Forecasting exchange rate: A bibliometric and content analysis

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dc.contributor.authorde Souza Vasconcelos C.
dc.contributor.authorHadad Junior E.
dc.date.accessioned2024-03-12T19:12:46Z
dc.date.available2024-03-12T19:12:46Z
dc.date.issued2023
dc.description.abstract© 2022 Elsevier Inc.The study aims to present a systematic overview of the research in the field of exchange rate projection models through bibliometric techniques and content analysis. First, 775 articles published in journals within the scope of the international Web of Science database from 1966 to May 2021 were analyzed through bibliometric techniques. Second, a selected sample of 69 articles was analyzed through a detail content analysis to identify hot topics and new avenues of interest in the field. The research findings suggest that the scientific production on the subject is in wide development. New approaches have been incorporated, such as neural networks, requiring a broad perspective by the researcher in the evaluation of the empirical results.
dc.description.firstpage607
dc.description.lastpage628
dc.description.volume83
dc.identifier.doi10.1016/j.iref.2022.09.006
dc.identifier.issn1059-0560
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/34247
dc.relation.ispartofInternational Review of Economics and Finance
dc.rightsAcesso Restrito
dc.subject.otherlanguageBibliometric review
dc.subject.otherlanguageContent analysis
dc.subject.otherlanguageExchange rate
dc.subject.otherlanguageModels
dc.titleForecasting exchange rate: A bibliometric and content analysis
dc.typeArtigo
local.scopus.citations5
local.scopus.eid2-s2.0-85140218267
local.scopus.updated2024-12-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85140218267&origin=inward
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