Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.

Este artículo prueba el grado de integración de México en los mercados internacionales del petróleo a través de la evolución de las correlaciones dinámicas en periodos estables, de crisis e inestables. Las estimaciones del modelo GARCH-CCD muestran que las correlaciones son positivas y cambian con e...

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Autores:: De Jesús-Gutiérrez, Raúl

Tipo de recurso:: Article of investigation

Fecha de publicación:: 2019

Institución:: Universidad Católica de Colombia

Repositorio:: RIUCaC - Repositorio U. Católica

Idioma:: spa

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dc.title.spa.fl_str_mv	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
dc.title.translated.eng.fl_str_mv	Integration among world and low quality crude oil markets based on dynamic conditional correlations.
title	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
spellingShingle	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas. Financial crises Integration crude oil markets Dynamics conditional correlations Correlaciones condicionales dinámicas Crisis financieras Integración de los mercados de petróleo Correlações condicionais dinâmicas Crises financeiras Integração dos mercados de petróleo
title_short	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
title_full	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
title_fullStr	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
title_full_unstemmed	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
title_sort	Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.
dc.creator.fl_str_mv	De Jesús-Gutiérrez, Raúl
dc.contributor.author.spa.fl_str_mv	De Jesús-Gutiérrez, Raúl
dc.subject.eng.fl_str_mv	Financial crises Integration crude oil markets Dynamics conditional correlations
topic	Financial crises Integration crude oil markets Dynamics conditional correlations Correlaciones condicionales dinámicas Crisis financieras Integración de los mercados de petróleo Correlações condicionais dinâmicas Crises financeiras Integração dos mercados de petróleo
dc.subject.spa.fl_str_mv	Correlaciones condicionales dinámicas Crisis financieras Integración de los mercados de petróleo Correlações condicionais dinâmicas Crises financeiras Integração dos mercados de petróleo
description	Este artículo prueba el grado de integración de México en los mercados internacionales del petróleo a través de la evolución de las correlaciones dinámicas en periodos estables, de crisis e inestables. Las estimaciones del modelo GARCH-CCD muestran que las correlaciones son positivas y cambian con el tiempo en respuesta al origen de choques en los precios del petróleo para los periodos de relativa calma, crisis y turbulencia financiera. Asimismo, los resultados del estadístico-t y valor-p bootstrap confirman que las correlaciones son significativamente diferentes en periodos de estabilidad e inestabilidad con respecto a las correlaciones del periodo de crisis, lo que favorece la hipótesis de regionalización entre los mercados de petróleo. Los hallazgos tienen importantes implicaciones económicas y financieras para el gobierno y los consumidores.
publishDate	2019
dc.date.accessioned.none.fl_str_mv	2019-07-01 00:00:00 2023-01-23T16:15:28Z
dc.date.available.none.fl_str_mv	2019-07-01 00:00:00 2023-01-23T16:15:28Z
dc.date.issued.none.fl_str_mv	2019-07-01
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.doi.none.fl_str_mv	10.14718/revfinanzpolitecon.2019.11.2.8
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dc.relation.citationedition.spa.fl_str_mv	Núm. 2 , Año 2019
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dc.relation.ispartofjournal.spa.fl_str_mv	Revista Finanzas y Política Económica
