Conformación automática de portafolios de inversión usando analítica financiera

ilustraciones, diagramas, tablas

Autores:: Echeverri Sánchez, Laura Cristina

Tipo de recurso:

Fecha de publicación:: 2021

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Conformación automática de portafolios de inversión usando analítica financiera
dc.title.translated.eng.fl_str_mv	Automatic conformation of investment portfolios using financial analytics
title	Conformación automática de portafolios de inversión usando analítica financiera
spellingShingle	Conformación automática de portafolios de inversión usando analítica financiera 000 - Ciencias de la computación, información y obras generales 330 - Economía::332 - Economía financiera Investments Portfolio Portafolio de inversiones Comercio algorítmico Inteligencia artificial Aprendizaje supervisado Mercado financiero Algorithmic trading Artificial intelligence Supervised learning Financial market
title_short	Conformación automática de portafolios de inversión usando analítica financiera
title_full	Conformación automática de portafolios de inversión usando analítica financiera
title_fullStr	Conformación automática de portafolios de inversión usando analítica financiera
title_full_unstemmed	Conformación automática de portafolios de inversión usando analítica financiera
title_sort	Conformación automática de portafolios de inversión usando analítica financiera
dc.creator.fl_str_mv	Echeverri Sánchez, Laura Cristina
dc.contributor.advisor.none.fl_str_mv	Velásquez Henao, Juan David
dc.contributor.author.none.fl_str_mv	Echeverri Sánchez, Laura Cristina
dc.contributor.researchgroup.spa.fl_str_mv	Big Data y Data Analytics
dc.subject.ddc.spa.fl_str_mv	000 - Ciencias de la computación, información y obras generales 330 - Economía::332 - Economía financiera
topic	000 - Ciencias de la computación, información y obras generales 330 - Economía::332 - Economía financiera Investments Portfolio Portafolio de inversiones Comercio algorítmico Inteligencia artificial Aprendizaje supervisado Mercado financiero Algorithmic trading Artificial intelligence Supervised learning Financial market
dc.subject.lemb.none.fl_str_mv	Investments Portfolio Portafolio de inversiones
dc.subject.proposal.spa.fl_str_mv	Comercio algorítmico Inteligencia artificial Aprendizaje supervisado Mercado financiero
dc.subject.proposal.eng.fl_str_mv	Algorithmic trading Artificial intelligence Supervised learning Financial market
description	ilustraciones, diagramas, tablas
publishDate	2021
dc.date.issued.none.fl_str_mv	2021-11
dc.date.accessioned.none.fl_str_mv	2022-03-14T14:48:55Z
dc.date.available.none.fl_str_mv	2022-03-14T14:48:55Z
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
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dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
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url	https://repositorio.unal.edu.co/handle/unal/81198 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Medellín - Minas - Maestría en Ingeniería - Ingeniería de Sistemas
dc.publisher.department.spa.fl_str_mv	Departamento de la Computación y la Decisión
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Velásquez Henao, Juan David7b16d4a5377f0f1b1f90d3c8c6fd9f8b600Echeverri Sánchez, Laura Cristina484bf265e548bca9057f11a8e8aa2fd4600Big Data y Data Analytics2022-03-14T14:48:55Z2022-03-14T14:48:55Z2021-11https://repositorio.unal.edu.co/handle/unal/81198Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, tablasEn este trabajo se presenta un prototipo de simulación para evaluar diferentes estrategias de Comercio Algorítmico en el mercado financiero colombiano; esto con el fin de analizar si es posible incorporar este tipo de estrategias por parte de los inversionistas. Para construir las estrategias, se hacen uso de diversos tipos de modelos de Inteligencia Artificial, como por ejemplo redes neuronales, bosques aleatorios y regresión logística, los cuales predicen la tendencia del precio del día siguiente. Estas predicciones son transformadas en señales de compra y venta de las acciones que permiten la conformación diaria del portafolio. Las diferentes estrategias varían en cuanto al tipo de modelo entrenado para cada activo, el subconjunto de acciones seleccionado y otros parámetros que se dan en la negociación y que dependen exclusivamente de la aversión al