{"id":"https://openalex.org/W4401882512","doi":"https://doi.org/10.1145/3677892.3677921","title":"European option pricing Prediction under time-varying Brown Motion Based on LSTM Hybrid Neural Network","display_name":"European option pricing Prediction under time-varying Brown Motion Based on LSTM Hybrid Neural Network","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4401882512","doi":"https://doi.org/10.1145/3677892.3677921"},"language":"en","primary_location":{"id":"doi:10.1145/3677892.3677921","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677892.3677921","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677892.3677921?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Digital Society and Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3677892.3677921?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035489770","display_name":"Zhaohong Chen","orcid":"https://orcid.org/0009-0004-6653-0386"},"institutions":[{"id":"https://openalex.org/I201459984","display_name":"Guangdong University Of Finances and Economics","ror":"https://ror.org/0459pv085","country_code":"CN","type":"education","lineage":["https://openalex.org/I201459984"]},{"id":"https://openalex.org/I4210149618","display_name":"Guangdong University of Finance","ror":"https://ror.org/04grzdh47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohong Chen","raw_affiliation_strings":["School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China"],"raw_orcid":"https://orcid.org/0009-0004-6653-0386","affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China","institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075637896","display_name":"Xiaolong Chai","orcid":"https://orcid.org/0009-0002-4405-7909"},"institutions":[{"id":"https://openalex.org/I201459984","display_name":"Guangdong University Of Finances and Economics","ror":"https://ror.org/0459pv085","country_code":"CN","type":"education","lineage":["https://openalex.org/I201459984"]},{"id":"https://openalex.org/I4210149618","display_name":"Guangdong University of Finance","ror":"https://ror.org/04grzdh47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Chai","raw_affiliation_strings":["School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China"],"raw_orcid":"https://orcid.org/0009-0002-4405-7909","affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Institute of Artificial Intelligence and Deep Learning, Guangdong University of Finance and Economics, China","institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19072042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"162","last_page":"165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9472000002861023,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6914686560630798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6552339196205139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46221891045570374},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.46139949560165405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35443419218063354}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6914686560630798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6552339196205139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46221891045570374},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.46139949560165405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35443419218063354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3677892.3677921","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677892.3677921","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677892.3677921?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Digital Society and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3677892.3677921","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677892.3677921","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677892.3677921?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Digital Society and Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320327557","display_name":"National Office for Philosophy and Social Sciences","ror":"https://ror.org/04m0ms912"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401882512.pdf","grobid_xml":"https://content.openalex.org/works/W4401882512.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1598847143","https://openalex.org/W1980927662","https://openalex.org/W2551963108","https://openalex.org/W2566350482","https://openalex.org/W2967081336","https://openalex.org/W3023654868","https://openalex.org/W3167826074","https://openalex.org/W4253471394"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"On":[0],"the":[1,5,39,44,85],"basis":[2],"of":[3,43],"analyzing":[4],"three":[6],"major":[7],"index":[8],"systems,":[9],"this":[10,89],"article":[11,90],"establishes":[12],"a":[13,25],"time-varying":[14,26],"LSTM-BS":[15],"model":[16,86],"and":[17,56,61,78,103],"achieves":[18],"prediction":[19],"function":[20],"by":[21],"comparing":[22],"it":[23],"with":[24,67],"LSTM":[27],"mixed":[28,71],"dual":[29,72],"fraction":[30,73],"model.":[31],"Further":[32],"empirical":[33],"analysis":[34],"will":[35,64],"be":[36,65],"conducted":[37,66],"on":[38],"historical":[40],"closing":[41],"prices":[42],"Shanghai":[45],"Stock":[46],"Exchange":[47],"50":[48],"ETF":[49],"Index,":[50,55,60],"Hong":[51],"Kong":[52],"Hang":[53],"Seng":[54],"Japan":[57],"Eastern":[58],"Composite":[59],"comparative":[62],"studies":[63],"traditional":[68],"BS":[69],"models,":[70,77],"Brown":[74],"motion":[75],"pricing":[76,96],"other":[79],"models.":[80],"The":[81],"results":[82],"showed":[83],"that":[84],"constructed":[87],"in":[88,94,99],"has":[91,104],"significant":[92],"advantages":[93],"option":[95],"accuracy,":[97],"especially":[98],"developed":[100],"securities":[101],"markets,":[102],"strong":[105],"predictive":[106],"ability.":[107]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}