Maestría en Administración Financiera (tesis)
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Ítem Modelación de los indicadores de eficiencia financiera, de las instituciones bancarias colombianas, a través de una regresión logística(Universidad EAFIT, 2024) López Hernández, Erick Steven; Durango Gutiérrez, María PatriciaÍtem Optimización de un portafolio de inversión con acciones del Colcap aplicando técnicas de machine learning(Universidad EAFIT, 2024) Osorio Buitrón, Maribel; Rico Villareal, Juan David; Rojas Ormanza, Bryan RicardoBased on the increases in the volumes of historical information on the shares of public companies, the question arises as to whether it is possible to create better optimized portfolios than those generated from traditional theory, making use of recent innovations in artificial intelligence and analysis of data from the last decade. For this reason, the present research aims to compare the traditional theory of portfolio optimization with the recent data analysis methodologies applied to Colcap. The methodology used is based on twelve previous investigations which had tested and demonstrated the performance of different machine learning models on stock exchanges around the world, such as S&P500, NASDAQ, DAX, SET and Colcap. From here, the best prospects were selected and applied to Colcap shares, to predict the future movement in the share price based on the historical behavior of certain significant variables and then compared with the traditional methodology. It was found that the best prediction model in the price movement applied to Colcap is the Random Forest, and the variables that best explain the future changes in the price of the shares of this exchange are the closing price of the share, the TRM index and the Colcap index. In addition, machine learning models managed to optimize portfolios with a smaller number of shares and higher returns backed by historical information.Ítem ¿Es posible pronosticar el precio por kilogramo en el mercado porcícola como una herramienta de gestión de riesgo?(Universidad EAFIT, 2024) Zapata Bustamante, Juan Camilo; Cruz Castañeda, VivianDue to the high volatility on the price per kilogram (COP/kg) in the pork market, the development of a predictive model as a risk management tool for producers is sought. The purpose of this tool is to provide a strategic guide to identify the best moment to sell a batch, organize the production accordingly and stablishing favorable conditions in selling contracts. This could provide an optimal risk management tool from the producer’s perspective in the market. To achieve this, the Box Jenkins methodology will be employed, using the ARIMA model as a base. The main objective its to anticipate possible fluctuations in the pig market, allowing producers to take informed decisions and in consequence, maximize de returns in the Colombian market operations.Ítem Control y gestión de inventarios y su impacto financiero en el sector del retail en Colombia(Universidad EAFIT, 2024) Aristizábal Gómez, Cindy Vanessa; Castellanos Acosta, Biviana del Pilar; Sánchez Ribero, Gustavo AlbertoÍtem Efectos de la implementación de buenas prácticas de gobierno corporativo en la rentabilidad del sector bancario colombiano(Universidad EAFIT, 2024) Sánchez Núñez, María Isabel; Gaitán Riaño, Sandra Constanza; Téllez Falla, Diego FernandoIn this research work, the effects of the implementation of good corporate governance practices in 24 Colombian banks in the period 2015-2019 were identified using panel econometric models in order to analyze the relationship between these practices and ROE, net interest margin, leverage multiplier and asset turnover. The positive and significant impact on the leverage multiplier and asset turnover was found, as well as the negative relationship between net interest margin and ROE in relation to good corporate governance practices. In addition, the relationship between representative qualitative characteristics of banks, such as origin, stock exchange listing and AAA risk rating, with the implementation of good corporate governance practices was analyzed, and it was found that banks listed on the stock exchange had greater incentives to comply with them.Ítem Potencialidad del financiamiento : una alternativa de cálculo(Universidad EAFIT, 2024) Fonseca Aguilar, María Dolores; Restrepo Tobón, Diego AlexanderÍtem ¿La banca española con valores? : caso BBVA, CaixaBank, Ibercaja y caja de ingenieros(Universidad EAFIT, 2024) Blandón Marín, Daniela; Durango Gutiérrez María PatriciaÍtem Aplicación de técnicas econométricas y estadísticas en el modelo financiero integral de planeación, previsión y proyección para una empresa de consultoría(Universidad EAFIT, 2024) Prieto Salinas, David Fernando; Quiroz Castellanos, Maira Andrea; Sánchez Ribero, Gustavo AlbertoÍtem Proceso de estructuración de un vehículo financiero para desarrollar proyectos de eficiencia energética en Colombia(Universidad EAFIT, 2023) Cuervo González, Sebastián; Grajales Bedoya, DuvánÍtem Aplicación de modelos de inteligencia artificial y aprendizaje automático para la previsión de precios y la optimización de portafolios : un enfoque integrado con datos estructurados y no estructurados con el fin de compararse con el S&P 500 como