dc.relation.references.spa.fl_str_mv	Adelman, M. A. (1984). International oil agreements. Energy Journal, 5(3), 1-9. https://www.jstor.org/stable/41321691 Bachmeier, L. J. y Griffin, J. M. (2006). Testing for market integration crude oil, coal, and natural gas. Energy Journal, 27(2), 55-71. https://econpapers.repec.org/article/aenjournl/2006v27-02-a04.htm Bentzen, J. (2007). Does OPEC influence crude oil price? Testing for co-movements and causality between regional crude oil prices. Applied Economics, 39(11), 1375-1385. 10.1080/00036840600606344 British Petroleum (2017). Statistical Review of World Energy. Londres: BP: Candelon, B., Joëts, M. y Tokpavi, S. (2013). Testing for Granger causality in distribution tails: An application to oil markets integration. Economic Modeling, 31, 276-285. 10.1016/j.econmod.2012.11.049 Caporin, M. y McAleer, M. (2013). Ten things you should know about the dynamic conditional correlation representation. Econometrics, 1 (1), 115-126. 10.3390/econometrics1010115 Collins, D. y Biekpe, N. (2003). Contagion a fear for Africa equity market? Journal of Economics and Business, 55(3), 285-297. 10.1016/S0148-6195(03)00020-1 Cook, J. (1998). California crude oil [Mimeo]. Recuperado de https://www.eia.doe.gov/pub/ De Jesús, R. (2016). Estrategias dinámicas de cobertura cruzada eficiente para el mercado del petróleo mexicano: evidencia de dos modelos GARCH multivariados con término de corrección de error. Economía: Teoría y Práctica, 44, 115-146. 10.24275/ETYPUAM/NE Domínguez, R. M., Venegas, F. y Palafox, A. O. (2018). Short-and long-term relations among prices of the Mexican Crude Oil Blend, West Texas Intermediate, and Brent: Market Trend and Risk Premia, 2005-2016. International Journal of Energy Economics and Policy, 8(3), 87-91. https://ideas.repec.org/a/eco/journ2/2018-03-13.html Energy Information Administration (2012). International Energy Statistics. Recuperado de https://www.eia.gov/international/data/world Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autore-gressive conditional heteroskedasticity models. Journal of Business and Economics Statistics, 20(3), 339-350. 10.1198/073500102288618487 Ewing, B. T y Harter, C. L. (2000). Co-movements of Alaska North Slope and UK Brent crude oil prices. Applied Economics Letters, 7(8), 553-558. 10.1080/13504850050033373 Fattouh, B. (2010). The dynamics of crude oil price differentials. Energy Economics, 32 (2), 334-342. 10.1016/j.eneco.2009.06.007 Forbes, K. y Rigobon, R. (2002). No contagion, only interdenpendence: measuring stock market co-movements. Journal of Finance, 57(5), 2223-2261. 10.1111/0022-1082.00494 Gülen, S. G. (1997). Regionalization in the world crude oil market. Energy Journal, 18(2), 109-127. Gülen, S. G. (1999). Regionalization in the world crude oil market: Further results. Energy Journal, 20(1), 125-139. https://researchers.dellmed.utexas.edu/en/publications/regionalization-in-the-world-crude-oil-market-further-evidence Hammoudeh, S., Thompson, M. y Ewing, B. (2008). Threshold cointegration analysis of crude oil benchmarks. Energy Journal, 29(4), 79-95. 10.2307/41323182 Jia, X., An, H., Fang, W. Sun, X. y Huang, X. (2015). How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective. Energy Economics, 49, 588-598. 10.1016/j.eneco.2015.03.008 Jiao, J. L., Fan, Y., Wei, Y. M., Han, Z. Y. y Zhang, J. T (2007). Analysis of the co-movements between Chinese and International crude oil price. International Journal of Global Energy, 27(1), 61-76. Ji, Q. y Fan, Y. (2015). Dynamic integration of world oil prices: A reinvestigation of globalisation vs. regionalization. Applied Energy, 155(1), 171-180. https://www.deepdyve.com/lp/elsevier/dynamic-integration-of-world-oil-prices-a-reinvestigation-of-Daf3SxZWrD Kleit, A.N. (2001). Are regional oil markets growing closer together? An arbitrage cost approach. Energy Journal, 22(2), 1-15. 10.5547/ISSN0195-6574-EJ-Vol22-No2-1 Kuck, K. y Schweikert, K. (2017). A Markov regime-switching model of crude oil market integration. Journal of Commodity Markets, 6, 16-31. 10.1016/j.jcomm.2017.03.001 Lanza, A., Manera, M. y McAleer, M. (2006). Modeling dynamic conditional correlations in WTI oil forward and futures returns. Finance Research Letters, 3 (2), 114-132. 