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Title

Modelling and Forecasting Crude Oil Prices Using Trend Analysis in a Binary-Temporal Representation

Authors

[ 1 ] Instytut Maszyn Roboczych i Pojazdów Samochodowych, Wydział Inżynierii Lądowej i Transportu, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.7] Civil engineering, geodesy and transport

Year of publication

2024

Published in

Energies

Journal year: 2024 | Journal volume: vol. 17 | Journal number: iss. 14

Article type

scientific article

Publication language

english

Keywords
EN
  • oil market
  • oil price forecasting
  • trend analysis
  • state modeling
Abstract

EN The oil market is one of the most important markets for the global economy. Often, oil prices influence the financial results of whole countries and sectors. Therefore, the modeling and prediction of crude oil prices are of high importance. Most up-to-date publications have used daily closing rates in crude oil price modeling, not considering the variability in prices during the day. The application of this kind of price representation leads to a loss of information about the range of price changes during the day, which influences the accuracy of the models and makes them useless in short-term course predictions. In this paper, we introduce the concept of a new state model in a binary-temporal representation, which uses trend analysis, which is one of the main methods used in the prediction of the direction of future changes in the course trajectory. The model described in this paper stands as the first tool that allows for predicting course changes in a given range. The presented work also summarizes the research results of modeling crude oil prices from the last six years, which prove the effectiveness of the mentioned modeling method.

Pages (from - to)

3361-1 - 3361-13

DOI

10.3390/en17143361

URL

https://www.mdpi.com/1996-1073/17/14/3361

Comments

Article number: 3361

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Full text of article

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Access level to full text

public

Ministry points / journal

140

Impact Factor

3 [List 2023]

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