Ibrahim Bassam A, Elamer Ahmed A, Abdou Hussein A
Department of Management, Faculty of Commerce, Mansoura University, Mansoura, Egypt.
Brunel Business School, Brunel University London, Kingston Lane, Uxbridge, London, UB8 3PH UK.
Ann Oper Res. 2022 Oct 28:1-44. doi: 10.1007/s10479-022-05024-4.
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.
本研究旨在探讨加密货币和美元在预测新冠疫情之前及期间油价方面的作用。该研究在2018年1月1日至2021年7月5日期间使用了三种神经网络模型（即支持向量机、多层感知器神经网络和广义回归神经网络（GRNN））。我们的研究结果有三点。第一，我们的结果表明，比特币在预测新冠疫情之前的熊市和牛市油价以及新冠疫情期间的下跌趋势时，对油价的影响最大。第二，新冠疫情变量在上涨趋势期间成为最具影响力的因素，尤其是死亡病例数。第三，我们的结果还表明，在新冠疫情后世界普遍存在的不确定性条件下，预测油价的最准确模型是GRNN。尽管在新冠疫情之前的正常条件下，上涨趋势期间的最佳预测模型是支持向量机，下跌趋势期间的最佳预测模型是GRNN。我们的研究结果为投资者、学者和政策制定者提供了关键证据，尤其是在全球不确定性期间。
