Examinando por Materia "CDS"
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Ítem El crecimiento económico colombiano y la percepción del riesgo (2005-2019)(Universidad Eafit, 2020) Franco Ibañez, Geneily Dayanna; Naranjo Saldarriaga, Sara; Posada Posada, Carlos EstebanÍtem Proceso de ASC - PREDICTING COLOMBIAN SOVEREIGN DEFAULT PROBABILITY USING MACHINE LEARNING(Universidad EAFIT, 2021) Cortés, Lina M; Mosquera, Stephania; Galeano, Juan; Mena, Luis; Universidad EAFITThe purpose of this research is to use a sample to predict the probability of default of the Colombian government, using machine learning techniques that seek to create prediction algorithms. The success of the algorithm relies on the quality of the data used (Mohri et al., 2018). One is interested in applying the best method to create the algorithm, which requires a testing and adjustment process based on the observations taken. The most popular methods in machine learning are logistic regressions, decision trees, random decision forests, support vector machines (SVM), Naive Bayes, K Nearest Neighbor (KNN), K-means (Shafer et al., 1996). The different methods are trained and tested according to the data and literature review.Ítem Valoración de Credit Default Swaps CDS: Una aproximación con Monte Carlo(Universidad Pontificia Javeriana, 2008) Arbeláez Zapata, Juan Camilo; Maya Ochoa, Cecilia; Escuela de Administración, Universidad EAFIT; Departamento de Finanzas, Universidad EAFIT; Economía y Finanzas; Finanzas; Grupo de Investigación Finanzas y Banca