Enhanced prediction of stock markets using a novel deep learning model PLSTM-TAL in urbanized smart cities

Accurate predictions of stock markets are important for investors and other stakeholders of the equity markets to formulate profitable investment strategies. The improved accuracy of a prediction model even with a slight margin can translate into considerable monetary returns. However, the stock mar...

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Bibliographic Details
Published in:	Heliyon Vol. 10; no. 6; p. e27747
Main Authors:	Latif, Saima, Javaid, Nadeem, Aslam, Faheem, Aldegheishem, Abdulaziz, Alrajeh, Nabil, Bouk, Safdar Hussain
Format:	Journal Article
Language:	English
Published:	England Elsevier Ltd 30.03.2024 Elsevier
Subjects:	Bayesian optimization China Contractive autoencoder data collection Ensemble empirical mode decomposition India Peephole LSTM prediction stakeholders stock exchange Stock market prediction Temporal attention layer Time series Urban planing urbanization China India Contractive autoencoder Urban planing Peephole LSTM Temporal attention layer Time series Ensemble empirical mode decomposition Bayesian optimization Stock market prediction
ISSN:	2405-8440, 2405-8440
Online Access:	Get full text
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