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dc.creatorZapata Quimbayo, Carlos Andrés-
dc.date2022-11-01-
dc.date.accessioned2023-03-27T17:38:32Z-
dc.date.available2023-03-27T17:38:32Z-
dc.identifierhttps://revistas.uexternado.edu.co/index.php/odeon/article/view/7837-
dc.identifier10.18601/17941113.n20.04-
dc.identifier.urihttps://biblioteca-repositorio.clacso.edu.ar/handle/CLACSO/230367-
dc.descriptionRobust optimization (or) models have made it possible to overcome the limitations of the mean-variance (mv) model, which involves the traditional approach for the optimal portfolio selection, by incorporating the uncertainty of the model parameters (expected returns and covariances). In this paper, the or advances in portfolio theory are presented using the worst-case approach, from which the robust formulations for the mv model are incorporated, considering the Markowitz and Sharpe works. From these formulations, a straightforward application is implemented where the advantages and benefits of the robust counterparts are highlighted compared to the original MV model. At the end, a brief discussion of additional formulations regarding uncertainty sets and other performance measures is presented.en-US
dc.descriptionLos modelos de optimización robusta (OR) han permitido superar las limitaciones del modelo media-varianza (MV), que comprende el enfoque tradicional para la selección de portafolios óptimos de inversión, al incorporar la incertidumbre de los parámetros del modelo (retornos esperados y covarianzas). En este trabajo se presentan los desarrollos de la OR en la teoría de portafolio mediante el enfoque del peor de los casos, a partir del cual se incorporan las formulaciones robustas para el modelo MV, teniendo en cuenta los trabajos de Markowitz y Sharpe. A partir de estas formulaciones, se lleva a cabo una sencilla aplicación en la que se resaltan las ventajas y bondades de las contrapartes robustas frente al modelo MV original. Al final, se presenta una breve discusión de formulaciones adicionales en materia de conjuntos de incertidumbre y otras medidas de desempeño.es-ES
dc.formatapplication/pdf-
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dc.languagespa-
dc.publisherUniversidad Externado de Colombiaes-ES
dc.relationhttps://revistas.uexternado.edu.co/index.php/odeon/article/view/7837/12752-
dc.relationhttps://revistas.uexternado.edu.co/index.php/odeon/article/view/7837/12753-
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dc.rightsDerechos de autor 2022 Carlos Andrés Zapata Quimbayoes-ES
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0es-ES
dc.sourceOdeon; No. 20 (2021): Enero-Junio; 93-121en-US
dc.sourceRevista ODEON; Núm. 20 (2021): Enero-Junio; 93-121es-ES
dc.source2346-2140-
dc.source1794-1113-
dc.subjectoptimal portfolio;en-US
dc.subjectrobust optimization;en-US
dc.subjectuncertainty setsen-US
dc.subjectportafolio óptimo;es-ES
dc.subjectoptimización robusta;es-ES
dc.subjectconjuntos de incertidumbrees-ES
dc.titleRobust Portfolio Optimization: Uncertainty Sets and Robust Counterpartsen-US
dc.titleOptimización robusta de portafolios: conjuntos de incertidumbre y contrapartes robustases-ES
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
Aparece en las colecciones: Centro de Investigaciones y Proyectos Especiales - CIPE/UEXTERNADO - Cosecha

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