{"id":"https://openalex.org/W4388994170","doi":"https://doi.org/10.1145/3604237.3626861","title":"Predictability of Post-Earnings Announcement Drift with Textual and Contextual Factors of Earnings Calls","display_name":"Predictability of Post-Earnings Announcement Drift with Textual and Contextual Factors of Earnings Calls","publication_year":2023,"publication_date":"2023-11-25","ids":{"openalex":"https://openalex.org/W4388994170","doi":"https://doi.org/10.1145/3604237.3626861"},"language":"en","primary_location":{"id":"doi:10.1145/3604237.3626861","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626861","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626861","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","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/10.1145/3604237.3626861","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018674878","display_name":"Andy Chung","orcid":"https://orcid.org/0009-0009-2446-7506"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Andy Chung","raw_affiliation_strings":["Department of Advanced Interdisciplinary Studies, Graduate School of Engineering, The University of Tokyo, JP"],"raw_orcid":"https://orcid.org/0009-0009-2446-7506","affiliations":[{"raw_affiliation_string":"Department of Advanced Interdisciplinary Studies, Graduate School of Engineering, The University of Tokyo, JP","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073822077","display_name":"Kumiko Tanaka\u2010Ishii","orcid":"https://orcid.org/0000-0003-1752-3951"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kumiko Tanaka-Ishii","raw_affiliation_strings":["Department of Computer Science and Engineering, School of Fundamental Science and Engineering, Waseda University, JP"],"raw_orcid":"https://orcid.org/0000-0003-1752-3951","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, School of Fundamental Science and Engineering, Waseda University, JP","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"401","last_page":"408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/post-earnings-announcement-drift","display_name":"Post-earnings-announcement drift","score":0.8872270584106445},{"id":"https://openalex.org/keywords/earnings","display_name":"Earnings","score":0.8246164321899414},{"id":"https://openalex.org/keywords/earnings-surprise","display_name":"Earnings surprise","score":0.7816709280014038},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6747342348098755},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.5474898219108582},{"id":"https://openalex.org/keywords/predictability","display_name":"Predictability","score":0.5384430885314941},{"id":"https://openalex.org/keywords/earnings-response-coefficient","display_name":"Earnings response coefficient","score":0.4961260259151459},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.46221014857292175},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.45408040285110474},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.4298381209373474},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4293639361858368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35244160890579224},{"id":"https://openalex.org/keywords/accounting","display_name":"Accounting","score":0.25255411863327026},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13885006308555603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12060967087745667},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1145336925983429}],"concepts":[{"id":"https://openalex.org/C147808555","wikidata":"https://www.wikidata.org/wiki/Q7233519","display_name":"Post-earnings-announcement drift","level":4,"score":0.8872270584106445},{"id":"https://openalex.org/C2781426361","wikidata":"https://www.wikidata.org/wiki/Q5326940","display_name":"Earnings","level":2,"score":0.8246164321899414},{"id":"https://openalex.org/C2778357720","wikidata":"https://www.wikidata.org/wiki/Q17147211","display_name":"Earnings surprise","level":5,"score":0.7816709280014038},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6747342348098755},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.5474898219108582},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.5384430885314941},{"id":"https://openalex.org/C190775180","wikidata":"https://www.wikidata.org/wiki/Q5326946","display_name":"Earnings response