{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/leveraging-financial-news-for-stock-trend","title":"Leveraging Financial News for Stock Trend Prediction with Attention-Based Recurrent Neural Network","arxiv_id":"1811.06173","date":"2018-11-15","proceeding":null,"authors":["Huicheng Liu"],"abstract":"Stock market prediction is one of the most attractive research topic since\nthe successful prediction on the market's future movement leads to significant\nprofit. Traditional short term stock market predictions are usually based on\nthe analysis of historical market data, such as stock prices, moving averages\nor daily returns. However, financial news also contains useful information on\npublic companies and the market. Existing methods in finance literature exploit\nsentiment signal features, which are limited by not considering factors such as\nevents and the news context. We address this issue by leveraging deep neural\nmodels to extract rich semantic features from news text. In particular, a\nBidirectional-LSTM are used to encode the news text and capture the context\ninformation, self attention mechanism are applied to distribute attention on\nmost relative words, news and days. In terms of predicting directional changes\nin both Standard & Poor's 500 index and individual companies stock price, we\nshow that this technique is competitive with other state of the art approaches,\ndemonstrating the effectiveness of recent NLP technology advances for\ncomputational finance.","url_abs":"http://arxiv.org/abs/1811.06173v1","url_pdf":"http://arxiv.org/pdf/1811.06173v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"leveraging-financial-news-for-stock-trend","repo_url":"https://github.com/maobubu/stock-prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"stock-market-prediction","task_name":"Stock Market Prediction"},{"task_slug":"stock-trend-prediction","task_name":"Stock Trend Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1811.06173","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}