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

Bruce J Vanstone, Adrian Gepp, Geoffrey Harris

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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
JournalApplied Intelligence
Early online date9 Apr 2019
DOIs
Publication statusE-pub ahead of print - 9 Apr 2019

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Network architecture
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abstract = "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.",
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Do News and Sentiment play a role in Stock Price Prediction? / Vanstone, Bruce J; Gepp, Adrian; Harris, Geoffrey.

In: Applied Intelligence, 09.04.2019.

Research output: Contribution to journalArticleResearchpeer-review

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