Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets
- Authors
- Islam, Umar; Awwad, Emad Mahrous; Sarhan, Nadia Mohamed; Fattah Sharaf, Mohamed Abdel; Ali, Ijaz; Khan, Inayat; Ahmad, Shehzad; Khan, 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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