IDEAS home Printed from https://ideas.repec.org/a/ere/journl/vxxxvy2016i2p175-194.html
   My bibliography  Save this article

Modelación de las dinámicas, volatilidades e interrelaciones de los rendimientos del petróleo mexicano, BRENT y WTI

Author

Listed:
  • Antonio Ruiz-Porras

    (Departamento de Métodos Cuantitativos. Universidad de Guadalajara, CUCEA. Zapopan, Jalisco, México.)

  • Javier Emmanuel Anguiano Pita

    (Universidad de Guadalajara, CUCEA. Zapopan, Jalisco, México.)

Abstract

Estudiamos las dinámicas, volatilidades e interrelaciones de los rendimientos del petróleo mexicano (MME), Brent y WTI con doce modelos GARCH multivariados. Los resultados sugieren que: 1) la volatilidad de la MME es mayor que la del WTI y menor que la del Brent; 2) el modelo AR(1)-TGARCH(1,1) con una distribución t-de-Student multivariada es el que mejor describe los rendimientos; 3) existen algunas interrelaciones entre las volatilidades de los rendimientos y 4) las buenas y malas noticias tienen impactos asimétricos sobre las volatilidades. El estudio usa datos diarios de los precios spot del petróleo y de sus rendimientos para el periodo 03/01/2000-11/02/2016.

Suggested Citation

  • Antonio Ruiz-Porras & Javier Emmanuel Anguiano Pita, 2016. "Modelación de las dinámicas, volatilidades e interrelaciones de los rendimientos del petróleo mexicano, BRENT y WTI," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 175-194, November.
    • Handle: RePEc:ere:journl:v:xxxv:y:2016:i:2:p:175-194
    as

    Download full text from publisher

    File URL: http://www.economia.uanl.mx/revistaensayos/xxxv/2/3_Modelacion_Porras.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955, January.
    3. Liwei Fan & Huiping Li, 2015. "Volatility analysis and forecasting models of crude oil prices: a review," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 5-17.
    4. Regnier, Eva, 2007. "Oil and energy price volatility," Energy Economics, Elsevier, vol. 29(3), pages 405-427, May.
    5. Papapetrou, Evangelia, 2001. "Oil price shocks, stock market, economic activity and employment in Greece," Energy Economics, Elsevier, vol. 23(5), pages 511-532, September.
    6. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    7. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Dávila-Pérez, Javier & Nuñez-Mora, Jose Antonio & Ruiz-Porras, Antonio, 2007. "Volatilidad del Precio de la Mezcla Mexicana de Exportación [Price Volatility of the Mexican Export Crude Oil Blend]," MPRA Paper 3562, University Library of Munich, Germany.
    10. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    11. Backus, David K. & Crucini, Mario J., 2000. "Oil prices and the terms of trade," Journal of International Economics, Elsevier, vol. 50(1), pages 185-213, February.
    12. Peter Ferderer, J., 1996. "Oil price volatility and the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 1-26.
    13. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    14. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    15. Hui Guo & Kevin L. Kliesen, 2005. "Oil price volatility and U.S. macroeconomic activity," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 669-684.
    16. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    3. Vinish Kathuria & Jyotirmayee Sabat, 2020. "Is Exchange Rate Volatility Symmetric to Oil Price Volatility? An Investigation for India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 525-550, September.
    4. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    5. El Hedi Arouri, Mohamed & Jouini, Jamel & Nguyen, Duc Khuong, 2011. "Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1387-1405.
    6. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    7. Maghyereh, Aktham I. & Awartani, Basel & Tziogkidis, Panagiotis, 2017. "Volatility spillovers and cross-hedging between gold, oil and equities: Evidence from the Gulf Cooperation Council countries," Energy Economics, Elsevier, vol. 68(C), pages 440-453.
    8. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    9. Y. K. Tse, 2002. "Residual-based diagnostics for conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 358-374, June.
    10. Degiannakis, Stavros & Filis, George & Floros, Christos, 2013. "Oil and stock returns: Evidence from European industrial sector indices in a time-varying environment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 175-191.
    11. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    12. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    13. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    14. R. Khalfaoui & M. Boutahar, 2012. "Portfolio Risk Evaluation: An Approach Based on Dynamic Conditional Correlations Models and Wavelet Multi-Resolution Analysis," Working Papers halshs-00793068, HAL.
    15. Arouri, Mohamed El Hedi & Lahiani, Amine & Nguyen, Duc Khuong, 2011. "Return and volatility transmission between world oil prices and stock markets of the GCC countries," Economic Modelling, Elsevier, vol. 28(4), pages 1815-1825, July.
    16. Rafiq, Shudhasattwa & Sgro, Pasquale & Apergis, Nicholas, 2016. "Asymmetric oil shocks and external balances of major oil exporting and importing countries," Energy Economics, Elsevier, vol. 56(C), pages 42-50.
    17. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. Muhammad Irfan Malik & Abdul Rashid, 2017. "Return And Volatility Spillover Between Sectoral Stock And Oil Price: Evidence From Pakistan Stock Exchange," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-22, June.
    19. Rotta, Pedro Nielsen & Pereira, Pedro L. Valls, 2013. "Analysis of contagion from the constant conditional correlation model with Markov regime switching," Textos para discussão 340, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    20. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Energy Policy, Elsevier, vol. 69(C), pages 227-247.

    More about this item

    Keywords

    Rendimientos del petróleo; MME; Brent; WTI; Modelos GARCH Multivariados;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ere:journl:v:xxxv:y:2016:i:2:p:175-194. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dora María Vega Facio (email available below). General contact details of provider: https://edirc.repec.org/data/feualmx.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.