Big Data Analysis of Energy Economics in Oil Market

Hui Liu (), Nikolaos Nikitas (), Yanfei Li () and Rui Yang ()
Additional contact information
Hui Liu: Central South University
Nikolaos Nikitas: University of Leeds
Yanfei Li: Hunan Agricultural University
Rui Yang: Central South University

Chapter Chapter 2 in Big Data in Energy Economics, 2022, pp 43-65 from Springer

Abstract: Abstract As industrial blood and raw material, crude oil occupies an important strategic position in the economic market of global energy. In this chapter, the economic significance and social value of forecasting crude oil prices are first introduced. Then the factors that affect the fluctuation in crude oil prices are expounded, including the relationship between supply and demand, economic development, policy formulation, global emergencies, etc. Next, this chapter conducts price prediction modeling on West Texas Intermediate crude oil and Brent crude oil, the two most important benchmark oils in the international crude oil market. The experiment compares the prediction capabilities of bi-directional long short-term memory network and deep belief network. Finally, this chapter provides an econometric analysis of the international crude oil market, big data technologies, and policy recommendations for developing the energy economy.

Keywords: Crude oil prices forecasting; Big data modeling; Price influencing factors; International crude oil market; Policies and recommendations (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-981-16-8965-9_2

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DOI: 10.1007/978-981-16-8965-9_2

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