Confidence and self-attribution bias in an artificial stock market
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1371/journal.pone.0172258 http://hdl.handle.net/11449/169489 |
Resumo: | Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. |
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Repositório Institucional da UNESP |
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Confidence and self-attribution bias in an artificial stock marketUsing an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Economics Sao Paulo State University (UNESP)Sao Paulo Metropolitan CompanyFederal Institute of Education Science and TechnologyMetropolitan College Boston UniversityCenter for Polymer Studies and Department of Physics Boston UniversityDepartment of Economics Sao Paulo State University (UNESP)FAPESP: 2014/19534-8Universidade Estadual Paulista (Unesp)Sao Paulo Metropolitan CompanyScience and TechnologyBoston UniversityBertella, Mario A. [UNESP]Pires, Felipe R.Rego, Henio H. A.Silva, Jonathas N. [UNESP]Vodenska, IrenaStanley, H. Eugene2018-12-11T16:46:06Z2018-12-11T16:46:06Z2017-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1371/journal.pone.0172258PLoS ONE, v. 12, n. 2, 2017.1932-6203http://hdl.handle.net/11449/16948910.1371/journal.pone.01722582-s2.0-850137889782-s2.0-85013788978.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPLoS ONE1,164info:eu-repo/semantics/openAccess2023-12-16T06:21:42Zoai:repositorio.unesp.br:11449/169489Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:30:18.032368Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Confidence and self-attribution bias in an artificial stock market |
title |
Confidence and self-attribution bias in an artificial stock market |
spellingShingle |
Confidence and self-attribution bias in an artificial stock market Bertella, Mario A. [UNESP] |
title_short |
Confidence and self-attribution bias in an artificial stock market |
title_full |
Confidence and self-attribution bias in an artificial stock market |
title_fullStr |
Confidence and self-attribution bias in an artificial stock market |
title_full_unstemmed |
Confidence and self-attribution bias in an artificial stock market |
title_sort |
Confidence and self-attribution bias in an artificial stock market |
author |
Bertella, Mario A. [UNESP] |
author_facet |
Bertella, Mario A. [UNESP] Pires, Felipe R. Rego, Henio H. A. Silva, Jonathas N. [UNESP] Vodenska, Irena Stanley, H. Eugene |
author_role |
author |
author2 |
Pires, Felipe R. Rego, Henio H. A. Silva, Jonathas N. [UNESP] Vodenska, Irena Stanley, H. Eugene |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Sao Paulo Metropolitan Company Science and Technology Boston University |
dc.contributor.author.fl_str_mv |
Bertella, Mario A. [UNESP] Pires, Felipe R. Rego, Henio H. A. Silva, Jonathas N. [UNESP] Vodenska, Irena Stanley, H. Eugene |
description |
Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-02-01 2018-12-11T16:46:06Z 2018-12-11T16:46:06Z |
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://dx.doi.org/10.1371/journal.pone.0172258 PLoS ONE, v. 12, n. 2, 2017. 1932-6203 http://hdl.handle.net/11449/169489 10.1371/journal.pone.0172258 2-s2.0-85013788978 2-s2.0-85013788978.pdf |
url |
http://dx.doi.org/10.1371/journal.pone.0172258 http://hdl.handle.net/11449/169489 |
identifier_str_mv |
PLoS ONE, v. 12, n. 2, 2017. 1932-6203 10.1371/journal.pone.0172258 2-s2.0-85013788978 2-s2.0-85013788978.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PLoS ONE 1,164 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808129211061239808 |