IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/98515.html

The Relationship between Crude Oil Prices and Exchange Rates

Author

Listed:
  • Salles, Andre Assis de

Abstract

Crude oil prices are influenced by several events that occur randomly, for example, the weather, the available stocks of oil, the economic growth, the variation in the industrial production, political or geopolitical aspects, exchange rate movements, and so on. Oil price volatility brings uncertainties for the world economy. Despite the difficulty in working with oil price time series, a lot of researches have been developing ways to better understand the stochastic process which represents oil prices movements. This work introduces an alternative methodology, with a Bayesian approach, for the construction of forecasting models to study the returns of oil prices. The methodology introduced here takes in consideration the violation of homoskedasticity and the occurrence of abnormal information, or the non-Gaussian distribution, in the construction of the price forecast models. Moreover, this work examines the relationship between crude oil prices and exchange rate through a cointegration test. The data used in this study consists of the daily closing exchange rate of US dollar to Euro, and oil prices of WTI, West Texas Intermediate, and Brent types, from January 2005 to March 2009. The results do not show the acceptance of cointegration hypothesis. With the presented models, it is possible to infer that the exchange rate is important to explain the oil barrel returns.

Suggested Citation

  • Salles, Andre Assis de, 2012. "The Relationship between Crude Oil Prices and Exchange Rates," MPRA Paper 98515, University Library of Munich, Germany, revised 2019.
    • Handle: RePEc:pra:mprapa:98515
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/98515/1/MPRA_paper_98515.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    2. Chen, Shiu-Sheng & Chen, Hung-Chyn, 2007. "Oil prices and real exchange rates," Energy Economics, Elsevier, vol. 29(3), pages 390-404, May.
    3. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    4. Sadorsky, Perry, 2000. "The empirical relationship between energy futures prices and exchange rates," Energy Economics, Elsevier, vol. 22(2), pages 253-266, April.
    5. Panas, Epaminondas & Ninni, Vassilia, 2000. "Are oil markets chaotic? A non-linear dynamic analysis," Energy Economics, Elsevier, vol. 22(5), pages 549-568, October.
    6. 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. Zhang, Yue-Jun & Fan, Ying & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Spillover effect of US dollar exchange rate on oil prices," Journal of Policy Modeling, Elsevier, vol. 30(6), pages 973-991.
    2. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
    3. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    4. Hassan Anjum, 2019. "Estimating volatility transmission between oil prices and the US Dollar exchange rate under structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(4), pages 750-763, October.
    5. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    6. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    7. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Working Papers 0501, University of Crete, Department of Economics.
    8. Bauer, Rob M M J & Nieuwland, Frederick G M C & Verschoor, Willem F C, 1994. "German Stock Market Dynamics," Empirical Economics, Springer, vol. 19(3), pages 397-418.
    9. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2015. "The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis," Energy Economics, Elsevier, vol. 51(C), pages 54-66.
    10. Takaishi, Tetsuya, 2017. "Rational GARCH model: An empirical test for stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 451-460.
    11. Estrada, Javier & Peña, Juan Ignacio, 1995. "Empirical evidence on the impact of European insider trading regulations," DEE - Working Papers. Business Economics. WB 7068, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    12. Kai Yang & Qingqing Zhang & Xinyang Yu & Xiaogang Dong, 2023. "Bayesian inference for a mixture double autoregressive model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 188-207, May.
    13. 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.
    14. Blagica Novkovska & Gordana Serafimovic, 2018. "Recognizing The Vulnerability Of Generation Z To Economic And Social Risks," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 29-37.
    15. Zied Ftiti & Aviral Tiwari & Ibrahim Fatnassi, 2014. "Oil price and macroeconomy in India – An evolutionary cospectral coherence approach," Working Papers 2014-68, Department of Research, Ipag Business School.
    16. Maria Malmierca-Ordoqui & Luis A. Gil-Alana & Manuel Monge, 2024. "Fractional cointegration between energy imports to the EURO area and exchange rates to the US dollar," Empirical Economics, Springer, vol. 66(2), pages 859-882, February.
    17. Bai, Shuming & Koong, Kai S., 2018. "Oil prices, stock returns, and exchange rates: Empirical evidence from China and the United States," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 12-33.
    18. Muñoz, M. Pilar & Dickey, David A., 2009. "Are electricity prices affected by the US dollar to Euro exchange rate? The Spanish case," Energy Economics, Elsevier, vol. 31(6), pages 857-866, November.
    19. Salisu, Afees A. & Mobolaji, Hakeem, 2013. "Modeling returns and volatility transmission between oil price and US–Nigeria exchange rate," Energy Economics, Elsevier, vol. 39(C), pages 169-176.
    20. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:pra:mprapa:98515. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.