Crude Oil Price Forecasting Using Text Mining and Big Data Modeling

Document Type : Research - Paper

Authors

1 Associate Professor, Faculty of Economics, Razi University, Kermanshah, Iran

2 Assistant Professor, Faculty of Economics, Payame Noor University, Tehran, Iran

3 Ph.D Student, Faculty of Economics, Razi University, Kermanshah, Iran

Abstract

This study uses data modeling and text mining techniques for oil price predictions. To improve the model's explanatory capability, text features from internet news articles on crude oil are automatically extracted using convolutional neural networks. Additionally, various time series models employ a state analysis approach called convolution. The years 2021 to 2011 saw the collection of almost 13000 news items, and it was discovered that text mining and data from large Internet-based apps perform better for prediction than other approaches. This means that it is pretty fair to say that there is a parallel link between news headlines, those headlines, and searches in the Google search engine. This relationship is highly appropriate for correctly forecasting the price of crude oil.

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Main Subjects

References

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History

  • Receive Date: 30 June 2022
  • Revise Date: 08 November 2022
  • Accept Date: 04 September 2022

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