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

• Luo, Zhaojie

• Cai, Xiaojing

• Tanaka, Katsuyuki

• Takiguchi, Tetsuya

• Kinkyo, Takuji

• Hamori, Shigeyuki

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.

Journal

• Journal of Risk and Financial Management

  Journal of Risk and Financial Management 12 (1), 9-9, 2019-03

  MDPI

Keywords

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

Details

• CRID: 1050012570392968960
• NII Article ID: 120006624225
• DOI: 10.3390/jrfm12010009
• ISSN: 19118074
• ISSN: 19118066
• HANDLE: 20.500.14094/90005926
• Web Site: https://www.mdpi.com/1911-8074/12/1/9/pdf
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN