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

Detalhes bibliográficos
Autor(a) principal: Lobão, Júlio
Data de Publicação: 2017
Outros Autores: Pacheco, Luís Miguel, Pereira, Carlos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11328/1985
Resumo: Purpose 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.
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spelling The use of the recognition heuristic as an investment strategy in European stock marketsInvestimentsBehavioural financeStock returnsFinantial marketRecognition heuristicPurpose 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.Emerald2017-12-06T19:20:49Z2017-12-05T00:00:00Z2017-12-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11328/1985eng10.1108/JEFAS-01-2017-0013Lobão, JúlioPacheco, Luís MiguelPereira, Carlosinfo: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:RCAAP2023-06-15T02:10:16ZPortal AgregadorONG
dc.title.none.fl_str_mv The use of the recognition heuristic as an investment strategy in European stock markets
title The use of the recognition heuristic as an investment strategy in European stock markets
spellingShingle The use of the recognition heuristic as an investment strategy in European stock markets
Lobão, Júlio
Investiments
Behavioural finance
Stock returns
Finantial market
Recognition heuristic
title_short The use of the recognition heuristic as an investment strategy in European stock markets
title_full The use of the recognition heuristic as an investment strategy in European stock markets
title_fullStr The use of the recognition heuristic as an investment strategy in European stock markets
title_full_unstemmed The use of the recognition heuristic as an investment strategy in European stock markets
title_sort The use of the recognition heuristic as an investment strategy in European stock markets
author Lobão, Júlio
author_facet Lobão, Júlio
Pacheco, Luís Miguel
Pereira, Carlos
author_role author
author2 Pacheco, Luís Miguel
Pereira, Carlos
author2_role author
author
dc.contributor.author.fl_str_mv Lobão, Júlio
Pacheco, Luís Miguel
Pereira, Carlos
dc.subject.por.fl_str_mv Investiments
Behavioural finance
Stock returns
Finantial market
Recognition heuristic
topic Investiments
Behavioural finance
Stock returns
Finantial market
Recognition heuristic
description Purpose 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-06T19:20:49Z
2017-12-05T00:00:00Z
2017-12-05
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/11328/1985
url http://hdl.handle.net/11328/1985
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1108/JEFAS-01-2017-0013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Emerald
publisher.none.fl_str_mv Emerald
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