benchmark(Universidad EAFIT, 2023) Vélez García, Santiago; Botero Ramírez, Juan CarlosThis study presents an integrated approach of artificial intelligence and machine learning models, combining neural networks for price forecasting and portfolio optimization in the financial industry. The results show that the integrated approach outperforms other financial analysis methods and provides more effective tools for market professionals compared to a buy and hold strategy represented in the analysis by the S&P500. The artificial intelligence and machine learning models used in this study enable the identification of patterns and trends in financial data, helping investors make more informed and accurate decisions. Furthermore, the study demonstrates that the inclusion of unstructured data, such as news and social networks, in financial analysis can significantly improve the accuracy of price predictions achieving an R2greater than 65% and portfolio optimization.Ítem Effect of ESG practices on earnings management : an analysis of S&P 500 companies(Universidad EAFIT, 2023) Naranjo Alzate, Natalia; Téllez Falla, Diego FernandoThe purpose of this research was focused on identifying whether better performance in ESG scores has an impact on the quality of financial reporting, if better performance implies a decrease in the level of earnings management. To validate this hypothesis, a sample of 412 non-financial companies listed in the S&P 500 between 2011 and 2022 was studied with an annual frequency. Using a panel data model with fixed effects, it was found that ESG scores have a negative and statistically significant relationship with earnings management. This relationship is both overall and with each of the three pillars ESG (environmental, social and governance). The study shows that the implementation of good ESG practices influences the transparency of financial information, allowing stakeholders to make decisions with better quality of information.Ítem La red del MILA. Un análisis de sus principales actores y las implicaciones en sus indicadores financieros(Universidad EAFIT, 2023) Reyes Castillo, Juan Manuel; Bolivar Caro, Luis Miguel; Domínguez Monterroza, Andy RafaelThe main objective of this research is to analyse the relationships between the prominence of the issuers that are part of the Latin American Integrated Market (Mercado Integrado Latinoamericano, MILA) network, particularly those that make up the S&P MILA Andean 40 index, and their main financial indicators. For this purpose, the use of the MST (minimum spanning tree) methodology is proposed, in order to build an optimal structure that identifies the key issuers in the network and evaluates their preponderance, using centrality and influence measures as a reference. The research also examines the historical stock price performances and annual financial indicators of the different issuers, to identify patterns and trends related to their position in the network. Finally, it provides valuable information for investors and risk managers regarding the influence that the network position of the issuers has on financial indicators.Ítem Desarrollo de un modelo de predicción usando redes neuronales artificiales de los precios de los futuros del dolar para la industria colombiana(Universidad EAFIT, 2023) Montoya Herrera, Alejandro; Durango Gutiérrez, María PatriciaThe present study presents an exploration of the dollar peso price prediction models, calculated through the use of artificial neural networks and stock market indicators, to constitute a tool for investment decision making. A general overview of the use of the most used stock market indicators in the market such as oscillators and moving averages is presented, as well as market analysis based on cycle theory, where finally the FLDS indicators are used. Various types of neural network training configuration are performed exploring the possible results of the models.Ítem Determinants of Digital Financial Inclusion in Latin America and The Caribbean(Universidad EAFIT, 2023) Díaz Lara, Juan Manuel; Agudelo Zuluaga, Daniela Isabel; Álvarez Franco, Pilar Beatriz; Cruz Castañeda, VivianÍtem Gestión del riesgo de mercado para una empresa exportadora de ganado vivo en Colombia(Universidad EAFIT, 2023) Cruz Romero, Juan Sebastián; Peña Higuavita, Germán AdolfoThe live cattle market in Colombia has experienced a shift in dynamics since 2018 with the resurgence of exports, impacting the volatility of purchasing costs. This volatility generates uncertainty in the cash flow of exporters, who have limited tools to hedge against exchange rate and interest rate risks. This article aims to evaluate different hedging alternatives used in other markets to develop a strat egy that mitigates this risk. The analyzed tools include financial derivatives such as futures and options.