{"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/using-deep-learning-neural-networks-and","title":"Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market","arxiv_id":"1903.12258","date":"2019-02-26","proceeding":null,"authors":["Rosdyana Mangir Irawan Kusuma","Trang-Thi Ho","Wei-Chun Kao","Yu-Yen Ou","Kai-Lung Hua"],"abstract":"Stock market prediction is still a challenging problem because there are many\nfactors effect to the stock market price such as company news and performance,\nindustry performance, investor sentiment, social media sentiment and economic\nfactors. This work explores the predictability in the stock market using Deep\nConvolutional Network and candlestick charts. The outcome is utilized to design\na decision support framework that can be used by traders to provide suggested\nindications of future stock price direction. We perform this work using various\ntypes of neural networks like convolutional neural network, residual network\nand visual geometry group network. From stock market historical data, we\nconverted it to candlestick charts. Finally, these candlestick charts will be\nfeed as input for training a Convolutional Neural Network model. This\nConvolutional Neural Network model will help us to analyze the patterns inside\nthe candlestick chart and predict the future movements of stock market. The\neffectiveness of our method is evaluated in stock market prediction with a\npromising results 92.2% and 92.1% accuracy for Taiwan and Indonesian stock\nmarket dataset respectively. The constructed model have been implemented as a\nweb-based system freely available at http://140.138.155.216/deepcandle/ for\npredicting stock market using candlestick chart and deep learning neural\nnetworks.","url_abs":"http://arxiv.org/abs/1903.12258v1","url_pdf":"http://arxiv.org/pdf/1903.12258v1.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":"using-deep-learning-neural-networks-and","repo_url":"https://github.com/riron1206/candlestick_model","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"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}