Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks

dc.contributor.advisor	Jiang, Hui
dc.creator	Peng, Yangtuo
dc.date.accessioned	2016-09-20T16:58:06Z
dc.date.available	2016-09-20T16:58:06Z
dc.date.copyright	2016-02-16
dc.date.issued	2016-09-20
dc.date.updated	2016-09-20T16:58:06Z
dc.degree.discipline	Computer Science
dc.degree.level	Master's
dc.degree.name	MSc - Master of Science
dc.description.abstract	Financial news contains useful information on public companies and the market. In this paper we apply the popular word embedding methods and deep neural networks to leverage financial news to predict stock price movements in the market. Experimental results have shown that our proposed methods are simple but very effective, which can significantly improve the stock prediction accuracy on a standard financial database over the baseline system using only the historical price information.
dc.identifier.uri	http://hdl.handle.net/10315/32266
dc.language.iso	en
dc.rights	Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subject	Computer science
dc.title	Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks
dc.type	Electronic Thesis or Dissertation

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