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Ítem Proceso de ASC - RELACION ENTRE EL DESEMPEÑO FINANCIERO Y DIVERSIDAD DE GENERO EN JUNTAS DIRECTIVAS EN PYMES(Universidad EAFIT, 2023) Giraldo Arrieta, María Bernarda; Yepes Raigosa, David Alejandro; Universidad EAFITThis study delves into the financial information of small and medium-sized enterprises (SMEs) in Colombia to assess the effect of gender diversity on corporate boards and its impact on financial performance. Employing Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) regressions with fixed effects, the study encompasses the period from 2015 to 2020. The findings do not reveal statistically significant evidence of a correlation between the proportion of female board members and the financial performance of SMEs in Colombia. Despite the absence of a direct link between female board representation and financial performance, the study highlights a notable increase in women's participation on corporate boards over time. Additionally, it identifies significant regional disparities in female board representation, with Antioquia exhibiting the lowest proportion of female board members among Colombian SMEs. These findings underscore the importance of promoting women's participation in leadership roles within SMEs and corporations, as gender, according to the study's results, does not negatively impact financial performance.Ítem Proceso de ASC - DESEMPEÑO EMPRESARIAL: EFECTO SOBRE LA CREACION DE VALOR EN EMPRESAS COLOMBIANAS POST-M&A(Universidad EAFIT, 2019) Cortés, Lina M.; Cárdenas, Santiago; Daza, Geraldine; Moreno, Alejandro; Universidad EAFITMergers and acquisitions (M&A) are a strategy for companies to achieve different objectives, including the creation of shareholder value. The objective of this study is to explore methodologies and variables that allow quantifying results on the creation of value after strategic alliances via M&A. This research studies events of Colombian companies belonging to the manufacturing sector in the period 1998-2017.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 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 Proceso de ASC - CALCULO DE LA PRIMA DE RIESGO EN EL CASO COLOMBIANO: UN ENFOQUE PRACTICO(Universidad EAFIT, 2020) Cortés, Lina M; Galeano, Juan; Brand, Sebastián; Universidad EAFITThe Market Risk Premium (MRPX) "is the incremental return that an investor demands from the stock market (from a diversified portfolio) above the required equity premium (Fernandez, 2009). The objective of this study is to explore methodologies and variables that allow calculating the risk premium in a practical way for the specific Colombian case.