{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:02:21Z","timestamp":1750309341841,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":13,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T00:00:00Z","timestamp":1716508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,24]]},"DOI":"10.1145\/3677892.3677921","type":"proceedings-article","created":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T16:35:50Z","timestamp":1724690150000},"page":"162-165","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["European option pricing Prediction under time-varying Brown Motion Based on LSTM Hybrid Neural Network"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6653-0386","authenticated-orcid":false,"given":"Zhaohong","family":"Chen","sequence":"first","affiliation":[{"name":"School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4405-7909","authenticated-orcid":false,"given":"Xiaolong","family":"Chai","sequence":"additional","affiliation":[{"name":"School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,8,26]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Andrew W LO. 1991. Long-Term Memory in Stock Market Prices. Econometrica."},{"volume-title":"Fractal Market Analysis: Applying Chaos theory to Investment and Economics","author":"Peters E E","key":"e_1_3_2_1_2_1","unstructured":"Peters E E. 1994. Fractal Market Analysis: Applying Chaos theory to Investment and Economics. J. Wiley. DOI: http:\/\/tainguyenso.vnu.edu.vn\/jspui\/handle\/123456789\/28775."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","unstructured":"C. Houdr\u00e9. Villa J. 2003. An example of infinite dimensional quasi-helix. DOI:10.9774\/GLEAF.978-1-909493-38-4_2.","DOI":"10.9774\/GLEAF.978-1-909493-38-4_2"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","unstructured":"Xu F. 2015. Pricing of European Options under Mixed Bifractional Brownian Motion. 26(01):50-53. DOI: 10.16219\/j.cnki.szxbzk.2015.01.011.","DOI":"10.16219\/j.cnki.szxbzk.2015.01.011"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.3844\/jmssp.2019.185.195"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","unstructured":"Liu D. Huang S. 2016. The Performance of Hybrid Artificial Neural Network Models for Option Pricing during Financial Crises. Journal of Data Science. DOI:10.6339\/JDS.201601_14(1).0001.","DOI":"10.6339\/JDS.201601_14(1).0001"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","unstructured":"Yokoo K. Ishida K. Ercan A. 2022. Capabilities of deep learning models on learning physical relationships: Case of rainfall-runoff modeling with LSTM. Science of The Total Environment. DOI: 10.1016\/J.SCITOTENV.2021.149876.","DOI":"10.1016\/J.SCITOTENV.2021.149876"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/fut.21821"},{"key":"e_1_3_2_1_9_1","unstructured":"Zheng Z X. Wang H R. and Zhu F M. 2019. Research on Jumping Behavior and Volatility Characteristics of the Shanghai Stock Exchange 50ETF Market Based on the Levy GARCH Model. Management Science in China. 2019 27(2):41-52."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbankfin.2020.105845"},{"key":"e_1_3_2_1_11_1","unstructured":"Cheng Y D. Cheng H. and Wang G T. 2017. Pricing of GARCH family European options under time-varying fractional Brownian motion. System engineering theory and practice. 2017 37(10):2527-2538."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.13653\/j.cnki.jqte.2010.01.009"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/0013-4694(51)90043-0"}],"event":{"name":"DSAI 2024: 2024 International Conference on Digital Society and Artificial Intelligence","acronym":"DSAI 2024","location":"Qingdao China"},"container-title":["Proceedings of the 2024 International Conference on Digital Society and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677892.3677921","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3677892.3677921","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:27Z","timestamp":1750291467000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677892.3677921"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,24]]},"references-count":13,"alternative-id":["10.1145\/3677892.3677921","10.1145\/3677892"],"URL":"https:\/\/doi.org\/10.1145\/3677892.3677921","relation":{},"subject":[],"published":{"date-parts":[[2024,5,24]]},"assertion":[{"value":"2024-08-26","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}