Uncovering Predictability in the Evolution of the WTI Oil Futures Curve

Fearghal Kearney, Han Lin Shang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
114 Downloads (Pure)


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 with it residing in the superior set of models in all considered instances.
Original languageEnglish
Pages (from-to)238-257
Number of pages20
JournalEuropean Financial Management
Issue number1
Early online date14 Jan 2019
Publication statusPublished - Jan 2020


  • Forecasting
  • crude oil
  • functional time series
  • futures contracts
  • futures markets

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Accounting


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