{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T21:13:00Z","timestamp":1786741980842,"version":"build-2736575974"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2019,4,17]],"date-time":"2019-04-17T00:00:00Z","timestamp":1555459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s00521-019-04212-x","type":"journal-article","created":{"date-parts":[[2019,4,17]],"date-time":"2019-04-17T16:41:01Z","timestamp":1555519261000},"page":"1609-1628","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":300,"title":["Stock price prediction based on deep neural networks"],"prefix":"10.1007","volume":"32","author":[{"given":"Pengfei","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuesong","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,4,17]]},"reference":[{"issue":"5","key":"4212_CR1","doi-asserted-by":"publisher","first-page":"1425","DOI":"10.1007\/s00521-017-3296-x","volume":"30","author":"Li Zhang","year":"2018","unstructured":"Zhang Li, Wang Fulin, Bing Xu, Chi Wenyu, Wang Qiongya, Sun Ting (2018) Prediction of stock prices based on LM-BP neural network and the estimation of overfitting point by RDCI. Neural Comput Appl 30(5):1425\u20131444","journal-title":"Neural Comput Appl"},{"issue":"1","key":"4212_CR2","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.neucom.2006.05.008","volume":"70","author":"ALI Oliveira","year":"2006","unstructured":"Oliveira ALI, Meira SRL (2006) Detecting novelties in time series through neural networks forecasting with robust confidence intervals. Neurocomputing 70(1):79\u201392","journal-title":"Neurocomputing"},{"issue":"7553","key":"4212_CR3","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y Lecun","year":"2015","unstructured":"Lecun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436","journal-title":"Nature"},{"key":"4212_CR4","doi-asserted-by":"crossref","unstructured":"White H (1988) Economic prediction using neural networks: the case of IBM daily stock returns 451\u2013458","DOI":"10.1109\/ICNN.1988.23959"},{"key":"4212_CR5","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/S0925-2312(01)00702-0","volume":"50","author":"GP Zhang","year":"2003","unstructured":"Zhang GP (2003) Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50:159\u2013175","journal-title":"Neurocomputing"},{"issue":"3","key":"4212_CR6","doi-asserted-by":"publisher","first-page":"6668","DOI":"10.1016\/j.eswa.2008.08.019","volume":"36","author":"B Vanstone","year":"2009","unstructured":"Vanstone B, Finnie G (2009) An empirical methodology for developing stockmarket trading systems using artificial neural networks. Expert Syst Appl 36(3):6668\u20136680","journal-title":"Expert Syst Appl"},{"issue":"4","key":"4212_CR7","doi-asserted-by":"publisher","first-page":"3884","DOI":"10.1016\/j.eswa.2010.09.049","volume":"38","author":"M Jasemi","year":"2011","unstructured":"Jasemi M, Kimiagari AM, Memariani A (2011) A modern neural network model to do stock market timing on the basis of the ancient investment technique of Japanese Candlestick. Expert Syst Appl 38(4):3884\u20133890","journal-title":"Expert Syst Appl"},{"issue":"14","key":"4212_CR8","doi-asserted-by":"publisher","first-page":"5501","DOI":"10.1016\/j.eswa.2013.04.013","volume":"40","author":"JL Ticknor","year":"2013","unstructured":"Ticknor JL (2013) A Bayesian regularized artificial neural network for stock market forecasting. Expert Syst Appl 40(14):5501\u20135506","journal-title":"Expert Syst Appl"},{"key":"4212_CR9","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.neucom.2014.12.084","volume":"156","author":"J Wang","year":"2015","unstructured":"Wang J (2015) Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks. Neurocomputing 156:68\u201378","journal-title":"Neurocomputing"},{"issue":"06","key":"4212_CR10","first-page":"64","volume":"28","author":"Z Xiong","year":"2011","unstructured":"Xiong Z (2011) Research on RMB exchange rate forecasting model based on combining ARIMA with Neural networks. J Quant Tech Econ 28(06):64\u201376 (in Chinese)","journal-title":"J Quant Tech Econ"},{"issue":"04","key":"4212_CR11","first-page":"703","volume":"50","author":"Q Wu","year":"2013","unstructured":"Wu Q, Wang C, Tang Y (2013) Empirical research on volume-price relationship based on GARCH