Forecasting crude oil prices volatility by reconstructing EEMD components using ARIMA and FFNN models

Laiba Sultan Dar, Muhammad Aamir, Zardad Khan, Muhammad Bilal, Nattakan Boonsatit, Anuwat Jirawattanapanit

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The energy sector which includes gas and oil is concerned to explore and develop refined oil and it’s a multitrillion business. As crude oil is a very important source of energy, and it has a very valuable impact on a country’s economic growth, national security, and social stability. Therefore, accurately predicting the crude oil price volatility is a very important topic of research and still, it is a challenge for researchers to accurately forecast crude oil prices. Therefore, this study is conducted to address the said problem significantly. This research presents a novel hybrid method for reconstructing EEMD IMFs that involves two steps. Visual analysis of Average Mutual Information (AMI) graphs were used to rebuild IMFs. EEMD IMFs were split into two components called stochastic and deterministic. In the proposed method, reconstruction of IMFs of EEMD was done at two stages to see if the stochastic components have more variation. Later, ARIMA and FFNN models were used to test the suggested method’s performance. For this purpose, Brent crude oil prices data was used, and the hybrid model EEMD-S2D1D2-ARIMA/FFNN outperformed the other existing hybrid model with minimum MAE = 0.2323, RMSE = 0.3058 and MAPE = 0.5273. A simulation study was also conducted to check the robustness of the proposed method for N = 50, 500, 1,000, 2000, 5,000, and 7,500. The simulation results also confirm that the unpredictability present in the reconstructed IMFs of the hybrid models EEMD-ARIMA/FFNN and EEMD-SD-ARIMA/FFNN has been reduced by the proposed hybrid models.

Original languageEnglish
Article number991602
JournalFrontiers in Energy Research
Volume10
DOIs
Publication statusPublished - Oct 10 2022
Externally publishedYes

Keywords

  • ARIMA
  • crude oil prices forecasting
  • EEMD
  • FFNN
  • IMFs reconstruction

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Economics and Econometrics

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