Financial Time-Series Data Analysis Using Deep Convolutional Neural Networks

By Jou-Fan Chen, Wei-Lun Chen, Chun-Ping Huang, Szu-Hao Huang, An-Pin Chen. 2016

146 citations recorded by the source corpus.

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Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks (2019, methodology): “With the introduction of deep learning models, methods such as recurrent neural network (RNN) [15], convolutional neural network (CNN) [4], and long short term memory (LSTM) [9] have started appearing on implementations that are used for analyzing ﬁnancial data.”
A Survey of Forex and Stock Price Prediction Using Deep Learning (2021, methodology): “In this table, papers [3,13,16,19,22,23,25,26] used a CNN-based model; papers [34,36,45,50,52–54,56,58,61–64] used an LSTM based model; papers [67,68,74] used a DNN-based model; papers [28,29] used an RNN-based model; and papers [87,89,92] used other deep learning methods.”
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2018, background): “However, there have been but a few published works that adopt CNNs to analyse financial microstructure data [26], [34], [35] and the existing CNN architectures are rather unsophisticated and lack of thorough investigation.”
Developing Arbitrage Strategy in High-frequency Pairs Trading with Filterbank CNN Algorithm (2018, methodology): “The experimental parameters were referenced by [17] where learning rate equal to 0.”
A survey of neural network techniques in market trend analysis (2017, methodology): “Representation of a convolutional network[6].”