{"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/long-term-stock-prediction-based-on-financial","title":"Long Term Stock Prediction based on Financial Statements","arxiv_id":null,"date":"2021-11-01","proceeding":"journal 2021 11","authors":["Shujia Liu"],"abstract":"This paper proposes a model with LSTM and fully connected layers to predict long term stock trendings based on financial statements. Two data augmentation techniques are applied on structured data: 1) adding random noise to data fields; 2) erasing partial information from training examples. The performance of the proposed approach is demonstrated on real-world data of about 7,000 stocks listed on Nasdaq.","url_abs":"http://cs230.stanford.edu/projects_winter_2021/reports/70728801.pdf","url_pdf":"http://cs230.stanford.edu/projects_winter_2021/reports/70728801.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":"long-term-stock-prediction-based-on-financial","repo_url":"https://github.com/sugia/tradeX","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"stock-prediction","task_name":"Stock Prediction"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}