A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting

The primary purpose of trading in stock markets is to profit from buying and selling listed stocks. However, numerous factors can influence the stock prices, such as the company's present financial situation, news, rumor, macroeconomics, psychological, economic, political, and geopolitical fact...

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Main Authors: Fathi, A.Y., El-Khodary, I.A., Saafan, M.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29588 /
Published: International Information and Engineering Technology Association 2021
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122723136&doi=10.18280%2fria.350606&partnerID=40&md5=bff149351800e7e03ea25cb8fe2bf06a
http://eprints.utp.edu.my/29588/
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spelling utp-eprints.295882022-03-25T02:09:56Z A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting Fathi, A.Y. El-Khodary, I.A. Saafan, M. The primary purpose of trading in stock markets is to profit from buying and selling listed stocks. However, numerous factors can influence the stock prices, such as the company's present financial situation, news, rumor, macroeconomics, psychological, economic, political, and geopolitical factors. Consequently, tremendous challenges already exist in predicting noisy stock prices. This paper proposes a hybrid model integrating the singular spectrum analysis (SSA) and the backpropagation neural network (BPNN) to forecast daily closing prices in stock markets. The model first decomposes the stock prices into several components using the SSA. Then, the extracted components are utilized for training BPNNs to forecast future prices. Compared with the BPNN, the hybrid SSA-BPNN model demonstrates a better predictive performance, indicating the SSA's ability to extract hidden information and reduce the noise effect of the original time series. © 2021 Lavoisier. All rights reserved. International Information and Engineering Technology Association 2021 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122723136&doi=10.18280%2fria.350606&partnerID=40&md5=bff149351800e7e03ea25cb8fe2bf06a Fathi, A.Y. and El-Khodary, I.A. and Saafan, M. (2021) A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting. Revue d'Intelligence Artificielle, 35 (6). pp. 483-488. http://eprints.utp.edu.my/29588/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The primary purpose of trading in stock markets is to profit from buying and selling listed stocks. However, numerous factors can influence the stock prices, such as the company's present financial situation, news, rumor, macroeconomics, psychological, economic, political, and geopolitical factors. Consequently, tremendous challenges already exist in predicting noisy stock prices. This paper proposes a hybrid model integrating the singular spectrum analysis (SSA) and the backpropagation neural network (BPNN) to forecast daily closing prices in stock markets. The model first decomposes the stock prices into several components using the SSA. Then, the extracted components are utilized for training BPNNs to forecast future prices. Compared with the BPNN, the hybrid SSA-BPNN model demonstrates a better predictive performance, indicating the SSA's ability to extract hidden information and reduce the noise effect of the original time series. © 2021 Lavoisier. All rights reserved.
format Article
author Fathi, A.Y.
El-Khodary, I.A.
Saafan, M.
spellingShingle Fathi, A.Y.
El-Khodary, I.A.
Saafan, M.
A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
author_sort Fathi, A.Y.
title A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
title_short A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
title_full A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
title_fullStr A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
title_full_unstemmed A Hybrid Model Integrating Singular Spectrum Analysis and Backpropagation Neural Network for Stock Price Forecasting
title_sort hybrid model integrating singular spectrum analysis and backpropagation neural network for stock price forecasting
publisher International Information and Engineering Technology Association
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122723136&doi=10.18280%2fria.350606&partnerID=40&md5=bff149351800e7e03ea25cb8fe2bf06a
http://eprints.utp.edu.my/29588/
_version_ 1741197267090538496
score 11.62408

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