Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1785
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Master Term Project Predicttion of Brent Oil Spot Prices Using Country Based Inventory and Trading Data(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2019) Usta, İsmail Batur; Ağralı, SemraCrude oil price forecasting has been the focus of numerous authorities, yet the task still persists on being a challenging one. The extremely volatile nature of oil market and high number of active players in it makes establishing a solid forecasting model that is constantly relevant to time very difficult. Recent advancements on data technologies, mainly ever-increasing computing power and trending big data technologies allowed new approaches to be born. From online learners to natural language processing, advanced data analytics models were employed with the help of easily accessible and diverse data. This project is an attempt on making use of such available data in order to forecast Brent oil spot price. By using monthly country by country inventory, trading and economic data, strong drivers of crude price was explored. The data used in this project comes from various sources and in multiple formats, with the final merged data frame has over 17000 observations and contains information on 86 countries. To enhance prediction power, a specialized learner is fit on each country individually and then the predictions are accumulated and filtered before outputting a single prediction. Compared to a single predictor, this approach enhanced the predictive power of the algorithm by adapting to dynamics of each country.