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Hybrid deep learning and ARIMA model for prediction Egyptian stock exchange
Author
Source
Scientific Journal for Commerce and Finance
Issue
Vol. 43, Issue 1، ج. 2 (31 Mar. 2023), pp.336-355, 20 p.
Publisher
Tanta University Faculty of Commerce
Publication Date
2023-03-31
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
The autoregressive integrated moving average (ARIMA) is a flexible, good, and simple linear model for forecasting and time series analysis.
some time series forecasting researches also propose the artificial neural network (ANN) model as a substitute nonlinear forecasting model.
the ARIMA model is good at capturing linear patterns, but the ANN model is effective at capturing nonlinear patterns.
ANN and ARIMA models were significantly used in the prediction of the Egyptian stock exchange.
both ANN and ARIMA can also be merged as a hybrid model to capitalize on the capabilities of both models in linear and nonlinear modeling.
we use the hybrid model in this research to merge ARIMA models and ANN model (the deep neural network with numerous hidden layers) the Egyptian stock exchange is the actual dataset used.
the initial comparison made between the experimented prediction models for the time horizons of 10 days, 20 days, 30 days, 40 days, and 50 days in advance using the datasets in this work.
to assess performance, statistical measurements for instance mean squared error (MSE), reveal that the DNN-ARIMA hybrid model outperforms non-hybrid models in predicting the Egyptian stock exchange and is particularly effective in improving prediction accuracy.
American Psychological Association (APA)
Mahmud, Hanan Khadari Mahdi. 2023. Hybrid deep learning and ARIMA model for prediction Egyptian stock exchange. Scientific Journal for Commerce and Finance،Vol. 43, no. 1، ج. 2, pp.336-355.
https://search.emarefa.net/detail/BIM-1516174
Modern Language Association (MLA)
Mahmud, Hanan Khadari Mahdi. Hybrid deep learning and ARIMA model for prediction Egyptian stock exchange. Scientific Journal for Commerce and Finance Vol. 43, no. 1, p. 2 (Mar. 2023), pp.336-355.
https://search.emarefa.net/detail/BIM-1516174
American Medical Association (AMA)
Mahmud, Hanan Khadari Mahdi. Hybrid deep learning and ARIMA model for prediction Egyptian stock exchange. Scientific Journal for Commerce and Finance. 2023. Vol. 43, no. 1، ج. 2, pp.336-355.
https://search.emarefa.net/detail/BIM-1516174
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references: p. 353-355
Record ID
BIM-1516174