{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:06:44Z","timestamp":1776182804159,"version":"3.50.1"},"reference-count":8,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,10]]},"DOI":"10.1109\/bigdata.2015.7364089","type":"proceedings-article","created":{"date-parts":[[2015,12,28]],"date-time":"2015-12-28T21:36:21Z","timestamp":1451338581000},"page":"2823-2824","source":"Crossref","is-referenced-by-count":497,"title":["A LSTM-based method for stock returns prediction: A case study of China stock market"],"prefix":"10.1109","author":[{"given":"Kai","family":"Chen","sequence":"first","affiliation":[]},{"given":"Yi","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Fangyan","family":"Dai","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/72.728395"},{"key":"ref3","article-title":"A Critical Review of Recurrent Neural Networks for Sequence Learning","author":"lipton","year":"2015","journal-title":"arXiv preprint arXiv 1506 01070"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1016\/j.eswa.2014.12.003","article-title":"Recurrent neural network and a hybrid model for prediction of stock returns","volume":"42","author":"akhter mohiuddin","year":"2015","journal-title":"Expert Systems with Applications"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1462198.1462204"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2010.12.007"},{"key":"ref2","first-page":"1360","article-title":"State-of-the-art in stock prediction techniques","volume":"2","author":"agrawal","year":"2013","journal-title":"International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering"},{"key":"ref1","article-title":"Financial time series forecasting with machine learning techniques: A survey","author":"krollner","year":"2010"}],"event":{"name":"2015 IEEE International Conference on Big Data (Big Data)","location":"Santa Clara, CA, USA","start":{"date-parts":[[2015,10,29]]},"end":{"date-parts":[[2015,11,1]]}},"container-title":["2015 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7347101\/7363706\/07364089.pdf?arnumber=7364089","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T02:37:10Z","timestamp":1498271830000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7364089\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,10]]},"references-count":8,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2015.7364089","relation":{},"subject":[],"published":{"date-parts":[[2015,10]]}}}