Can We Forecast Daily Oil Futures Prices? Experimental Evidence from Convolutional Neural Networks
Can We Forecast Daily Oil Futures Prices? Experimental Evidence from Convolutional Neural Networks
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DOI：
10.3390/jrfm12010009
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发表时间：
2019-01
影响因子：
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通讯作者：
Zhaojie Luo;X. Cai;Katsuyuki Tanaka;T. Takiguchi;Takuji Kinkyo;S. Hamori
中科院分区：
文献类型：
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作者：
Zhaojie Luo;X. Cai;Katsuyuki Tanaka;T. Takiguchi;Takuji Kinkyo;S. Hamori
本文提出了一种新的方法，基于卷积神经网络（CNN）模型，预测短期原油期货价格具有良好的性能。在我们的研究中，我们证实了基于人工智能（AI）的深度学习方法可以提供比基准朴素预测（NF）模型更准确的短期油价预测。我们还提供了强有力的证据，证明具有矩阵输入的CNN模型比具有单向量输入的神经网络（NN）模型更好地进行短期预测，这表明加强输入的依赖性并提供更多有用的信息可以提高短期预测性能。
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.