Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos

Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)Lamos Diaz, HenryVecino Arenas, Carlos EnriqueJerez Barajas, Mayra Alejandra2024-03-0320162024-03-0320162016https://noesis.uis.edu.co/handle/20.500.14071/34743El petróleo se ha convertido en un gran protagonista en la economía global por ser el eje principal de la mayoría de industrias manufactureras y de transporte, afectando de manera significativa la dinámica de las economías de los países en donde su principal actividad económica se fundamenta en la explotación e industrialización del petróleo. La constante variabilidad en el precio del petróleo a través del tiempo, ha generado la necesidad de que a nivel científico se busquen o generen modelos matemáticos que permitan pronosticar a corto y largo plazo el precio del petróleo de manera eficiente.application/pdfspahttp://creativecommons.org/licenses/by/4.0/Precios Del PetróleoModelos EstocásticosPrevisiónArimaGbm Y Simulación.Modelación del comportamiento de los precios del petróleo mediante modelos estocásticosUniversidad Industrial de SantanderTesis/Trabajo de grado - Monografía - PregradoUniversidad Industrial de Santanderhttps://noesis.uis.edu.coOil has become one of the principal actor in the global economy as the main focus of most manufacturing industries and transportaffecting significantly the dynamics of the economies of the countries where its main economic activity is based on the oil exploitation and industrialization. The constant variability in the price of oil over the timehas generated the need in a scientific level to search or generate mathematical models to predict short and long term oil prices in a efficiently way. In this research we studied and analyzed the stochastic ARIMA models and Geometric Brownian Motion (GBM) with possible mean reversion and Poisson jumpsin order to compare the effectiveness of each model when making a forecast. Simulations for different periods of time were made on the database in oil prices WTI and BRENT references. It has been concluded in this thesis that the stochastic process ARIMA implemented with an additional stochastic process (ARCH - GARCH) manages to generate a more efficient outcome than the Geometric Brownian Motion in terms of accuracy and volatility. 3Oil Prices, Stochastic Models, Forecasting, Arima, Gbm And Simulation.info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)