Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Research on Crude Oil Price Forecasting Technology Cased on Fbprophet

Authors
Haoran Ma1, *
1International Department of Harbin NO.9 High School, Harbin, Heilongjiang, 150001, China
*Corresponding author. Email: chengjimin@htdc.ltd
Corresponding Author
Haoran Ma
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_29How to use a DOI?
Keywords
Oil Price; Forecasting Technology; On Fbprophet
Abstract

Forecasting oil prices is crucial for various industries and economic decision-making. This abstract explores the application of the fbprophet library for accurate and reliable oil price predictions. Fbprophet, developed by Facebook’s Core Data Science team, offers a user-friendly interface for time series modeling and forecasting. By utilizing a decomposable time series model, fbprophet captures the underlying trends, seasonality, and holiday effects in oil price data. It also handles missing data and outliers effectively. This abstract outlines the steps involved in implementing oil price forecasting using fbprophet, including data preprocessing, model fitting, prediction generation, and result visualization. The fbprophet library provides a powerful tool for businesses, policymakers, and investors to make informed decisions based on accurate oil price forecasts. This summary highlights the advantages of using fb prophet over traditional prediction methods such as its ability to deal with nonlinear trends and incorporate external factors. The results of applying financial forecasts to historical oil price data demonstrate its effectiveness in providing reliable forecasts, enabling stakeholders to reduce risk and optimize their strategies in volatile oil markets.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_29
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_29How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Haoran Ma
PY  - 2024
DA  - 2024/02/14
TI  - Research on Crude Oil Price Forecasting Technology Cased on Fbprophet
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 260
EP  - 269
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_29
DO  - 10.2991/978-94-6463-370-2_29
ID  - Ma2024
ER  -