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A hybrid approach for forecasting of oil prices volatility

Author

Listed:
  • Akbar Komijani
  • Esmaeil Naderi
  • Nadiya Gandali Alikhani

Abstract

This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the ‘predictability’ hypothesis was tested using the variance ratio test, BDS test and the chaos analysis. Structural analyses were also carried out to identify possible non-linear patterns in this series. On this basis, Lyapunov exponents confirmed that the return series of crude oil price is chaotic. Moreover, according to the findings, the rate of return series has the long memory property rejecting the efficient market hypothesis and affirming the fractal markets hypothesis. The results of the Geweke and Porter-Hudak test verified that both the rate of return and volatility series of crude oil price have the long memory property. Besides, according to both mean square error (MSE) and root mean square error (RMSE) criteria, wavelet-decomposed data improve the performance of the model significantly. Therefore, a hybrid model was introduced based on the long memory property which uses wavelet decomposed data as the most relevant model.

Suggested Citation

  • Akbar Komijani & Esmaeil Naderi & Nadiya Gandali Alikhani, 2014. "A hybrid approach for forecasting of oil prices volatility," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 323-340, September.
    • Handle: RePEc:bla:opecrv:v:38:y:2014:i:3:p:323-340
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    File URL: http://hdl.handle.net/10.1111/opec.12030
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    Cited by:

    1. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2021. "Modelling Oil Price with Lie Algebras and Long Short-Term Memory Networks," Mathematics, MDPI, vol. 9(14), pages 1-10, July.
    2. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    3. Delavari, Majid & Baranpour, Naghmeh & Abdeshahi, Abbas, 2014. "Analyzing the Effect of Real Exchange Rate on Petrochemicals Exporting," MPRA Paper 60360, University Library of Munich, Germany.
    4. Tao Yin & Yiming Wang, 2019. "Predicting the Price of WTI Crude Oil Using ANN and Chaos," Sustainability, MDPI, vol. 11(21), pages 1-14, October.
    5. Zarei, Samira, 2019. "How do Real Exchange Rate Movements Affect the Economic Growth in Iran?," MPRA Paper 99102, University Library of Munich, Germany.
    6. Zarei, Samira, 2020. "Analyzing the Asymmetric Effects of Inflation and Exchange Rate Misalignments on the Petrochemical Stock index: The Case of Iran," MPRA Paper 99101, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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