A stock market forecasting model in Peru using artificial intelligence and computational optimization tools

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Cano Lengua, Miguel Angel, Rodríguez Mallma, Mirko Jerber, Papa Quiroz, Erik Alex
Formato: objeto de conferencia
Fecha de Publicación:2020
Institución:Universidad Privada del Norte
Repositorio:UPN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.upn.edu.pe:11537/27222
Enlace del recurso:https://hdl.handle.net/11537/27222
https://doi.org/10.1007/978-3-030-57548-9_7
Nivel de acceso:acceso abierto
Materia:Bolsa de valores
Inteligencia artificial
Simulación por computadora
Mercado financiero
https://purl.org/pe-repo/ocde/ford#2.02.04
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dc.title.es_PE.fl_str_mv A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
title A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
spellingShingle A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
Cano Lengua, Miguel Angel
Bolsa de valores
Inteligencia artificial
Simulación por computadora
Mercado financiero
https://purl.org/pe-repo/ocde/ford#2.02.04
title_short A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
title_full A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
title_fullStr A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
title_full_unstemmed A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
title_sort A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
author Cano Lengua, Miguel Angel
author_facet Cano Lengua, Miguel Angel
Rodríguez Mallma, Mirko Jerber
Papa Quiroz, Erik Alex
author_role author
author2 Rodríguez Mallma, Mirko Jerber
Papa Quiroz, Erik Alex
author2_role author
author
dc.contributor.author.fl_str_mv Cano Lengua, Miguel Angel
Rodríguez Mallma, Mirko Jerber
Papa Quiroz, Erik Alex
dc.subject.es_PE.fl_str_mv Bolsa de valores
Inteligencia artificial
Simulación por computadora
Mercado financiero
topic Bolsa de valores
Inteligencia artificial
Simulación por computadora
Mercado financiero
https://purl.org/pe-repo/ocde/ford#2.02.04
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.04
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2021-07-15T20:41:40Z
dc.date.available.none.fl_str_mv 2021-07-15T20:41:40Z
dc.date.issued.fl_str_mv 2020-12-15
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.citation.es_PE.fl_str_mv Cano, M. A., Rodríguez, M. J., & Papa, E. A. (2020). A stock market forecasting model in Peru using artificial intelligence and computational optimization tools. Proceedings of the 5th Brazilian Technology Symposium. Smart Innovation, Systems and Technologies, 201, 79-86. https://doi.org/10.1007/978-3-030-57548-9_7
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11537/27222
dc.identifier.journal.es_PE.fl_str_mv Proceedings of the 5th Brazilian Technology Symposium
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-57548-9_7
identifier_str_mv Cano, M. A., Rodríguez, M. J., & Papa, E. A. (2020). A stock market forecasting model in Peru using artificial intelligence and computational optimization tools. Proceedings of the 5th Brazilian Technology Symposium. Smart Innovation, Systems and Technologies, 201, 79-86. https://doi.org/10.1007/978-3-030-57548-9_7
Proceedings of the 5th Brazilian Technology Symposium
url https://hdl.handle.net/11537/27222
https://doi.org/10.1007/978-3-030-57548-9_7
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América
https://creativecommons.org/licenses/by-nc-sa/3.0/us/
dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv Springer
dc.publisher.country.es_PE.fl_str_mv CH
dc.source.es_PE.fl_str_mv Universidad Privada del Norte
Repositorio Institucional - UPN
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instname_str Universidad Privada del Norte
instacron_str UPN
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spelling Cano Lengua, Miguel AngelRodríguez Mallma, Mirko JerberPapa Quiroz, Erik Alex2021-07-15T20:41:40Z2021-07-15T20:41:40Z2020-12-15Cano, M. A., Rodríguez, M. J., & Papa, E. A. (2020). A stock market forecasting model in Peru using artificial intelligence and computational optimization tools. Proceedings of the 5th Brazilian Technology Symposium. Smart Innovation, Systems and Technologies, 201, 79-86. https://doi.org/10.1007/978-3-030-57548-9_7https://hdl.handle.net/11537/27222Proceedings of the 5th Brazilian Technology Symposiumhttps://doi.org/10.1007/978-3-030-57548-9_7El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.ABSTRACT It is proposed the development of a forecast model capable of predicting the behavior of the price indices and quotes of the shares traded on the Lima Stock Exchange, based on the use of artificial intelligence techniques such as artificial neural networks and fuzzy logic based on computational optimization methods. The proposed model considers the forecast, in addition to the historical quantitative data of the share price, the inclusion of qualitative macroeconomic factors that significantly influence the behavior of the time series of the stock markets. It is about harnessing the ability of artificial neural networks to work with nonlinear quantitative data and their capacity for learning and also take advantage of the fuzzy logic technique to simulate the way of reasoning of human beings by defining judgment rules or knowledge base and their evaluation through inference mechanisms. The main contribution is to demonstrate that the proposed model is capable of obtaining more optimal approximations in the forecast of the financial time series.Revisión por paresComasapplication/pdfengSpringerCHinfo:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de Américahttps://creativecommons.org/licenses/by-nc-sa/3.0/us/Universidad Privada del NorteRepositorio Institucional - UPNreponame:UPN-Institucionalinstname:Universidad Privada del Norteinstacron:UPNBolsa de valoresInteligencia artificialSimulación por computadoraMercado financierohttps://purl.org/pe-repo/ocde/ford#2.02.04A stock market forecasting model in Peru using artificial intelligence and computational optimization toolsinfo:eu-repo/semantics/conferenceObjectCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81037https://repositorio.upn.edu.pe/bitstream/11537/27222/1/license_rdf80294ba9ff4c5b4f07812ee200fbc42fMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.upn.edu.pe/bitstream/11537/27222/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5211537/27222oai:repositorio.upn.edu.pe:11537/272222021-07-15 15:41:45.885Repositorio Institucional UPNjordan.rivero@upn.edu.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A stock market forecasting model in Peru using artificial intelligence and computational optimization tools
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