evidence for investors, academics and policymakers, especially during global uncertainties." @default.
• W4308183020 created "2022-11-09" @default.
• W4308183020 creator A5011669648 @default.
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• W4308183020 date "2022-10-28" @default.
• W4308183020 modified "2023-09-25" @default.
• W4308183020 title "The role of cryptocurrencies in predicting oil prices pre and during COVID-19 pandemic using machine learning" @default.
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• W4308183020 doi "https://doi.org/10.1007/s10479-022-05024-4" @default.
• W4308183020 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36320866" @default.
• W4308183020 hasPublicationYear "2022" @default.
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