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 (Journal of Risk and Financial Management, 2019)
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.
Keywords: 330; crude oil futures prices forecasting; convolutional neural networks; short-term forecasting