Predicting M&A targets using news sentiment and topic detection

Detalhes bibliográficos
Autor(a) principal: Hajek, Petr
Data de Publicação: 2024
Outros Autores: Henriques, Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/163548
Resumo: Hajek, P., & Henriques, R. (2024). Predicting M&A targets using news sentiment and topic detection. Technological Forecasting and Social Change, 201, 1-12. Article 123270. https://doi.org/10.1016/j.techfore.2024.123270 --- The authors acknowledge the financial support of the Czech Science Foundation [Grant No. 22-22586S]
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spelling Predicting M&A targets using news sentiment and topic detectionM&ATakeoverNewsSentimentTopic detectionBERTBusiness and International ManagementApplied PsychologyManagement of Technology and InnovationHajek, P., & Henriques, R. (2024). Predicting M&A targets using news sentiment and topic detection. Technological Forecasting and Social Change, 201, 1-12. Article 123270. https://doi.org/10.1016/j.techfore.2024.123270 --- The authors acknowledge the financial support of the Czech Science Foundation [Grant No. 22-22586S]This paper uses news sentiment and topics to discuss the challenges and opportunities of predicting mergers and acquisition (M&A) targets. We explore the effect of investor sentiment on identifying M&As targets and how company-specific news articles can be used as a source of sentiment and topics to obtain richer information on various corporate events. We propose a framework incorporating news sentiment and topics into the M&A target prediction model, utilising state-of-the-art transformer-based sentiment analysis and topic modelling approaches. We evaluate the textual features' predictive power using a real-world dataset of US and UK target and non-target companies from 2020 to 2021, with several experiments conducted to reveal the contribution of sentiment and thematic focus of news to M&A target prediction. A profit-based objective function is proposed to overcome the inherent class imbalance problem in the dataset. Our findings suggest that news-based prediction models outperform traditional statistical and single machine learning methods, indicating the need for more robust and less prone to overfitting ensemble learning methods. Additionally, our study provides evidence for the positive effect of news-based negative sentiment on the likelihood of M&A. Our research has important implications for investors and analysts who seek to identify investment opportunities.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNHajek, PetrHenriques, Roberto2024-02-15T00:08:14Z2024-04-012024-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12application/pdfhttp://hdl.handle.net/10362/163548eng0040-1625PURE: 83422345https://doi.org/10.1016/j.techfore.2024.123270info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-18T01:43:53Zoai:run.unl.pt:10362/163548Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:59:27.368715Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Predicting M&A targets using news sentiment and topic detection
title Predicting M&A targets using news sentiment and topic detection
spellingShingle Predicting M&A targets using news sentiment and topic detection
Hajek, Petr
M&A
Takeover
News
Sentiment
Topic detection
BERT
Business and International Management
Applied Psychology
Management of Technology and Innovation
title_short Predicting M&A targets using news sentiment and topic detection
title_full Predicting M&A targets using news sentiment and topic detection
title_fullStr Predicting M&A targets using news sentiment and topic detection
title_full_unstemmed Predicting M&A targets using news sentiment and topic detection
title_sort Predicting M&A targets using news sentiment and topic detection
author Hajek, Petr
author_facet Hajek, Petr
Henriques, Roberto
author_role author
author2 Henriques, Roberto
author2_role author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Hajek, Petr
Henriques, Roberto
dc.subject.por.fl_str_mv M&A
Takeover
News
Sentiment
Topic detection
BERT
Business and International Management
Applied Psychology
Management of Technology and Innovation
topic M&A
Takeover
News
Sentiment
Topic detection
BERT
Business and International Management
Applied Psychology
Management of Technology and Innovation
description Hajek, P., & Henriques, R. (2024). Predicting M&A targets using news sentiment and topic detection. Technological Forecasting and Social Change, 201, 1-12. Article 123270. https://doi.org/10.1016/j.techfore.2024.123270 --- The authors acknowledge the financial support of the Czech Science Foundation [Grant No. 22-22586S]
publishDate 2024
dc.date.none.fl_str_mv 2024-02-15T00:08:14Z
2024-04-01
2024-04-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/163548
url http://hdl.handle.net/10362/163548
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0040-1625
PURE: 83422345
https://doi.org/10.1016/j.techfore.2024.123270
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 12
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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