{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:01:09Z","timestamp":1774540869882,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"abstract":"<jats:p>Stock Trend Prediction(STP) has drawn wide attention from various fields, especially Artificial Intelligence. Most previous studies are single-scale oriented which results in information loss from a multi-scale perspective. In fact, multi-scale behavior is vital for making intelligent investment decisions. A mature investor will thoroughly investigate the state of a stock market at various time scales. To automatically learn the multi-scale information in stock data, we propose a Multi-scale Two-way Deep Neural Network. It learns multi-scale patterns from two types of scale-information, wavelet-based and downsampling-based, by eXtreme Gradient Boosting and Recurrent Convolutional Neural Network, respectively. After combining the learned patterns from the two-way, our model achieves state-of-the-art performance on FI-2010 and CSI-2016, where the latter is our published long-range stock dataset to help future studies for STP task. Extensive experimental results on the two datasets indicate that multi-scale information can significantly improve the STP performance and our model is superior in capturing such information.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/628","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T12:12:10Z","timestamp":1594210330000},"page":"4555-4561","source":"Crossref","is-referenced-by-count":42,"title":["Multi-scale Two-way Deep Neural Network for Stock Trend Prediction"],"prefix":"10.24963","author":[{"given":"Guang","family":"Liu","sequence":"first","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."},{"name":"School of Computer Science, Beijing University of Posts and Telecommunications"}]},{"given":"Yuzhao","family":"Mao","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."},{"name":"School of Computer Science, Beijing University of Posts and Telecommunications"}]},{"given":"Qi","family":"Sun","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."}]},{"given":"Hailong","family":"Huang","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."}]},{"given":"Weiguo","family":"Gao","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."}]},{"given":"Xuan","family":"Li","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."}]},{"given":"Jianping","family":"Shen","sequence":"additional","affiliation":[{"name":"PingAn Life Insurance Company of China, Ltd."}]},{"given":"Ruifan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Beijing University of Posts and Telecommunications"}]},{"given":"Xiaojie","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Beijing University of Posts and Telecommunications"}]}],"member":"10584","event":{"name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","theme":"Artificial Intelligence","location":"Yokohama, Japan","acronym":"IJCAI-PRICAI-2020","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2020,7,11]]},"end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T02:16:21Z","timestamp":1594260981000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/628"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/628","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}