Stock Market Prediction based on Deep Long Short Term Memory Neural Network

Xiongwen Pang, Yanqiang Zhou, Pan Wang, Weiwei Lin, Victor Chang

2018

Abstract

To study the influence of market characteristics on stock prices, traditional neural network algorithm may also fail to predict the stock market precisely, since the initial weight of the random selection problem can be easily prone to incorrect predictions. Based on the idea of word vector in deep learning, we demonstrate the concept of stock vector. The input is no longer a single index or single stock index, but multi-stock high-dimensional historical data. We propose the deep long-short term memory neural network (LSMN) with embedded layer to predict the stock market. In this model, we use the embedded layer to vectorize the data, in a bid to forecast the stock via long-short term memory neural network. The experimental results show that the deep long short term memory neural network with embedded layer is state-of-the-art in developing countries. Specifically, the accuracy of this model is 57.2% for the Shanghai A-shares composite index. Furthermore, this is 52.4% for individual stocks.

Paper Citation

in Harvard Style

Pang X., Zhou Y., Wang P., Lin W. and Chang V. (2018). Stock Market Prediction based on Deep Long Short Term Memory Neural Network.In Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS, ISBN 978-989-758-297-4, pages 102-108. DOI: 10.5220/0006749901020108

in Bibtex Style

@conference{complexis18,
author={Xiongwen Pang and Yanqiang Zhou and Pan Wang and Weiwei Lin and Victor Chang},
title={Stock Market Prediction based on Deep Long Short Term Memory Neural Network},
booktitle={Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,},
year={2018},
pages={102-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006749901020108},
isbn={978-989-758-297-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,
TI - Stock Market Prediction based on Deep Long Short Term Memory Neural Network
SN - 978-989-758-297-4
AU - Pang X.
AU - Zhou Y.
AU - Wang P.
AU - Lin W.
AU - Chang V.
PY - 2018
SP - 102
EP - 108
DO - 10.5220/0006749901020108