A novel interval dual convolutional neural network method for interval-valued stock price prediction
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M Jiang, W Chen, H Xu, Y Liu
Pattern Recognition, 2024
Elsevier
Accurate interval-valued stock price prediction is challenging and of great interest to investors and for-profit organizations. In this study, by considering individual stock information and relevant stock information simultaneously, we propose a novel interval dual convolutional neural network (Dual-CNN I) model based method to predict interval-valued stock prices. First, the individual and relevant stock information are collected and transformed into images. Then, the Dual-CNN I model is proposed to predict interval-valued …