10.1016/j.frl.2006.01.005 Laurent, S., Rombouts, J. V. y Violante, F. (2012). On the forecasting accuracy of multivariate GARCH models. Journal of Applied Econometrics, 27(6), 934-955. 10.1002/jae.1248 Li, R. y Leung, G. C. (2011). The integration of China into the world crude oil market since 1998. Energy Policy, 39(9), 5159-5165. https://ideas.repec.org/a/eee/enepol/v39y2011i9p5159-5166.html Liao, H. C., Lin, S. C. y Huang, H. C. (2014). Are crude oil markets globalized or regionalized? Evidence from WTI and Brent. Applied Economics Letters, 21 (4), 235-241. Liu, L., Chen, C. y Wan, J. (2013). Is world oil market "one great pool"? An example from China's and international oil market. Economic Modelling, 35, 364-373. 10.1016/j.econmod.2013.07.027 Lu, F., Hong, Y., Wang, S. Lai, K. y Liu, J. (2014). Time-varying Granger causality tests for applications in global crude oil markets. Energy Economics, 42, 289-298. 10.1016ZJ.eneco.2014.01.002 Milonas, N. y Henker, T (2001). Price spread and convenience yield behaviour in the international oil market. Applied Financial Economics, 11 (1), 23-36. 10.1080/09603100150210237 Montepeque, J. (2005). Sour crude pricing: A pressing global issue. Middle East Economic Survey, 48(14), 1-42. Politis, D. N. y Romano, J. P (1994). The stationary bootstrap. Journal of the American Statistical Association, 89(428), 1303-1313. 10.1080/01621459.1994.10476870 Reboredo, J. C. (2011). How do crude oil prices co-move? A copula approach. Energy Economics, 33(5), 948-955. https://ideas.repec.org/a/eee/eneeco/v33y2011i5p948-955.html Ruiz, A. y Anguiano, J. E. (2016). Modelación de las dinámicas, volatilidades e interrelaciones de los rendimientos del petróleo mexicano, BRENT y WTI. Ensayos, Revista de Economía, 2, 175-194. https://ideas.repec.org/a/ere/journl/vxxxvy2016i2p175-194.html Weiner, R. J. (1991). Is the world oil market one great pool? Energy Journal, 12(3), 95-107. https://pdfs.semanticscholar.org/cf53/f3cd19d2dfc859ada89d740c4910c6fe333e.pdf Wilmot, N. A. (2013). Cointegration in the oil market among regional blends. International Journal Energy Economic Policy, 3(4), 424-433. https://experts.umn.edu/en/publications/cointegration-in-the-oil-market-among-regional-blends
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spelling	De Jesús-Gutiérrez, Raúlec72b255-c711-4add-80b4-843bcc67870c2019-07-01 00:00:002023-01-23T16:15:28Z2019-07-01 00:00:002023-01-23T16:15:28Z2019-07-01Este artículo prueba el grado de integración de México en los mercados internacionales del petróleo a través de la evolución de las correlaciones dinámicas en periodos estables, de crisis e inestables. Las estimaciones del modelo GARCH-CCD muestran que las correlaciones son positivas y cambian con el tiempo en respuesta al origen de choques en los precios del petróleo para los periodos de relativa calma, crisis y turbulencia financiera. Asimismo, los resultados del estadístico-t y valor-p bootstrap confirman que las correlaciones son significativamente diferentes en periodos de estabilidad e inestabilidad con respecto a las correlaciones del periodo de crisis, lo que favorece la hipótesis de regionalización entre los mercados de petróleo. Los hallazgos tienen importantes implicaciones económicas y financieras para el gobierno y los consumidores.This paper tests the degree of integration between Mexico’s and world crude oil markets throughout the evolution of dynamics correlations during the stable, crisis and volatile periods. The estimations of DCC-GARCH model show that the correlations are positive and time-varying in responds to the origin of the oil price shocks in periods of relative calm and financial turmoil. Likewise, the results of statistic-t and bootstrap p-value confirm strongly that the correlations in the crisis period are significantly different from those in the stable and volatile periods, which provides evidence in favor of the regionalization hypothesis between crude oil markets. The findings have important economic and financial implications for the government and