{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T14:28:57Z","timestamp":1746628137840,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811579837"},{"type":"electronic","value":"9789811579844"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-15-7984-4_23","type":"book-chapter","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T12:03:10Z","timestamp":1597924990000},"page":"309-328","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Stock Price Forecasting and Rule Extraction Based on L1-Orthogonal Regularized GRU Decision Tree Interpretation Model"],"prefix":"10.1007","author":[{"given":"Wenjun","family":"Wu","sequence":"first","affiliation":[]},{"given":"Yuechen","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Yue","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xiuli","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"23_CR1","unstructured":"Li, C.: Prediction of stock index futures price based on BP neural network. Master Thesis of Qingdao University, Qingdao (2012)"},{"key":"23_CR2","unstructured":"Yu, Z., Qin, L., Zhao Z., Wen, W.: Stock price prediction based on principal component analysis and generalized regression neural network. Stat. Decis. Making 34(18), 168\u2013171 (2008)"},{"key":"23_CR3","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1111\/j.1540-6261.1970.tb00518.x","volume":"25","author":"BG Malkiel","year":"1970","unstructured":"Malkiel, B.G., Fama, E.F.: Efficient capital markets: a review of theory and empirical work. J. Financ. 25, 383\u2013417 (1970)","journal-title":"J. Financ."},{"key":"23_CR4","volume-title":"Investments","author":"Z Bodie","year":"2014","unstructured":"Bodie, Z., Kane, A., Marcus, A.J.: Investments, 10th edn. McGraw-Hill Education, New York (2014)","edition":"10"},{"key":"23_CR5","unstructured":"Liu, Z., Wang, Y.: An empirical study on the forecasting effectiveness of price-based technical indicators in bull and bear cycles of China\u2019s Shanghai stock market. In: Proceeding of 12th International Conference on Management of e-Commerce and e-Government (ICMECG 2018), pp. 412\u2013417 (2018)"},{"key":"23_CR6","unstructured":"Chen, X., Sun A.: Effectiveness test of CAPM in Chinese stock market. J. Peking Univ. (philosophy and social sciences), 28\u201337 (2000)"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Wang, J.-H., Leu, J.-Y.: Stock market trend prediction using arima-based neural networks. In: IEEE International Conference on Neural Networks, vol. 4, pp. 2160\u20132165. IEEE (1996)","DOI":"10.1109\/ICNN.1996.549236"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"White H.F.: Economic prediction using neural networks: the case of IBM daily stock returns. Earth Surf. Process. Land. 2, 451\u2013458 (1988)","DOI":"10.1109\/ICNN.1988.23959"},{"key":"23_CR9","doi-asserted-by":"crossref","unstructured":"Kimoto, T., Asakawa, K., Yoda, M., Takeoka, M.: Stock market prediction system with modular neural networks. In: 1990 IJCNN International Joint Conference on Neural Networks, vol. 1, pp. 1\u20136 (1990)","DOI":"10.1109\/IJCNN.1990.137535"},{"key":"23_CR10","unstructured":"Yoon, Y., Swales, G.: Predicting stock price performance: a neural network approach. In: Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences, Kauai, HI, USA, vol. 4, pp. 156\u2013162 (1991)"},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Nelson, D.M.Q., Pereira, A.C.M., de Oliveira, R.A.: Stock market\u2019s price movement prediction with LSTM neural networks. In: 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, pp. 1419\u20131426 (2017)","DOI":"10.1109\/IJCNN.2017.7966019"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Gao, S.E., Lin, B.S., Wang, C.: Share price trend prediction using CRNN with LSTM structure. In: 2018 International Symposium on Computer, Consumer and Control (IS3C), Taichung, Taiwan, pp. 10\u201313 (2018)","DOI":"10.1109\/IS3C.2018.00012"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Althelaya, K.A., El-Alfy, E.M., Mohammed, S.: Stock market forecast using multivariate analysis with bidirectional and stacked (LSTM, GRU). In: 2018 21st Saudi Computer Society National Computer Conference (NCC), Riyadh, pp. 1\u20137 (2018)","DOI":"10.1109\/NCG.2018.8593076"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Bach, S., Binder, A., Montavon, G., Klauschen, F., Muller, K.-R., Samek, W.: On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation, PloS ONE, 10(7), e0130140 (2015)","DOI":"10.1371\/journal.pone.0130140"},{"issue":"5","key":"23_CR15","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Statist. 