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Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets

Authors
Islam, UmarAwwad, Emad MahrousSarhan, Nadia MohamedFattah Sharaf, Mohamed AbdelAli, IjazKhan, InayatAhmad, ShehzadKhan, Faheem
Issue Date
Apr-2024
Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
Keywords
Oil price forecasting; stock market performance; machine learning; global forecasting; economic factors
Citation
FLUCTUATION AND NOISE LETTERS, v.23, no.2
Journal Title
FLUCTUATION AND NOISE LETTERS
Volume
23
Number
2
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91024
DOI
10.1142/S0219477524400212
ISSN
0219-4775
1793-6780
Abstract
In today's globalized economic landscape, the assurance of economic stability is of paramount importance, necessitating precise financial decision-making and policy formulation. This assurance is significantly augmented by innovative approaches to predicting crude oil prices, particularly in the context of energy stock markets denominated in USD. This paper delves into the transformative effect of accurate crude oil price prediction on economic policy stability. It underscores the challenges and limitations posed by policy uncertainties and emphasizes the pivotal role of innovative solutions in mitigating these challenges. Moreover, it recognizes the imperative need for secure data storage to facilitate the application of machine learning in this domain. Furthermore, effective management and regulation of power grid systems are explored as indispensable strategies for tempering the volatility introduced by fluctuations in energy stock markets. As we work to address these gaps in knowledge, the potential for sustainable power systems to supersede fossil fuels emerges as a driving force behind the maintenance of stable economic policies.
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College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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