Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos
El 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 e...
- Autores:
-
Jerez Barajas, Mayra Alejandra
- Tipo de recurso:
- http://purl.org/coar/version/c_b1a7d7d4d402bcce
- Fecha de publicación:
- 2016
- Institución:
- Universidad Industrial de Santander
- Repositorio:
- Repositorio UIS
- Idioma:
- spa
- OAI Identifier:
- oai:noesis.uis.edu.co:20.500.14071/34743
- Palabra clave:
- Precios Del Petróleo
Modelos Estocásticos
Previsión
Arima
Gbm Y Simulación.
Oil has become one of the principal actor in the global economy as the main focus of most manufacturing industries and transport
affecting 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 time
has 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 jumps
in 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. 3
- Rights
- License
- Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by-nc/4.0Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Lamos Diaz, HenryVecino Arenas, Carlos EnriqueJerez Barajas, Mayra Alejandra2024-03-03T22:40:41Z20162024-03-03T22:40:41Z20162016https://noesis.uis.edu.co/handle/20.500.14071/34743Universidad Industrial de SantanderUniversidad Industrial de Santanderhttps://noesis.uis.edu.coEl 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.PregradoIngeniero IndustrialModeling the behavior of oil prices by stochastic models 3application/pdfspaUniversidad Industrial de SantanderFacultad de Ingenierías FisicomecánicasIngeniería IndustrialEscuela de Estudios Industriales y EmpresarialesPrecios Del PetróleoModelos EstocásticosPrevisiónArimaGbm Y Simulación.Oil 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. 3Modelación del comportamiento de los precios del petróleo mediante modelos estocásticosOil Prices, Stochastic Models, Forecasting, Arima, Gbm And Simulation.Tesis/Trabajo de grado - Monografía - Pregradohttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_b1a7d7d4d402bcceORIGINALCarta de autorización.pdfapplication/pdf292418https://noesis.uis.edu.co/bitstreams/dd18655d-96fb-457b-a43a-04456c81a334/download6af74a70f1237cfca9a90bdc31a455b4MD51Documento.pdfapplication/pdf4024813https://noesis.uis.edu.co/bitstreams/35b839e4-dc8e-4560-890c-d1a7b2c10be8/download8ebe906f3bc6b4aca52734a6b28d6d92MD52Nota de proyecto.pdfapplication/pdf190352https://noesis.uis.edu.co/bitstreams/09fc0f61-5077-46e4-bea2-04585ed20632/download5fb08a39c4e1513df2908bb92e1a6487MD5320.500.14071/34743oai:noesis.uis.edu.co:20.500.14071/347432024-03-03 17:40:41.449http://creativecommons.org/licenses/by-nc/4.0http://creativecommons.org/licenses/by/4.0/open.accesshttps://noesis.uis.edu.coDSpace at UISnoesis@uis.edu.co |
dc.title.none.fl_str_mv |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
dc.title.english.none.fl_str_mv |
Oil Prices, Stochastic Models, Forecasting, Arima, Gbm And Simulation. |
title |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
spellingShingle |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos Precios Del Petróleo Modelos Estocásticos Previsión Arima Gbm Y Simulación. Oil has become one of the principal actor in the global economy as the main focus of most manufacturing industries and transport affecting 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 time has 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 jumps in 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. 3 |
title_short |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
title_full |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
title_fullStr |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
title_full_unstemmed |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
title_sort |
Modelación del comportamiento de los precios del petróleo mediante modelos estocásticos |
dc.creator.fl_str_mv |
Jerez Barajas, Mayra Alejandra |
dc.contributor.advisor.none.fl_str_mv |
Lamos Diaz, Henry Vecino Arenas, Carlos Enrique |
dc.contributor.author.none.fl_str_mv |
Jerez Barajas, Mayra Alejandra |
dc.subject.none.fl_str_mv |
Precios Del Petróleo Modelos Estocásticos Previsión Arima Gbm Y Simulación. |
topic |
Precios Del Petróleo Modelos Estocásticos Previsión Arima Gbm Y Simulación. Oil has become one of the principal actor in the global economy as the main focus of most manufacturing industries and transport affecting 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 time has 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 jumps in 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. 3 |
dc.subject.keyword.none.fl_str_mv |
Oil has become one of the principal actor in the global economy as the main focus of most manufacturing industries and transport affecting 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 time has 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 jumps in 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. 3 |
description |
El 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. |
publishDate |
2016 |
dc.date.available.none.fl_str_mv |
2016 2024-03-03T22:40:41Z |
dc.date.created.none.fl_str_mv |
2016 |
dc.date.issued.none.fl_str_mv |
2016 |
dc.date.accessioned.none.fl_str_mv |
2024-03-03T22:40:41Z |
dc.type.local.none.fl_str_mv |
Tesis/Trabajo de grado - Monografía - Pregrado |
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http://purl.org/coar/resource_type/c_7a1f |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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https://noesis.uis.edu.co/handle/20.500.14071/34743 |
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Universidad Industrial de Santander |
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Universidad Industrial de Santander |
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https://noesis.uis.edu.co |
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https://noesis.uis.edu.co/handle/20.500.14071/34743 https://noesis.uis.edu.co |
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Universidad Industrial de Santander |
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Universidad Industrial de Santander |
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Ingeniería Industrial |
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