{"id":"https://openalex.org/W4391113930","doi":"https://doi.org/10.1109/bigdata59044.2023.10386751","title":"Finformer: A Static-dynamic Spatiotemporal Framework for Stock Trend Prediction","display_name":"Finformer: A Static-dynamic Spatiotemporal Framework for Stock Trend Prediction","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391113930","doi":"https://doi.org/10.1109/bigdata59044.2023.10386751"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386751","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092441998","display_name":"Yi Zu","orcid":"https://orcid.org/0009-0002-0799-0708"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zu","raw_affiliation_strings":["Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102606038","display_name":"Jiacong Mi","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiacong Mi","raw_affiliation_strings":["Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113102018","display_name":"Lingning Song","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingning Song","raw_affiliation_strings":["Southeast University,School of Software Engineering,Nanjing,China","School of Software Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Software Engineering,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Software Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732939","display_name":"Shan Lu","orcid":"https://orcid.org/0000-0001-9849-216X"},"institutions":[{"id":"https://openalex.org/I4210133666","display_name":"Tiandi Science & Technology (China)","ror":"https://ror.org/03ssr6t63","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Lu","raw_affiliation_strings":["Nanjing Fenghuo Tiandi Communication Technology Co., Ltd,Nanjing,China","Nanjing Fenghuo Tiandi Communication Technology Co., Ltd, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Fenghuo Tiandi Communication Technology Co., Ltd,Nanjing,China","institution_ids":["https://openalex.org/I4210133666"]},{"raw_affiliation_string":"Nanjing Fenghuo Tiandi Communication Technology Co., Ltd, Nanjing, China","institution_ids":["https://openalex.org/I4210133666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101699117","display_name":"Jieyue He","orcid":"https://orcid.org/0000-0002-3265-3351"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieyue He","raw_affiliation_strings":["Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Key Lab of Computer Network and Information Integration, MOE, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.236,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62266279,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"1460","last_page":"1469"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6332532167434692},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5283597111701965},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07397252321243286}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6332532167434692},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5283597111701965},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07397252321243286},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386751","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W74101598","https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1574447377","https://openalex.org/W1969852690","https://openalex.org/W2064675550","https://openalex.org/W2090637028","https://openalex.org/W2095219646","https://openalex.org/W2116341502","https://openalex.org/W2157331557","https://openalex.org/W2172073485","https://openalex.org/W2313339984","https://openalex.org/W2613328025","https://openalex.org/W2734777338","https://openalex.org/W2744043447","https://openalex.org/W2792764867","https://openalex.org/W2798413829","https://openalex.org/W2896309423","https://openalex.org/W2945302307","https://openalex.org/W2964413206","https://openalex.org/W2969677753","https://openalex.org/W2985576648","https://openalex.org/W2997848713","https://openalex.org/W3034478396","https://openalex.org/W3035336738","https://openalex.org/W3035414307","https://openalex.org/W3093733835","https://openalex.org/W3099645789","https://openalex.org/W3131543199","https://openalex.org/W3154141829","https://openalex.org/W3160222876","https://openalex.org/W3170487013","https://openalex.org/W3172807453","https://openalex.org/W3175058599","https://openalex.org/W3175177406","https://openalex.org/W3187312953","https://openalex.org/W3208499031","https://openalex.org/W4205550663","https://openalex.org/W4224316292","https://openalex.org/W4224917168","https://openalex.org/W4226142228","https://openalex.org/W4231449374","https://openalex.org/W4289744562","https://openalex.org/W4302307947","https://openalex.org/W4306317230","https://openalex.org/W4306317752","https://openalex.org/W4385245566","https://openalex.org/W4385767800","https://openalex.org/W6631190155","https://openalex.org/W6739901393","https://openalex.org/W6749825310","https://openalex.org/W6767528804","https://openalex.org/W6803067837"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0,13,215],"core":[1],"of":[2,16,204,213],"quantitative":[3],"investment":[4],"lies":[5],"in":[6,10,43,84,99,135,181,191,207],"predicting":[7],"future":[8,14],"trends":[9],"stock":[11,18,40,137,169],"prices.":[12],"trend":[15,41],"a":[17,89,95,110],"is":[19],"closely":[20],"related":[21],"to":[22,27,101,114,129],"the":[23,51,58,77,85,136,178,182,192,202,208,211],"industry":[24],"it":[25,121],"belongs":[26],"and":[28,125,143,184,197,210],"its":[29],"relationship":[30],"with":[31],"other":[32],"stocks.":[33,62],"Although":[34],"some":[35],"research":[36,64],"has":[37,65,87],"focused":[38],"on":[39,159,166],"prediction":[42],"recent":[44],"years,":[45],"most":[46],"studies":[47],"have":[48],"only":[49,71],"considered":[50,72],"stock\u2019s":[52],"own":[53],"time":[54,105,124],"series":[55,106],"feature,":[56],"neglecting":[57],"spatial":[59,67,82,118,133,142],"features":[60,134,157],"between":[61],"Some":[63],"incorporated":[66],"information,":[68],"but":[69],"typically":[70],"predefined":[73,127],"static":[74],"relationships.":[75],"At":[76],"same":[78],"time,":[79],"capturing":[80],"dynamic":[81,116],"information":[83,119],"market":[86,117,160,170],"been":[88],"long-standing":[90],"challenge.":[91],"Thus,":[92],"we":[93,146],"propose":[94],"spatio-temporal":[96,150,156],"model,":[97],"Finformer,":[98],"order":[100],"go":[102],"beyond":[103],"traditional":[104],"models.":[107],"We":[108],"designed":[109],"sparse":[111],"static-dynamic":[112],"transformer":[113],"capture":[115],"as":[120],"changes":[122],"over":[123],"combined":[126],"relationships":[128],"extract":[130],"highly":[131],"correlated":[132],"market.":[138],"To":[139],"effectively":[140],"integrate":[141],"temporal":[144],"features,":[145],"introduced":[147],"an":[148],"adaptive":[149],"fusion":[151],"module":[152,206],"that":[153,173],"dynamically":[154],"fuses":[155],"based":[158],"conditions":[161],"at":[162],"different":[163],"periods.":[164],"Experiments":[165],"two":[167],"real-world":[168],"datasets":[171],"show":[172],"our":[174],"proposed":[175],"model":[176,209],"outperforms":[177],"state-of-the-art":[179],"baselines":[180],"signal-based":[183],"portfolio-based":[185],"metrics,":[186],"which":[187],"are":[188],"widely":[189],"concerned":[190],"financial":[193],"field.":[194],"Ablation":[195],"study":[196,199],"hyper-parameter":[198],"further":[200],"reveal":[201],"effectiveness":[203],"each":[205],"impact":[212],"hyper-parameters.":[214],"code":[216],"will":[217],"be":[218],"made":[219],"publicly":[220],"available.":[221],"<sup":[222],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[223],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[224]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}