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Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model

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  • Ani Shabri
  • Ruhaidah Samsudin

Abstract

A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS). The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI) and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.

Suggested Citation

  • Ani Shabri & Ruhaidah Samsudin, 2014. "Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, July.
    • Handle: RePEc:hin:jnlmpe:201402
    DOI: 10.1155/2014/201402
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    Cited by:

    1. Hosseini, Seyed Hossein & Shakouri G., Hamed & Kazemi, Aliyeh, 2021. "Oil price future regarding unconventional oil production and its near-term deployment: A system dynamics approach," Energy, Elsevier, vol. 222(C).
    2. Li, Guohui & Yin, Shibo & Yang, Hong, 2022. "A novel crude oil prices forecasting model based on secondary decomposition," Energy, Elsevier, vol. 257(C).
    3. Arthur Stepchenko & Jurij Chizhov & Ludmila Aleksejeva, 2018. "Transfer of the data preprocessing parameters and fore- casting models," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 4(6), pages 214-221.
    4. Yee-Fan Tan & Lee-Yeng Ong & Meng-Chew Leow & Yee-Xian Goh, 2021. "Exploring Time-Series Forecasting Models for Dynamic Pricing in Digital Signage Advertising," Future Internet, MDPI, vol. 13(10), pages 1-24, September.
    5. Arash Sioofy Khoojine & Mahboubeh Shadabfar & Yousef Edrisi Tabriz, 2022. "A Mutual Information-Based Network Autoregressive Model for Crude Oil Price Forecasting Using Open-High-Low-Close Prices," Mathematics, MDPI, vol. 10(17), pages 1-20, September.

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