A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD

The stock market is a chaotic, complex, and dynamic financial market. The prediction of future stock prices is a concern and controversial research issue for researchers. More and more analysis and prediction methods are proposed by researchers. We proposed a hybrid method for the prediction of futu...

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Main Authors: Yang Yujun, Yang Yimei, Xiao Jianhua
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/6431712
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author Yang Yujun
Yang Yimei
Xiao Jianhua
author_facet Yang Yujun
Yang Yimei
Xiao Jianhua
author_sort Yang Yujun
collection DOAJ
description The stock market is a chaotic, complex, and dynamic financial market. The prediction of future stock prices is a concern and controversial research issue for researchers. More and more analysis and prediction methods are proposed by researchers. We proposed a hybrid method for the prediction of future stock prices using LSTM and ensemble EMD in this paper. We use comprehensive EMD to decompose the complex original stock price time series into several subsequences which are smoother, more regular and stable than the original time series. Then, we use the LSTM method to train and predict each subsequence. Finally, we obtained the prediction values of the original stock price time series by fused the prediction values of several subsequences. In the experiment, we selected five data to fully test the performance of the method. The comparison results with the other four prediction methods show that the predicted values show higher accuracy. The hybrid prediction method we proposed is effective and accurate in future stock price prediction. Hence, the hybrid prediction method has practical application and reference value.
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institution Kabale University
issn 1076-2787
1099-0526
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-9bd1062fff3249dfb14e138c2e90956d2025-02-03T05:52:24ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/64317126431712A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMDYang Yujun0Yang Yimei1Xiao Jianhua2School of Computer Science and Engineering, Huaihua University, Huaihua 418008, ChinaSchool of Computer Science and Engineering, Huaihua University, Huaihua 418008, ChinaSchool of Computer Science and Engineering, Huaihua University, Huaihua 418008, ChinaThe stock market is a chaotic, complex, and dynamic financial market. The prediction of future stock prices is a concern and controversial research issue for researchers. More and more analysis and prediction methods are proposed by researchers. We proposed a hybrid method for the prediction of future stock prices using LSTM and ensemble EMD in this paper. We use comprehensive EMD to decompose the complex original stock price time series into several subsequences which are smoother, more regular and stable than the original time series. Then, we use the LSTM method to train and predict each subsequence. Finally, we obtained the prediction values of the original stock price time series by fused the prediction values of several subsequences. In the experiment, we selected five data to fully test the performance of the method. The comparison results with the other four prediction methods show that the predicted values show higher accuracy. The hybrid prediction method we proposed is effective and accurate in future stock price prediction. Hence, the hybrid prediction method has practical application and reference value.http://dx.doi.org/10.1155/2020/6431712
spellingShingle Yang Yujun
Yang Yimei
Xiao Jianhua
A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
Complexity
title A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
title_full A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
title_fullStr A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
title_full_unstemmed A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
title_short A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD
title_sort hybrid prediction method for stock price using lstm and ensemble emd
url http://dx.doi.org/10.1155/2020/6431712
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