Examinando por Materia "Predicción de rendimientos"
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Ítem Evaluación del efecto de incluir la predicción de rendimientos mediante la técnica de Support Vector Machines en la eficiencia del modelo de media-varianza de Markowitz(Universidad EAFIT, 2024) Aristizábal Nieto, Eliana Jiset; García Agudelo, Estefanía; Botero Ramírez, Juan CarlosPortfolio investment optimization aims to maximize expected returns given certain levels of risk. This process requires dealing with different variables in a nonlinear, noisy system due to market complexity. This is understood as a system that is affected by different external conditions that may be uncontrollable, where volatility influenced by unpredictable factors is present. In this study, an analysis of the results obtained by integrating machine learning techniques, specifically the set of algorithms called Support Vector Machines (SVM), into classical portfolio construction models is conducted. These algorithms allow for the analysis of large amounts of data and the estimation of asset return time series, resulting in a hybrid optimization model. Historical data from the stock markets of the United States and Colombia are used for numerical experiments; one set of data is used for model training (Training Set) and another for testing (Testing Set). Finally, the efficiency of the model is evaluated comparatively with the mean-variance portfolio selection theory proposed by Markowitz.Ítem Optimización de portafolios : integración de modelos de aprendizaje automático y estrategias tradicionales para una gestión eficiente de inversiones(Universidad EAFIT, 2024) Agudelo Niño, Yolanda María; Cruz Castañeda, Vivian