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Uncovering predictability in the evolution of the WTI oil futures curve

Author

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  • Fearghal Kearney
  • Han Lin Shang

Abstract

Accurately forecasting the price of oil, the world's most actively traded commodity, is of great importance to both academics and practitioners. We contribute by proposing a functional time series based method to model and forecast oil futures. Our approach boasts a number of theoretical and practical advantages, including effectively exploiting underlying process dynamics missed by classical discrete approaches. We evaluate the finite‐sample performance against established benchmarks using a model confidence set test. A realistic out‐of‐sample exercise provides strong support for the adoption of our approach, which resides in the superior set of models in all considered instances.

Suggested Citation

  • Fearghal Kearney & Han Lin Shang, 2020. "Uncovering predictability in the evolution of the WTI oil futures curve," European Financial Management, European Financial Management Association, vol. 26(1), pages 238-257, January.
  • Handle: RePEc:bla:eufman:v:26:y:2020:i:1:p:238-257
    DOI: 10.1111/eufm.12212
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    Cited by:

    1. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
    2. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    3. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    4. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    5. Qiang Ji & Dayong Zhang & Yuqian Zhao, 2022. "Intra-day co-movements of crude oil futures: China and the international benchmarks," Annals of Operations Research, Springer, vol. 313(1), pages 77-103, June.

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