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An information diffusion-based model of oil futures price

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  • Li, Ziran
  • Sun, Jiajing
  • Wang, Shouyang

Abstract

Inspired by the increasing evidence of financialization/speculation in commodity pricing, this paper constitutes a first attempt to build an information diffusion-based asset pricing framework for the oil futures market. With gradual information dissemination, slowly decaying uncertainty about the asset's future fundamentals generates persistent conditional volatility and a drift in asset return. Volatility-based proxies for information flows are proposed to examine empirically the asset pricing implications. The results confirm a significant intertemporal relationship between return on the price of oil futures, information diffusion and volatility components. An important implication of our study is that the slow diffusion of information generates predictability in price dynamics. A forecasting model is then constructed and tested in relation to our theory. It is found that the lagged series of the pricing factors possess significant predicting power for returns.

Suggested Citation

  • Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
  • Handle: RePEc:eee:eneeco:v:36:y:2013:i:c:p:518-525
    DOI: 10.1016/j.eneco.2012.10.009
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    2. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    3. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    4. Nian, Fuzhong & Liu, Jinshuo, 2021. "Feedback driven message spreading on network," Chaos, Solitons & Fractals, Elsevier, vol. 149(C).
    5. Xie Haibin & Zhou Mo & Yu Mei & Hu Yi, 2014. "Forecasting the Crude Oil Price with Extreme Values," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 193-205, June.

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    More about this item

    Keywords

    Financialization; Information diffusion; Component GARCH; Volatility; Oil futures price;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • G1 - Financial Economics - - General Financial Markets
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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