consumers.application/pdftext/htmltext/xml10.14718/revfinanzpolitecon.2019.11.2.82011-76632248-6046https://hdl.handle.net/10983/29404https://doi.org/10.14718/revfinanzpolitecon.2019.11.2.8spaUniversidad Católica de Colombiahttps://revfinypolecon.ucatolica.edu.co/article/download/2574/3076https://revfinypolecon.ucatolica.edu.co/article/download/2574/3108https://revfinypolecon.ucatolica.edu.co/article/download/2574/3487Núm. 2 , Año 2019374235311Revista Finanzas y Política EconómicaAdelman, M. A. (1984). International oil agreements. Energy Journal, 5(3), 1-9. https://www.jstor.org/stable/41321691Bachmeier, L. J. y Griffin, J. M. (2006). Testing for market integration crude oil, coal, and natural gas. Energy Journal, 27(2), 55-71. https://econpapers.repec.org/article/aenjournl/2006v27-02-a04.htmBentzen, J. (2007). Does OPEC influence crude oil price? Testing for co-movements and causality between regional crude oil prices. Applied Economics, 39(11), 1375-1385. 10.1080/00036840600606344British Petroleum (2017). Statistical Review of World Energy. Londres: BP:Candelon, B., Joëts, M. y Tokpavi, S. (2013). Testing for Granger causality in distribution tails: An application to oil markets integration. Economic Modeling, 31, 276-285. 10.1016/j.econmod.2012.11.049Caporin, M. y McAleer, M. (2013). Ten things you should know about the dynamic conditional correlation representation. Econometrics, 1 (1), 115-126. 10.3390/econometrics1010115Collins, D. y Biekpe, N. (2003). Contagion a fear for Africa equity market? Journal of Economics and Business, 55(3), 285-297. 10.1016/S0148-6195(03)00020-1Cook, J. (1998). California crude oil [Mimeo]. Recuperado de https://www.eia.doe.gov/pub/De Jesús, R. (2016). Estrategias dinámicas de cobertura cruzada eficiente para el mercado del petróleo mexicano: evidencia de dos modelos GARCH multivariados con término de corrección de error. Economía: Teoría y Práctica, 44, 115-146. 10.24275/ETYPUAM/NEDomínguez, R. M., Venegas, F. y Palafox, A. O. (2018). Short-and long-term relations among prices of the Mexican Crude Oil Blend, West Texas Intermediate, and Brent: Market Trend and Risk Premia, 2005-2016. International Journal of Energy Economics and Policy, 8(3), 87-91. https://ideas.repec.org/a/eco/journ2/2018-03-13.htmlEnergy Information Administration (2012). International Energy Statistics. Recuperado de https://www.eia.gov/international/data/worldEngle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autore-gressive conditional heteroskedasticity models. Journal of Business and Economics Statistics, 20(3), 339-350. 10.1198/073500102288618487Ewing, B. T y Harter, C. L. (2000). Co-movements of Alaska North Slope and UK Brent crude oil prices. Applied Economics Letters, 7(8), 553-558. 10.1080/13504850050033373Fattouh, B. (2010). The dynamics of crude oil price differentials. Energy Economics, 32 (2), 334-342. 10.1016/j.eneco.2009.06.007Forbes, K. y Rigobon, R. (2002). No contagion, only interdenpendence: measuring stock market co-movements. Journal of Finance, 57(5), 2223-2261. 10.1111/0022-1082.00494Gülen, S. G. (1997). Regionalization in the world crude oil market. Energy Journal, 18(2), 109-127.Gülen, S. G. (1999). Regionalization in the world crude oil market: Further results. Energy Journal, 20(1), 125-139. https://researchers.dellmed.utexas.edu/en/publications/regionalization-in-the-world-crude-oil-market-further-evidenceHammoudeh, S., Thompson, M. y Ewing, B. (2008). Threshold cointegration analysis of crude oil benchmarks. Energy Journal, 29(4), 79-95. 10.2307/41323182Jia, X., An, H., Fang, W. Sun, X. y Huang, X. (2015). How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective. Energy Economics, 49, 588-598. 10.1016/j.eneco.2015.03.008Jiao, J. L., Fan, Y., Wei, Y. M., Han, Z. Y. y Zhang, J. T (2007). Analysis of the co-movements between Chinese and International crude oil price. International Journal of Global Energy, 27(1), 61-76.Ji, Q. y Fan, Y. (2015). Dynamic integration of world oil prices: A reinvestigation of globalisation vs. regionalization. Applied Energy, 155(1), 171-180. https://www.deepdyve.com/lp/elsevier/dynamic-integration-of-world-oil-prices-a-reinvestigation-of-Daf3SxZWrDKleit, A.N. (2001). Are regional oil markets growing closer together? An arbitrage cost approach. Energy Journal, 22(2), 1-15. 