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On the Oil Price Uncertainty

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  • Zied Ftiti and Fredj Jawadi

Abstract

This study focuses on oil price volatility and uncertainty over the period January 1986-December 2018, covering episodes of oil price increases and collapses. Accordingly, in line with Poon and Granger (2003), and Terasvirta and Zhao (2011), we propose three different specifications of stochastic oil volatility: standard stochastic volatility, stochastic volatility moving average, leverage stochastic volatility models. We compute the out-of-sample forecasts for the uncertainty in oil prices using the estimates for these three stochastic oil price volatility models and we discuss its effects. Our findings show that the standard stochastic volatility model outperforms the other two models when focusing on oil price uncertainty. This finding is relevant to better forecast and understand the effects of oil price uncertainty on the real economy.

Suggested Citation

  • Zied Ftiti and Fredj Jawadi, 2019. "On the Oil Price Uncertainty," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    • Handle: RePEc:aen:journl:ej40-si2-ftiti
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    1. Bashar, Omar H.M.N. & Wadud, I.K.M. Mokhtarul & Ali Ahmed, Huson Joher, 2013. "Oil price uncertainty, monetary policy and the macroeconomy: The Canadian perspective," Economic Modelling, Elsevier, vol. 35(C), pages 249-259.
    2. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    3. Sadorsky, Perry, 2008. "Assessing the impact of oil prices on firms of different sizes: Its tough being in the middle," Energy Policy, Elsevier, vol. 36(10), pages 3854-3861, October.
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    Cited by:

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    2. Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024. "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper 122899, University Library of Munich, Germany.
    3. Ciniro A. L. Nametala & Jonas Villela de Souza & Alexandre Pimenta & Eduardo Gontijo Carrano, 2023. "Use of Econometric Predictors and Artificial Neural Networks for the Construction of Stock Market Investment Bots," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 743-773, February.

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