Uncovering predictability in the evolution of the WTI oil futures curve

Fearghal Kearney*, Han Lin Shang

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.
Original languageEnglish
Pages (from-to)238-257
Number of pages20
JournalEuropean Financial Management
Volume26
Issue number1
DOIs
Publication statusPublished - 14 Jan 2020
Externally publishedYes

Keywords

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

Fingerprint Dive into the research topics of 'Uncovering predictability in the evolution of the WTI oil futures curve'. Together they form a unique fingerprint.

Cite this