10.5547/ISSN0195-6574-EJ-Vol22-No2-1Kuck, K. y Schweikert, K. (2017). A Markov regime-switching model of crude oil market integration. Journal of Commodity Markets, 6, 16-31. 10.1016/j.jcomm.2017.03.001Lanza, A., Manera, M. y McAleer, M. (2006). Modeling dynamic conditional correlations in WTI oil forward and futures returns. Finance Research Letters, 3 (2), 114-132. 10.1016/j.frl.2006.01.005Laurent, S., Rombouts, J. V. y Violante, F. (2012). On the forecasting accuracy of multivariate GARCH models. Journal of Applied Econometrics, 27(6), 934-955. 10.1002/jae.1248Li, R. y Leung, G. C. (2011). The integration of China into the world crude oil market since 1998. Energy Policy, 39(9), 5159-5165. https://ideas.repec.org/a/eee/enepol/v39y2011i9p5159-5166.htmlLiao, H. C., Lin, S. C. y Huang, H. C. (2014). Are crude oil markets globalized or regionalized? Evidence from WTI and Brent. Applied Economics Letters, 21 (4), 235-241.Liu, L., Chen, C. y Wan, J. (2013). Is world oil market "one great pool"? An example from China's and international oil market. Economic Modelling, 35, 364-373. 10.1016/j.econmod.2013.07.027Lu, F., Hong, Y., Wang, S. Lai, K. y Liu, J. (2014). Time-varying Granger causality tests for applications in global crude oil markets. Energy Economics, 42, 289-298. 10.1016ZJ.eneco.2014.01.002Milonas, N. y Henker, T (2001). Price spread and convenience yield behaviour in the international oil market. Applied Financial Economics, 11 (1), 23-36. 10.1080/09603100150210237Montepeque, J. (2005). Sour crude pricing: A pressing global issue. Middle East Economic Survey, 48(14), 1-42.Politis, D. N. y Romano, J. P (1994). The stationary bootstrap. Journal of the American Statistical Association, 89(428), 1303-1313. 10.1080/01621459.1994.10476870Reboredo, J. C. (2011). How do crude oil prices co-move? A copula approach. Energy Economics, 33(5), 948-955. https://ideas.repec.org/a/eee/eneeco/v33y2011i5p948-955.htmlRuiz, A. y Anguiano, J. E. (2016). Modelación de las dinámicas, volatilidades e interrelaciones de los rendimientos del petróleo mexicano, BRENT y WTI. Ensayos, Revista de Economía, 2, 175-194. https://ideas.repec.org/a/ere/journl/vxxxvy2016i2p175-194.htmlWeiner, R. J. (1991). Is the world oil market one great pool? Energy Journal, 12(3), 95-107. https://pdfs.semanticscholar.org/cf53/f3cd19d2dfc859ada89d740c4910c6fe333e.pdfWilmot, N. A. (2013). Cointegration in the oil market among regional blends. International Journal Energy Economic Policy, 3(4), 424-433. https://experts.umn.edu/en/publications/cointegration-in-the-oil-market-among-regional-blendsRaúl de Jesús Gutiérrez - 2019info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-sa/4.0/https://revfinypolecon.ucatolica.edu.co/article/view/2574Financial crisesIntegration crude oil marketsDynamics conditional correlationsCorrelaciones condicionales dinámicasCrisis financierasIntegración de los mercados de petróleoCorrelações condicionais dinâmicasCrises financeirasIntegração dos mercados de petróleoIntegración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.Integration among world and low quality crude oil markets based on dynamic conditional correlations.Artículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionPublicationOREORE.xmltext/xml2631https://repository.ucatolica.edu.co/bitstreams/7ceb01dc-0f21-4266-b198-fb31652483d5/download2d3eb13ca04108e524557703aabdd04bMD5110983/29404oai:repository.ucatolica.edu.co:10983/294042023-03-24 17:02:14.487https://creativecommons.org/licenses/by-nc-sa/4.0/Raúl de Jesús Gutiérrez - 2019https://repository.ucatolica.edu.coRepositorio Institucional Universidad Católica de Colombia - RIUCaCbdigital@metabiblioteca.com

Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas.

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