The use of the recognition heuristic as an investment strategy in European stock markets

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dc.contributor.authorLobão, Júlio
dc.contributor.authorPereira, Carlos
dc.contributor.authorPacheco, Luís Miguel
dc.date.accessioned2017-12-06T19:20:49Z
dc.date.available2017-12-06T19:20:49Z
dc.date.issued2017-12-05
dc.description.abstractPurpose People often face constraints such as a lack of time or information in taking decisions, which leads them to use heuristics. In these situations, fast and frugal rules may be useful for making adaptive decisions with fewer resources, even if it leads to suboptimal choices. When applied to financial markets, the recognition heuristic predicts that investors acquire the stocks that they are aware of, thereby inflating the price of the most recognized stocks. This paper aims to study the profitability against the market of the most recognized stocks in Europe. Design/methodology/approach In this paper, the authors perform a survey and use Google Trends to study the profitability against the market of the most recognized stocks in Europe. Findings The authors conclude that a recognition heuristic portfolio yields poorer returns than a market portfolio. In contrast, from the data collected on Google Trends, weak evidence was found that strong increases in companies monthly search volumes may lead to abnormal returns in the following month. Research limitations/implications The applied investment strategy does not account for transaction costs, which may jeopardize its profitability given the fact that it is necessary to revise the portfolio on a monthly basis. Despite the results obtained, they are useful to understanding the performance of recognition heuristic strategies over a comprehensive time horizon, and it would be interesting to depict its viability during different market conditions. This analysis could provide additional information about a preferable scenario for employing our strategies and, ultimately, enhance the profitability of recognition heuristic strategies. Practical implications Through the exhaustive analysis performed here on the recognition heuristic in the European stock market, it is possible to conclude that no evidence was found for the viability of exploring this type of strategy. In fact, the investors would always gain better returns when adopting a passive investment strategy. Therefore, it would be wise to assume that the European market presents at least a degree of efficiency where no investment would yield abnormal returns following the recognition heuristic. Originality/value The main objective of this paper is to study the performance of the recognition heuristic in the financial markets and to contribute to the knowledge in this field. Although many authors have already studied this heuristic when applied to financial markets, there is a lack of consensus in the literature.
dc.identifier.citationLobão, J., Pacheco, L. M., & Pereira, C. (2017). The use of the recognition heuristic as an investment strategy in European stock markets. Journal of Economics, Finance and Administrative Science, 22(43), 207-223. doi: 10.1108/JEFAS-01-2017-0013. Disponível no Repositório UPT, http://hdl.handle.net/11328/1985
dc.identifier.doi10.1108/JEFAS-01-2017-0013pt_PT
dc.identifier.urihttp://hdl.handle.net/11328/1985
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherEmeraldpt_PT
dc.rightsopen access
dc.subjectInvestiments
dc.subjectBehavioural finance
dc.subjectStock returns
dc.subjectFinantial market
dc.subjectRecognition heuristic
dc.titleThe use of the recognition heuristic as an investment strategy in European stock marketspt_PT
dc.typejournal articlept_PT
degois.publication.firstPage207pt_PT
degois.publication.issue43
degois.publication.lastPage223pt_PT
degois.publication.titleJournal of Economics, Finance and Administrative Sciencept_PT
degois.publication.volume22pt_PT
dspace.entity.typePublicationen
person.familyNamePacheco
person.givenNameLuís Miguel
person.identifier.ciencia-idBF16-0EF2-107B
person.identifier.orcid0000-0002-9066-6441
person.identifier.ridE-5193-2010
person.identifier.scopus-author-id55945343700
relation.isAuthorOfPublicationa25aba90-4787-45a8-b908-646f24b32dfc
relation.isAuthorOfPublication.latestForDiscoverya25aba90-4787-45a8-b908-646f24b32dfc

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