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

  • Shuanglong Liu
  • Chao Zhang
  • Jinwen MaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10635)

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.

Keywords

Neural network CNN LSTM Quantitative strategy Stock markets 

Notes

Acknowledgement

This work was supported by the Natural Science Foundation of China for Grant 61171138.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Information Science, School of Mathematical Sciences and LMAMPeking UniversityBeijingChina
  2. 2.Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina

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