29(5), 1189\u20131232 (2001)","journal-title":"Ann. Statist."},{"key":"23_CR16","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/978-3-319-46307-0_29","volume-title":"Discovery Science","author":"JR Zilke","year":"2016","unstructured":"Zilke, J.R., Loza Menc\u00eda, E., Janssen, F.: DeepRED \u2013 rule extraction from deep neural networks. In: Calders, T., Ceci, M., Malerba, D. (eds.) DS 2016. LNCS (LNAI), vol. 9956, pp. 457\u2013473. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46307-0_29"},{"key":"23_CR17","unstructured":"Lakkaraju, H., et al.: Interpretable & explorable approximations of black box models. arXiv preprint, arXiv:1707.01154 (2017)"},{"key":"23_CR18","unstructured":"Puri, N., et al.: Magix: model agnostic globally interpretable explanations. arXiv preprint, arXiv:1706.07160 (2017)"},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"Wu, M., Hughes, M.C., Parbhoo, S., et al.: Beyond sparsity: tree regularization of deep models for interpretability. In: Proceeding of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 1670\u20131678 (2018)","DOI":"10.1609\/aaai.v32i1.11501"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Schaaf, N., Huber, M.F.: Enhancing decision tree based interpretation of deep neural networks through L1-orthogonal regularization. arXiv preprint, arXiv:1904.05394 (2019)","DOI":"10.1109\/ICMLA.2019.00016"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Feuerriegel, S., Gordon, J.: News-based forecasts of macroeconomic indicators: a semantic path model for interpretable predictions. Eur. J. Oper. Res. 272(1), 162\u2013175 (2019)","DOI":"10.1016\/j.ejor.2018.05.068"},{"issue":"3","key":"23_CR22","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1007\/s00500-017-2800-7","volume":"23","author":"S Rajab","year":"2019","unstructured":"Rajab, S., Sharma, V.: An interpretable neuro-fuzzy approach to stock price forecasting. Soft Comput. J. 23(3), 921\u2013936 (2019). https:\/\/doi.org\/10.1007\/s00500-017-2800-7","journal-title":"Soft Comput. J."},{"key":"23_CR23","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/978-981-15-0121-0_37","volume-title":"Data Science","author":"W Wu","year":"2019","unstructured":"Wu, W., et al.: Preliminary study on interpreting stock price forecasting based on tree regularization of GRU. In: Mao, R., Wang, H., Xie, X., Lu, Z. (eds.) ICPCSEE 2019. CCIS, vol. 1059, pp. 476\u2013487. Springer, Singapore (2019). https:\/\/doi.org\/10.1007\/978-981-15-0121-0_37"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Patel, J., Shah, S., Thakkar, P., et al.: Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Syst. Appl. J. 42(1), 259\u2013268 (2015)","DOI":"10.1016\/j.eswa.2014.07.040"},{"key":"23_CR25","unstructured":"Hong, J.H.: Research on stock price trend prediction based on GBDT model. Jinan university (2017)"},{"key":"23_CR26","doi-asserted-by":"crossref","unstructured":"Granger, C.W.J., Pesaran, M.H.: Economic and statistical measures of forecast accuracy. J. Forecast. 19(7), 537\u2013560 (1999). Cambridge Working Papers in Economics","DOI":"10.1002\/1099-131X(200012)19:7<537::AID-FOR769>3.3.CO;2-7"},{"key":"23_CR27","doi-asserted-by":"publisher","unstructured":"Varma, S., Simon, R.: Bias in error estimation when using cross-validation for model selection. BMC Bioinform. 7(1), 91\u2013100 (2006). https:\/\/doi.org\/10.1186\/1471-2105-7-91","DOI":"10.1186\/1471-2105-7-91"}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-7984-4_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T06:35:27Z","timestamp":1723444527000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-15-7984-4_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811579837","9789811579844"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-7984-4_23","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"20 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPCSEE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of Pioneering Computer Scientists, Engineers and Educators","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiyuan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpcsee2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2020.icpcsee.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"392","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"74","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}