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Can We Forecast Daily Oil Futures Prices? Experimental Evidence from Convolutional Neural Networks

  • Zhaojie Luo
  • , Xiaojing Cai
  • , Katsuyuki Tanaka
  • , Tetsuya Takiguchi
  • , Takuji Kinkyo
  • , Shigeyuki Hamori

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forecasts the short-term crude oil futures prices with good performance. In our study, we confirm that artificial intelligence (AI)-based deep-learning approaches can provide more accurate forecasts of short-term oil prices than those of the benchmark Naive Forecast (NF) model. We also provide strong evidence that CNN models with matrix inputs are better at short-term prediction than neural network (NN) models with single-vector input, which indicates that strengthening the dependence of inputs and providing more useful information can improve short-term forecasting performance.

Original languageEnglish
Article number9
JournalJournal of Risk and Financial Management
Volume12
Issue number1
DOIs
Publication statusPublished - Mar 2019
Externally publishedYes

Keywords

  • convolutional neural networks
  • crude oil futures prices forecasting
  • short-term forecasting

ASJC Scopus subject areas

  • Accounting
  • Business, Management and Accounting (miscellaneous)
  • Finance
  • Economics and Econometrics

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