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Compared with previous neural networks models, the recurrent neural network can better use the previous information to infer subsequent events, which is more suitable for price time series analysis. Long Short-Term Memory (LSTM) has made structural changes to the RNN to avoid long-term dependency problems. The empirical research uses the 2010\u20132017 price panel data of four kinds of soybean futures in China\u2019s futures market, and confirms the model\u2019s improved predictive ability through statistical tests. The empirical analysis of futures trading verifies the practice of these model strategies in terms of risked return. This paper improves and expands the application of recurrent neural networks model, and provides a new idea for applying artificial neural network algorithm to futures trading.<\/jats:p>","DOI":"10.3233\/jifs-179280","type":"journal-article","created":{"date-parts":[[2019,6,28]],"date-time":"2019-06-28T13:07:11Z","timestamp":1561727231000},"page":"4477-4484","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["A novel recurrent neural network algorithm with long short-term memory model for futures trading"],"prefix":"10.1177","volume":"37","author":[{"given":"Quan","family":"Gu","sequence":"first","affiliation":[{"name":"School of Economics and Management, Tongji University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Economics and Management, Xi\u2019an Aeronautical University, Xi\u2019an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Management, Wuhan University of Technology, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,6,27]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1096-9934(199812)18:8<965::AID-FUT5>3.0.CO;2-A"},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/TSMCC.2008.2007255","article-title":"Integrating a Piecewise Linear Representation Method and a Neural Network Model for Stock Trading Points Prediction","volume":"39","author":"Chang P.C.","year":"2008","unstructured":"ChangP.C., FanC.Y. and LiuC.H., Integrating a Piecewise Linear Representation Method and a Neural Network Model for Stock Trading Points Prediction, IEEE Transactions on Systems Man & Cybernetics Part C 39.1 (2008), 80\u201392.","journal-title":"IEEE Transactions on Systems Man & Cybernetics Part C"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.08.077"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2012.05.039"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mcm.2013.02.002"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.03.023"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.07.116"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.08.019"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1080\/1351847X.2011.606990"},{"key":"e_1_3_1_11_2","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1007\/s10489-007-0052-4","article-title":"A novel recurrent neural network-based prediction system for option trading and hedging","volume":"29","author":"Quek C.","year":"2008","unstructured":"QuekC., PasquierM. and KumarN., A novel recurrent neural network-based prediction system for option trading and hedging, Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies 29.2 (2008), 138\u2013151.","journal-title":"Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.03.002"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1080\/1351847X.2013.830140"}],"container-title":["Journal of Intelligent &amp; 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