{"id":"https://openalex.org/W3008700930","doi":"https://doi.org/10.1109/bigdata47090.2019.9006015","title":"Deal or No Deal: Predicting Mergers and Acquisitions at Scale","display_name":"Deal or No Deal: Predicting Mergers and Acquisitions at Scale","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3008700930","doi":"https://doi.org/10.1109/bigdata47090.2019.9006015","mag":"3008700930"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5027489163","display_name":"Ryan V. Moriarty","orcid":"https://orcid.org/0000-0001-7100-1906"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]},{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ryan Moriarty","raw_affiliation_strings":["Courant Institute of Mathematical Sciences New York University New York, New York"],"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences New York University New York, New York","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001644298","display_name":"Howard Ly","orcid":null},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Howard Ly","raw_affiliation_strings":["Courant Institute of Mathematical Sciences New York University New York, New York"],"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences New York University New York, New York","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040600809","display_name":"Ellie Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ellie Lan","raw_affiliation_strings":["Bloomberg LP New York, New York"],"affiliations":[{"raw_affiliation_string":"Bloomberg LP New York, New York","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048803050","display_name":"Suzanne McIntosh","orcid":"https://orcid.org/0000-0001-9605-6743"},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suzanne K. McIntosh","raw_affiliation_strings":["Courant Institute of Mathematical Sciences, and NYU Center for Data Science New York University New York, New York"],"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, and NYU Center for Data Science New York University New York, New York","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027489163"],"corresponding_institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":0.7922,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.77500837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5552","last_page":"5558"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9957000017166138,"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":0.9957000017166138,"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/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.980400025844574,"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"}},{"id":"https://openalex.org/T10019","display_name":"Corporate Finance and Governance","score":0.9779000282287598,"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/mergers-and-acquisitions","display_name":"Mergers and acquisitions","score":0.7627004981040955},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7243655920028687},{"id":"https://openalex.org/keywords/realm","display_name":"Realm","score":0.7050472497940063},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5822846293449402},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5811273455619812},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5778238773345947},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.48917677998542786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35776078701019287},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3077997863292694},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.20123544335365295},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.12424132227897644}],"concepts":[{"id":"https://openalex.org/C548217281","wikidata":"https://www.wikidata.org/wiki/Q731112","display_name":"Mergers and acquisitions","level":2,"score":0.7627004981040955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7243655920028687},{"id":"https://openalex.org/C2778757428","wikidata":"https://www.wikidata.org/wiki/Q1250464","display_name":"Realm","level":2,"score":0.7050472497940063},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5822846293449402},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5811273455619812},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5778238773345947},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.48917677998542786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35776078701019287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3077997863292694},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.20123544335365295},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.12424132227897644},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W158052132","https://openalex.org/W1880262756","https://openalex.org/W1969047491","https://openalex.org/W2035465815","https://openalex.org/W2070077261","https://openalex.org/W2150598666","https://openalex.org/W2186533409","https://openalex.org/W2797360401","https://openalex.org/W4285719527","https://openalex.org/W6606404243","https://openalex.org/W6639619044"],"related_works":["https://openalex.org/W2359053655","https://openalex.org/W2387777532","https://openalex.org/W2382709029","https://openalex.org/W2389147080","https://openalex.org/W2377883125","https://openalex.org/W2362479786","https://openalex.org/W2392455911","https://openalex.org/W2374248756","https://openalex.org/W2375492428","https://openalex.org/W2278792348"],"abstract_inverted_index":{"While":[0],"research":[1],"on":[2,25],"merger":[3],"and":[4,74,90,115],"acquisition":[5],"(M&A)":[6],"has":[7,22],"been":[8,23],"extensive":[9],"in":[10,14],"the":[11,15,97],"finance":[12],"literature,":[13],"realm":[16],"of":[17,78,101],"data":[18],"science,":[19],"little":[20],"work":[21],"done":[24],"deploying":[26],"a":[27,48,85],"successful":[28],"Big":[29],"Data":[30],"informed":[31],"M&A":[32,45,80],"prediction":[33],"model.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,69,93,104],"explore":[39],"what":[40],"can":[41],"be":[42],"learned":[43],"about":[44],"activity":[46],"from":[47],"firm's":[49],"annual":[50],"Form":[51],"10-K":[52],"SEC":[53],"filing.":[54],"We":[55,82],"utilize":[56],"natural":[57],"language":[58],"processing":[59],"(NLP)":[60],"techniques":[61],"to":[62,87,95,111],"vectorize":[63],"each":[64],"filing's":[65],"textual":[66],"data.":[67,118],"Next,":[68],"cluster":[70],"firms":[71],"by":[72],"industry":[73],"identify":[75],"keywords":[76],"suggestive":[77],"upcoming":[79],"activity.":[81],"then":[83],"train":[84],"classifier":[86],"predict":[88],"acquirers":[89],"targets,":[91],"which":[92,108],"use":[94],"forecast":[96],"most":[98],"likely":[99],"M&As":[100],"2019.":[102],"Lastly,":[103],"deploy":[105],"an":[106],"application":[107],"enables":[109],"users":[110],"query":[112],"our":[113,117],"forecasts":[114],"visualize":[116]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}