Abstract
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.
S. Liu and C. Zhang—The two authors contributed equally to this paper.
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Acknowledgement
This work was supported by the Natural Science Foundation of China for Grant 61171138.
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Liu, S., Zhang, C., Ma, J. (2017). CNN-LSTM Neural Network Model for Quantitative Strategy Analysis in Stock Markets. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10635. Springer, Cham. https://doi.org/10.1007/978-3-319-70096-0_21
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DOI: https://doi.org/10.1007/978-3-319-70096-0_21
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