Examinando por Materia "Monte Carlo simulation"
Mostrando 1 - 9 de 9
Resultados por página
Opciones de ordenación
Ítem Application of sensitivity- and uncertainty-based techniques for the assessment of epidemiological models in real-life study cases(Universidad EAFIT, 2019) Rojas Díaz, Daniel; Vélez Sánchez, Carlos Mario; Puerta Yepes, María EugeniaUncertainty analysis (UA) and sensitivity analysis (SA) are tools to assess and to quantify the uncertainty spread from the input factors (parameters and initial states) to the model output, taking into account the effect of the interactions among those factors. Throughout the following works, I treat UA as a graphical assessment of uncertainty propagation based on Monte Carlo simulation, which makes it possible to state a range for the model output in cases where it is considered relevant. On the other hand, I privilege the global approach for SA instead of the local one, since the first attempts to quantify the uncertainty contribution of the model factors in their entire distribution range while the second one is only informative for a single locus in the distribution. In this way, when applying global UA/SA on a model, it is possible to identify those factors that mostly determine the model behavior. Furthermore, I have noticed that the concepts and principles of UA/SA are associated with other main tasks in modeling, as factors estimation and confidence intervals achievement: Briefly, those non-identifiable factors in a model (factors whose value can not be estimated uniquely from some information about output data) should belong to the categories of non-sensible or sensitive but correlated from SA; and, the sub-space of the space of factors where the factors may jointly exist producing a model output that fits, in some extent, to a given output data, could be approximately estimated with UA-based approaches, constituting a new kind of confidence interval. Thus, in this compendium, I present five works related to the applications of UA/SA techniques as well as its relevance. The objective of those applications evolves from the most logically immediate to some derived and more complex ones, though still preserving the model pertinence as a central topic.Ítem Datos atípicos en las predicciones: una solución al problema(2021-06-10) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Lio, Yuhlong; Vicerrectoría de Descubrimiento y CreaciónÍtem Datos atípicos en las predicciones: una solución al problema(Universidad EAFIT, 2020-12-01) Martinez Guerrero, Christian Alexander; Martinez-Guerrero, Christian Alexander; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Yuhlong, Lio; Estudios en MantenimientoÍtem Diseño de un sistema de gestión de riesgos para la compañía Microminerales S. A. S.(Universidad EAFIT, 2018) Ospina Ospina, Julián David; Giraldo Hernández, Gina María; Gómez Salazar, Elkin ArcesioThis work presents the design of a risk management system for the operating processes of the company Microminerales S. A. S. The main objective is to generate a tool to identify, qualify, evaluate and implement treatment measures and monitor the risks that exist in each process and that are linked with strategic planning. The work was referenced in accordance with the Colombian technical norm NTC-ISO 31000 and the Risicar method, regarding conceptual considerations, and the Monte Carlo simulation method was used for statistical simulations. The work seeks to obtain benefits such as: more probability to achieve the company's strategic objectives, improve management controls, improve process measurement systems, minimize losses and generate a culture of prevention to improve decision making.Ítem Gestión del riesgo de crédito en Project Finance(Universidad EAFIT, 2019) Rivera Galvis, Juan Pablo; Hernández Ramírez, Mónica María; Bello Bernal, Miguel ÁngelThe management of credit risk under the Project Finance methodology aims to observe the feasibility of a project based on the performance of the debt service coverage ratio. This management seeks to ensure the stability of the operating cash flows to respond to the lenders. This risk is calculated using the Monte Carlo simulation, estimating the probability that operating cash flows will fall below a certain value. In the case of the company Fuentes de Agua Viva, credit risk was evidenced in the first years of project execution, explained by the liquidity limitations during this period; thus, it was decided to opt for a long-term loan that entailed low debt payments in the first years of amortization.Ítem Henry Velasco, un ingeniero que cambió su vida en EAFIT(2021-04-05) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Velasco, Henry; Laniado, Henry; Toro, Mauricio; Leiva, Victor; Lio, Yuhlong; Vicerrectoría de Descubrimiento y CreaciónÍtem Modelo de gestión del riesgo de cartera y creación de valor en una empresa de servicios públicos(Universidad EAFIT, 2024) Taborda Urriago, Sandra Patricia; Frasser Quiñones, Stefanny; Arango Londoño, Carlos MarioÍtem Valoración de una fintech a través de opciones reales (ROV)(Universidad EAFIT, 2019) Palacio Marín, Laura; Huepa Bolívar, Carlos Eduardo; Bravo Vélez, Juan FelipeThe discounted cash flow (DCF) considers the variables statically or deterministically. For this reason, through a Monte Carlo simulation proceed to sensitize variables of the environment and the company randomly, considering the main indicators of value generation that can be obtained in the DCF. Additionally, as a complementary methodology, a valuation is made by real options considering the management flexibility implicit in the project; this model can translate this flexibility into volatility, allowing to incorporate the extrinsic value of upside potential risk of the investment.Ítem VaR corporativo : una aplicación en la industria petroquímica colombiana(Universidad EAFIT, 2019) Castañeda Sanchez, Laura; Severiche Calderon, Natalia; Manco López, OscarThis study estimates the EaR (Earnings at Risk) for a company in the Colombian petrochemical sector through the impact of its main macroeconomic risk variables: oil, Libor (three months) and the representative market rate in its main financial indicators, given a level of confidence for a projected period of time between 2019 and 2021 and based on the results of 2017 and 2018. The methodology used is based on the definition of the probability distributions for the risk variables, which will be applied in the Montecarlo simulation process, where their impact on the projected financial results will be determined.