CNN-LSTM Neural Network Model for Quantitative Strategy Analysis in Stock Markets

In this paper, the convolutional neural network and long short-term memory (CNN-LSTM) neural network model is proposed to analyse the quantitative strategy in stock markets. Methodically, the CNN-LSTM neural network is used to make the quantitative stock selection strategy for judging stock trends b...

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Bibliographic Details
Published inNeural Information Processing Vol. 10635; pp. 198 - 206
Main Authors Liu, Shuanglong, Zhang, Chao, Ma, Jinwen
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2017
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
CNN
LSTM
Neural network
Quantitative strategy
Stock markets
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Summary:In this paper, the convolutional neural network and long short-term memory (CNN-LSTM) neural network model is proposed to analyse the quantitative strategy in stock markets. Methodically, the CNN-LSTM neural network is used to make the quantitative stock selection strategy for judging stock trends by using the CNN, and then make the quantitative timing strategy for improving the profits by using the LSTM. It is demonstrated by the experiments that the CNN-LSTM neural network model can be successfully applied to making quantitative strategy, and achieving better returns than the basic Momentum strategy and the Benchmark index.
Bibliography:S. Liu and C. Zhang—The two authors contributed equally to this paper.
ISBN:3319700952
9783319700953
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-70096-0_21