Examinando por Materia "Default"

Mostrando 1 - 5 de 5
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    Ítem
    Impacto de las prácticas de gobierno corporativo en la probabilidad de incumplimiento de las empresas colombianas
    (Universidad EAFIT, 2022) Escobar Marín, William; Zapata Pérez, Manuel; Gaitán Riaño, Sandra Constanza; Téllez Falla, Diego Fernando
    The implementation of good corporate governance practices is one of the most encouraged strategies in companies today. In the present thesis, the impact that the application of these best practices can have on the probability of bankruptcy for no-financial companies in Colombia is studied. A data panel model is made considering the Survey of Best Country Government Practices of the Financial Superintendence of Colombia and the probability of default, measured through the Z”-Score of the Altman’s model, the above for a sample of companies from different economic sectors between the years 2015 to 2021. The relationship between best practices and the probability of non-compliance is presented in order to give recommendations for financial management and corporate governance, in the same way limitations and recommendations are presented for future lines of research on the subject.
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    Ítem
    Implementación de un modelo de scoring de crédito para Mexichem Colombia SAS
    (Universidad EAFIT, 2024) Vargas Izquierdo, Daniel Camilo; Rojas Ormaza, Brayan Ricardo
    This project sought to implement a credit scoring model for Mexichem Colombia SAS using machine learning techniques to predict the probability of default in companies. Four algorithms were compared: decision trees, random forest, gradient boosting and neural networks, each with unique characteristics in terms of accuracy and handling of complex data. The research included the selection and evaluation of relevant variables using the Gini index and recursive elimination techniques to avoid overfitting. The results helped to identify the most effective model to predict credit risks, optimizing financial decision-making.
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    Ítem
    Proceso de ASC - PREDICTING COLOMBIAN SOVEREIGN DEFAULT PROBABILITY USING MACHINE LEARNING
    (Universidad EAFIT, 2021) Cortés, Lina M; Mosquera, Stephania; Galeano, Juan; Mena, Luis; Universidad EAFIT
    The 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.
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    Ítem
    Reestructuración de pasivos y su efecto en la probabilidad de default de una compañía
    (Universidad EAFIT, 2020) Palmett Herazo, Jaiber Mauricio; Ospina Mejía, Jaime Alberto
    This paper examined the effect of debt restructuring on a company's default distance in the short and long term, based on the initial understanding of the probability of default by sector and size of companies in Colombia and firms that were liquidated. This task was carried out by applying the Merton model (1974) to the companies that form the insolvency base of the Superintendencia de Sociedades as of December 2019 and to the company Avianca Holdings S. A. As a result, the short-term and total default probability for Avianca measured before and after restructuring is obtained. These results allow to compare the probabilities of the different classifications of companies and conclude on the effectiveness of the restructuring carried out by Avianca.
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    Ítem
    El riesgo de crédito en el mercado secundario no bancario de las libranzas en Colombia
    (Universidad EAFIT, 2017) Chávez Palacios, Claudia Idalith; Trespalacios Carrasquilla, Alfredo
    El objetivo de la presente investigación es efectuar una caracterización del riesgo de crédito conexo a las operaciones sobre libranzas en el mercado secundario no bancario en Colombia, para lo cual se evaluó, por una parte, la regulación legal en materia de libranzas; y por la otra, el riesgo de crédito inherente a dichas operaciones, determinando igualmente las situaciones de riesgo que influyen en la materialización de circunstancias de default dentro de este mercado, resultado de lo cual se concluyó que es cierta la hipótesis planteada al inicio de la investigación, según la cual existe relación entre la escasa fortaleza o suficiencia de la regulación en materia de operaciones sobre libranzas en el mercado no regulado y el incremento del riesgo de crédito inherente a las mismas -- Igualmente, se evidenció que la ponderación que se ha efectuado del riesgo de crédito no corresponde a la realidad de este mercado