coefficient","level":3,"score":0.4961260259151459},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.46221014857292175},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.45408040285110474},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.4298381209373474},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4293639361858368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35244160890579224},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.25255411863327026},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13885006308555603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12060967087745667},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1145336925983429},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604237.3626861","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626861","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626861","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3604237.3626861","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604237.3626861","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604237.3626861","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388994170.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W16136587","https://openalex.org/W28412257","https://openalex.org/W1481128830","https://openalex.org/W1507711477","https://openalex.org/W1645816215","https://openalex.org/W1995834279","https://openalex.org/W2001619934","https://openalex.org/W2019759670","https://openalex.org/W2036367260","https://openalex.org/W2066350381","https://openalex.org/W2081432842","https://openalex.org/W2113443463","https://openalex.org/W2117334662","https://openalex.org/W2119621677","https://openalex.org/W2153381244","https://openalex.org/W2170208137","https://openalex.org/W2250539671","https://openalex.org/W2553681755","https://openalex.org/W2963026768","https://openalex.org/W3016473712","https://openalex.org/W3112391668","https://openalex.org/W3122489471","https://openalex.org/W3123829300","https://openalex.org/W3124596119","https://openalex.org/W3125788531","https://openalex.org/W3125952890","https://openalex.org/W3138164040","https://openalex.org/W3186237585","https://openalex.org/W3199441486","https://openalex.org/W3214898841","https://openalex.org/W4231546411","https://openalex.org/W4288253152","https://openalex.org/W4297734170","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2040130734","https://openalex.org/W3125511128","https://openalex.org/W3124506222","https://openalex.org/W2207859800","https://openalex.org/W2186486242","https://openalex.org/W2158134346","https://openalex.org/W2150849684","https://openalex.org/W2097615164","https://openalex.org/W2103117905","https://openalex.org/W2170289782"],"abstract_inverted_index":{"Post-Earnings":[0],"Announcement":[1],"Drift":[2],"(PEAD),":[3],"a":[4,27,38,54,169],"well-known":[5],"anomaly":[6],"in":[7,19,142,176],"financial":[8],"markets,":[9],"describes":[10],"the":[11,20,60,63,70,86,98,128,143,163],"tendency":[12],"of":[13,22,56,62,88,109,137,168],"cumulative":[14],"stock":[15,145],"returns":[16,165],"to":[17,42,84,135,188,194],"drift":[18],"direction":[21],"an":[23,31],"earnings":[24,32,64,95,118,132],"surprise":[25],"for":[26,69,97],"prolonged":[28],"period":[29],"following":[30],"announcement.":[33],"Numerous":[34],"studies":[35],"have":[36],"used":[37,68],"supervised":[39,104],"learning":[40],"approach":[41],"predict":[43],"PEAD,":[44],"using":[45,131],"earnings,":[46,157,203],"fundamental":[47,122,158,204],"and":[48,80,91,120,123,159,192,205],"technical":[49,124,160,206],"factors.":[50],"However,":[51],"there":[52],"is":[53],"lack":[55],"study":[57,127],"on":[58],"how":[59],"context":[61],"call":[65],"can":[66],"be":[67],"PEAD":[71,99],"prediction":[72,100],"task.":[73,101],"This":[74],"paper":[75],"uses":[76,201],"computational":[77],"linguistics":[78],"techniques":[79],"large":[81],"language":[82],"models":[83],"examine":[85],"effectiveness":[87],"incorporating":[89],"textual":[90,112],"contextual":[92,115,151],"features":[93,152],"from":[94,133,186,197],"calls":[96],"Our":[102,147],"proposed":[103,129],"model":[105,130],"includes":[106],"four":[107,180],"categories":[108],"features:":[110],"1)":[111],"features,":[113,116,119,161],"2)":[114],"3)":[117],"4)":[121],"features.":[125,207],"We":[126],"2010/01/01":[134],"2022/12/31":[136],"all":[138,179],"point-in-time":[139],"S&P500":[140],"constituents":[141],"US":[144],"market.":[146],"results":[148],"show":[149],"that":[150],"provide":[153],"information":[154],"unexplained":[155],"by":[156],"improving":[162],"average":[164],"per":[166],"trade":[167],"hypothetical":[170],"long-short":[171],"portfolio":[172],"against":[173],"baseline":[174,198],"solution":[175],"out-of-sample":[177],"across":[178],"different":[181],"abnormal":[182],"return":[183],"calculations,":[184],"ranging":[185],"53":[187],"354":[189],"basis":[190],"points":[191],"16.9%":[193],"108.5%":[195],"improvement":[196],"model,":[199],"which":[200],"only":[202]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}
