Logo des Repositoriums
 
Textdokument

Adapting Natural Language Processing Strategies for Stock Price Prediction

Lade...
Vorschaubild

Volltext URI

Dokumententyp

Text

Zusatzinformation

Datum

2023

Zeitschriftentitel

ISSN der Zeitschrift

Bandtitel

Verlag

Gesellschaft für Informatik e.V.

Zusammenfassung

Due to the parallels between Natural Language Processing (NLP) and stock price prediction (SPP) as a time series problem, an attempt is made to interpret SPP as an NLP problem. As adaptable techniques word vector representations, pre-trained language models, advanced recurrent neural networks, unsupervised learning methods, and multimodal methods are introduced and it is outlined how they can be transferred into the stock prediction domain.

Beschreibung

Voigt, Frederic (2023): Adapting Natural Language Processing Strategies for Stock Price Prediction. DC@KI2023: Proceedings of Doctoral Consortium at KI 2023. DOI: 10.18420/ki2023-dc-03. Gesellschaft für Informatik e.V.. pp. 20-29. Doctoral Consortium at KI 2023. Berlin. 45195

Zitierform

Tags