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Adapting Natural Language Processing Strategies for Stock Price Prediction
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2023
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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.