Voigt, FredericStolzenburg, Frieder2023-09-202023-09-202023https://dl.gi.de/handle/20.500.12116/42403Due 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.enStock Price Prediction; Financial Analysis; Quantitative Analysis; Fundamental Analysis; NLPText10.18420/ki2023-dc-03