Forecasting Crude Oil Prices: a Deep Learning based Model
Yanhui Chen, Kaijian He, Kwok Fai Tso
Shanghai Maritime University Hunan University of Science and Technology Beijing University of Chemical Technology City University of Hong Kong
内容与影响
With the popularity of the deep learning model in the engineering fields, it has attracted significant research interests in the economic and finance fields. In this paper, we use the deep learning model to capture the unknown complex nonlinear characteristics of the crude oil price movement. We further propose a new hybrid crude oil price forecasting model based on the deep learning model. Using the proposed model, major crude oil price movement is analyzed and modeled. The performance of the proposed model is evaluated using the price data in the WTI crude oil markets. The empirical results show that the proposed model achieves the improved forecasting accuracy.
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经济 / 管理Market Dynamics and Volatility
Petroleum Processing and Analysis · Stock Market Forecasting Methods
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