IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v134y2019ics0301421519305506.html
   My bibliography  Save this article

Can switching from gasoline to aromatics mitigate the price risk of refineries?

Author

Listed:
  • Quintino, António
  • Catalão-Lopes, Margarida
  • Lourenço, João Carlos

Abstract

Oil prices wide fluctuations have been a constant in energy economics, influencing heavily the profits of oil companies. Even small oil prices changes imply wide variations in the refining margins, the main economic drivers of the profits of oil companies with relevant refining assets. The future will bring an even more volatile environment as the level of implementation of low-carbon policies increases, implying a declining demand for refined products for internal combustion engine vehicles. One of the possible paths to mitigate the refining margin volatility and the decreasing demand for refined products is to switch gasoline production to aromatics products, through new aromatics plants. In this paper we apply the copula-GARCH model with Monte Carlo simulation to evaluate the economic impacts of this production switching, supporting a European oil company's decision. The results show that the product switch success depends on gasoline prices and on how the aromatics plant is built, if in stand-alone mode or integrated with the refinery. It is also shown that the desired reduction of the integrated refining margin volatility is not achieved with the product switching.

Suggested Citation

  • Quintino, António & Catalão-Lopes, Margarida & Lourenço, João Carlos, 2019. "Can switching from gasoline to aromatics mitigate the price risk of refineries?," Energy Policy, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:enepol:v:134:y:2019:i:c:s0301421519305506
    DOI: 10.1016/j.enpol.2019.110963
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421519305506
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    2. David Cabedo, J. & Moya, Ismael, 2003. "Estimating oil price 'Value at Risk' using the historical simulation approach," Energy Economics, Elsevier, vol. 25(3), pages 239-253, May.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Tavares, Marina Elisabete Espinho & Szklo, Alexandre Salem & Machado, Giovani Vitoria & Schaeffer, Roberto & Mariano, Jacqueline Barboza & Sala, Janaina Francisco, 2006. "Oil refining expansion criteria for Brazil," Energy Policy, Elsevier, vol. 34(17), pages 3027-3040, November.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. K. C. Chen & R. Stephen Sears & Dah‐Nein Tzang, 1987. "Oil prices and energy futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 7(5), pages 501-518, October.
    7. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    8. Wu, Chih-Chiang & Chung, Huimin & Chang, Yu-Hsien, 2012. "The economic value of co-movement between oil price and exchange rate using copula-based GARCH models," Energy Economics, Elsevier, vol. 34(1), pages 270-282.
    9. Ahmad R. Jalali‐Naini & Maryam Kazemi Manesh, 2006. "Price volatility, hedging and variable risk premium in the crude oil market," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 30(2), pages 55-70, June.
    10. Jing Li & Henry Thompson, 2010. "A Note on the Oil Price Trend and GARCH Shocks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 159-166.
    11. Ji, Qiang & Fan, Ying, 2011. "A dynamic hedging approach for refineries in multiproduct oil markets," Energy, Elsevier, vol. 36(2), pages 881-887.
    12. Castelo Branco, David A. & Gomes, Gabriel L. & Szklo, Alexandre S., 2010. "Challenges and technological opportunities for the oil refining industry: A Brazilian refinery case," Energy Policy, Elsevier, vol. 38(6), pages 3098-3105, June.
    13. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nunes, Inês Carrilho & Catalão-Lopes, Margarida, 2020. "The impact of oil shocks on innovation for alternative sources of energy: Is there an asymmetric response when oil prices go up or down?," Journal of Commodity Markets, Elsevier, vol. 19(C).

    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. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    2. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    3. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    4. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 191-210.
    5. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.
    6. KANTA TANNIYOM & Paponpat Taveeapiradeecharoen & Prapatchon Jariyapan, 2015. "Modeling Dependency and Conditional Volatility between Asian Economic Community (AEC) Country Exchange Rate and Inflation Using the Copula-GARCH Model," Proceedings of International Academic Conferences 2704733, International Institute of Social and Economic Sciences.
    7. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    8. Chirag Shekhar & Mark Trede, 2017. "Portfolio Optimization Using Multivariate t-Copulas with Conditionally Skewed Margins," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 29-41, August.
    9. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    10. Bedoui, Rihab & Braiek, Sana & Guesmi, Khaled & Chevallier, Julien, 2019. "On the conditional dependence structure between oil, gold and USD exchange rates: Nested copula based GJR-GARCH model," Energy Economics, Elsevier, vol. 80(C), pages 876-889.
    11. Govindan, Rajesh & Al-Ansari, Tareq, 2019. "Computational decision framework for enhancing resilience of the energy, water and food nexus in risky environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 653-668.
    12. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    13. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    14. 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.
    15. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2011. "Multi-regime nonlinear capital asset pricing models," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1421-1438, April.
    16. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    17. Taras Bodnar & Nikolaus Hautsch, 2012. "Copula-Based Dynamic Conditional Correlation Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2012-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    19. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela ben, 2015. "Global factors driving structural changes in the co-movement between sharia stocks and sukuk in the Gulf Cooperation Council countries," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 311-329.
    20. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.

    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:eee:enepol:v:134:y:2019:i:c:s0301421519305506. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/enpol .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.