Do News and Sentiment play a role in Stock Price Prediction?

Bruce J Vanstone, Adrian Gepp, Geoffrey Harris

Research output: Contribution to journalArticleResearchpeer-review

18 Citations (Scopus)
273 Downloads (Pure)


Despite continuous improvement in the range and quality of machine learning techniques, accurately predicting stock prices still remains as elusive as ever. We approach this problem using a modern autoregressive neural network architecture and incorporate sentiment predictors, which are becoming increasingly available due to advances in text mining techniques. We find that the inclusion of predictors based on counts of the number of news articles and twitter posts can significantly improve the quality of stock price predictions.
Original languageEnglish
Pages (from-to)3815-3820
Number of pages6
JournalApplied Intelligence
Issue number11
Early online date9 Apr 2019
Publication statusPublished - 1 Nov 2019


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