models and BP neural network. J Sichuan Univ Nat Sci Edn 50(04):703\u2013708 (in Chinese)","journal-title":"J Sichuan Univ Nat Sci Edn"},{"issue":"01","key":"4212_CR12","first-page":"86","volume":"47","author":"X Li","year":"2014","unstructured":"Li X, Zhang Z (2014) Support vector machine method for financial time series prediction based on simultaneous error prediction. J Tianjin Univ Sci Technol 47(01):86\u201394 (in Chinese)","journal-title":"J Tianjin Univ Sci Technol"},{"key":"4212_CR13","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85\u2013117","journal-title":"Neural Netw"},{"key":"4212_CR14","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.neucom.2015.04.071","volume":"167","author":"F Shen","year":"2015","unstructured":"Shen F, Chao J, Zhao J (2015) Forecasting exchange rate using deep belief networks and conjugate gradient method. Neurocomputing 167:243\u2013253","journal-title":"Neurocomputing"},{"key":"4212_CR15","unstructured":"Ding X, Zhang Y, Liu T, et al (2015) Deep learning for event-driven stock prediction. In Twenty-fourth international joint conference on artificial intelligence, pp 2327\u20132333"},{"key":"4212_CR16","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.eneco.2017.05.023","volume":"66","author":"Y Zhao","year":"2017","unstructured":"Zhao Y, Li J, Yu L (2017) A deep learning ensemble approach for crude oil price forecasting. Energy Econ 66:9\u201316","journal-title":"Energy Econ"},{"issue":"2","key":"4212_CR17","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/j.ejor.2016.10.031","volume":"259","author":"C Krauss","year":"2017","unstructured":"Krauss C, Do XA, Huck N (2017) Deep neural networks, gradient-boosted trees, random forests: statistical arbitrage on the S&P 500. Eur J Oper Res 259(2):689\u2013702","journal-title":"Eur J Oper Res"},{"key":"4212_CR18","first-page":"1","volume":"49","author":"Y Song","year":"2018","unstructured":"Song Y, Lee JW, Lee J (2018) A study on novel filtering and relationship between input-features and target-vectors in a deep learning model for stock price prediction. Appl Intell 49:1\u201315","journal-title":"Appl Intell"},{"key":"4212_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ACCESS.2018.2812929","volume":"6","author":"DL Minh","year":"2018","unstructured":"Minh DL, Sadeghi-Niaraki A, Huy HD et al (2018) Deep learning approach for short-term stock trends prediction based on two-stream gated recurrent unit network. IEEE Access 6:1\u20131","journal-title":"IEEE Access"},{"issue":"2","key":"4212_CR20","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1007\/s00521-017-3089-2","volume":"31","author":"M G\u00f6\u00e7ken","year":"2019","unstructured":"G\u00f6\u00e7ken M, \u00d6z\u00e7alici M, Boru A, Dosdogru AT (2019) Stock price prediction using hybrid soft computing models incorporating parameter tuning and input variable selection. Neural Comput Appl 31(2):577\u2013592","journal-title":"Neural Comput Appl"},{"key":"4212_CR21","unstructured":"Graves A, Jaitly N (2014) Towards end-to-end speech recognition with recurrent neural networks. In: International conference on machine learning, pp 1764\u20131772"},{"key":"4212_CR22","first-page":"1","volume":"28","author":"K Greff","year":"2016","unstructured":"Greff K, Srivastava RK, Koutnik J et al (2016) LSTM: a search space Odyssey. IEEE Trans Neural Netw 28:1\u201311","journal-title":"IEEE Trans Neural Netw"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04212-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04212-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04212-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,15]],"date-time":"2020-04-15T23:25:05Z","timestamp":1586993105000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04212-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,17]]},"references-count":22,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["4212"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04212-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,17]]},"assertion":[{"value":"17 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 April 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"No conflicts of interest of this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}