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)
59 Downloads (Pure)

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 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
Volume26
Issue number1
Early online date14 Jan 2019
DOIs
Publication statusPublished - Jan 2020

Keywords

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

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Accounting

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