Ítem Modelos de predicción estocástica para bitcoin : una evaluación de métodos y desempeño(Universidad EAFIT, 2023) Forero Criollo, Juan Sebastián; Hernández Hernández, Caroline; Cadavil Gil, AlejandroThis research focuses on forecasting Bitcoin (BTC) prices using statistical models, including LSTM, GRU, SVR, decision trees, Random Forest, and XGBoost. We evaluate their performance in terms of R2, RSME, MAPE, Lin Concordance Coefficient (CCC), and Explained Variance Score—metrics selected for their ability to assess regression models. We utilized BTC closing price data from 2014 to 2023, subjected to preprocessing involving cleaning, optimization, and data engineering. The models, initially unoptimized, were enhanced through hyperparameter tuning and specialized statistical techniques such as cross-validation, L1-L2 regularization, Bayesian and genetic optimization. The results highlight XGBoost as the optimal model with the incorporation of iterative hyperparameter tuning, Bayesian optimization, and nested cross-validation. It achieved outstanding values in all evaluated metrics: RSME of USD 30.45, MAPE of 0.09%, R-squared of 1.0, Lin Concordance Coefficient, and Explained Variance Score of 1.0 in each case.Ítem Análisis de sentimiento en acciones americanas : una herramienta para la toma de decisiones informada en el mercado financiero(Universidad EAFIT, 2023) Padilla Quintero, Javier Felipe; Brun, Xavier; Durango Gutiérrez, María PatriciaThis research study aims to assess the effectiveness of sentiment analysis in determining market perception of specific companies listed on the American stock market. The study focuses on employing sentiment analysis on collected news articles within a defined period. The specific objectives include gathering relevant news articles, employing natural language processing techniques for sentiment analysis, obtaining corresponding historical price data, and calculating the Pearson correlation between news sentiment and stock prices. The study endeavors to provide a deeper understanding of how sentiment analysis can impact the evaluation of companies and their market performance. The findings and analysis derived from this study can support investors in making more informed and data-driven decisions by considering market perception in conjunction with stock prices.Ítem Biodiversity and sustainable finance challenges : an analytical framework to understand the current challenges and how to face them in different economic sectors(Universidad EAFIT, 2023) Acuna Bayona, Andrés Felipe; Trivino Cortés, Diego Alejandro; Vergara Garavito, Judith CeciliaThis paper focuses on three sectors that significantly impact these Biodiversity and sustainable finance challenges: agriculture, oil & gas, and finance. This paper explores the challenges facing these sectors in adapting to the demands of biodiversity loss and to a sustainable finance. We examine the current practices and initiatives these sectors are implementing and identify areas for improvement. The present analysis aims to provide insights into how these sectors can adapt to meet these challenges and contribute to a sustainable future.Ítem Impacto financiero a través del uso de coberturas con Forward para una empresa exportadora de servicios BPO en Colombia(Universidad EAFIT, 2023) Martínez Osorio, Valery Tatiana; Marín Orozco, Stivenson; Cardona Llano, Juan FelipeColombia has had a financial derivatives market for over 20 years, and for approximately ten years, there has been a trading platform for standardized instruments (Hernández, 2018). Despite this, the participation of companies in this sector has been very low. Consequently, it is necessary to conduct a financial analysis to determine the impact generated by the use of forwards in foreign trade operations. This analysis allows for the identification of how this financial instrument contributes to minimizing exchange rate risk and ensuring the financial efficiency of a company. It is worth noting that the efficient use of these derivatives can contribute to minimizing the exchange rate risk faced by companies in the BPO sector from 2019 to 2022. It also enables them to experience less uncertainty, providing stability in their revenues and cash flow projections. This, in turn, helps ensure the normal development of business units.Ítem Estrategias con instrumentos financieros para mitigar el riesgo cambiario en el sector farmacéuticos animal en Colombia(Universidad EAFIT, 2023) Pérez Gómez, Fredy Herney; Arias Sánchez, Juan ManuelThis work seeks to evaluate and model, using descriptive statistics and econometric methods, the viability of strategies that mitigate the effects caused by exchange risk that impacts the liquidity and continuity over time of organizations. For this case study, the focus will be on the pharmaceutical laboratories of the animal sector in Colombia, based on the change exposure you have due to the composition of their operational structure, which becomes a critical point for its financial and operational performance. The development of this field case will focus on the review of a statistical method applied in Excel where the different financial instruments used in Colombia, such as Forward, futures and others, will be evaluated using an econometric model; validating its economic and accounting application, which must be aligned with the normal ones currently accepted for hedge accounting according to International Standard, the result will validate which actions will be indicated to implement and have a lower level of exposure to currency risk for these companies in Colombia, the date range is from January 2015 to 2021 years of greatest devaluation recorded between the peso versus dollar pair.