riesgo del inversionista, tal como el porcentaje invertido en cada movimiento y la pérdida máxima aceptada. Las diferentes simulaciones permiten establecer la estrategia que logra la mayor rentabilidad para el inversionista, que en el escenario planteado en este trabajo consta de la selección de 11 acciones y un tipo de modelo diferente para cada activo según su mejor desempeño predictivo. Dicha estrategia alcanza una rentabilidad de 78% sobre la inversión. Los resultados de esta estrategia automática de negociación fueron comparados con la rentabilidad generada por la estrategia tradicional de conformación de portafolio Markowitz, la cual genera un 5% de pérdida. Al contrastar estos resultados se aprecian las bondades que trae para el inversionista implementar una estrategia automática de negociación basada en la predicción de la dirección del precio de las acciones. (Texto tomado de la fuente)In this work a simulation prototype is presented to evaluate different Algorithmic Trading strategies in the Colombian financial market; the purpose is to analyze the possibility to incorporate this type of strategy by investors. In order to build the strategies, various types of Artificial Intelligence models are applied, such as neural networks, random forests and logistic regression, which predict the price trend of the next day. These predictions are transformed into buy and sell signals for the stocks that allow the daily formation of the portfolio. The different strategies vary in terms of the type of model trained for each asset, the selected subset of stocks and other parameters that occur in the negotiation and that depend exclusively on the investor's aversion to risk, such as the percentage invested in each movement and the maximum accepted loss. The different simulations make it possible to establish the strategy that achieves the highest profitability for the investor, which in the scenario proposed in this work consists of the selection of 11 stocks and a different type of model for each asset according to its best predictive performance. This strategy achieves a 78% return on investment. The results of this automatic trading strategy were compared with the profitability generated by the traditional Markowitz portfolio formation strategy, which generates a 5% loss. When comparing these results, the benefits that the investor brings to implement an automatic negotiation strategy based on the prediction of the direction of the share price can be appreciated.Las series de tiempo de las acciones seleccionadas son tomadas a modo de ejemplo con los datos disponibles de la Bolsa de Valores de Colombia, por lo que dicha información es netamente para uso práctico.MaestríaMagíster en Ingeniería - Ingeniería de SistemasAnalítica PredictivaÁrea Curricular de Ingeniería de Sistemas e Informáticaxiv, 87 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - Ingeniería de SistemasDepartamento de la Computación y la DecisiónFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín000 - Ciencias de la computación, información y obras generales330 - Economía::332 - Economía financieraInvestments PortfolioPortafolio de inversionesComercio algorítmicoInteligencia artificialAprendizaje supervisadoMercado financieroAlgorithmic tradingArtificial intelligenceSupervised learningFinancial marketConformación automática de portafolios de inversión usando analítica financieraAutomatic conformation of investment portfolios using financial analyticsTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAloud, M. 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IEEE.EstudiantesInvestigadoresMaestrosPúblico generalORIGINAL1036950970.2022.pdf1036950970.2022.pdfTesis de Maestría en Ingeniería - Ingeniería de Sistemasapplication/pdf2247704https://repositorio.unal.edu.co/bitstream/unal/81198/1/1036950970.2022.pdf9018c31fd249b1f29d2e110ca88397faMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81198/2/license.txt8153f7789df02f0a4c9e079953658ab2MD52THUMBNAIL1036950970.2022.pdf.jpg1036950970.2022.pdf.jpgGenerated Thumbnailimage/jpeg4483https://repositorio.unal.edu.co/bitstream/unal/81198/3/1036950970.2022.pdf.jpg6303ef83bda67d36e9881d5ad089344dMD53unal/81198oai:repositorio.unal.edu.co:unal/811982023-10-06 14:53:15.831Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

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