An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1573-7721

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis ; day:28 ; month:11 ; year:2022 ; pages:1-33
Multimedia tools and applications ; (28.11.2022), 1-33

Classification: Wirtschaft

Creator: Sharaf, Marwa
Hemdan, Ezz El-Din
El-Sayed, Ayman
El-Bahnasawy, Nirmeen A.

Contributor: SpringerLink (Online service)

DOI: 10.1007/s11042-022-14216-w

URN: urn:nbn:de:101:1-2023021109062734854764

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 11:02 AM CEST

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Sharaf, Marwa
Hemdan, Ezz El-Din
El-Sayed, Ayman
El-Bahnasawy, Nirmeen A.
SpringerLink (Online service)

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An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis

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