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The Relationship between Crude Oil Prices and Exchange Rates

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Chen, Shiu-Sheng & Chen, Hung-Chyn, 2007. "Oil prices and real exchange rates," Energy Economics, Elsevier, vol. 29(3), pages 390-404, May.
    4. 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.
    5. Sadorsky, Perry, 2000. "The empirical relationship between energy futures prices and exchange rates," Energy Economics, Elsevier, vol. 22(2), pages 253-266, April.
    6. Panas, Epaminondas & Ninni, Vassilia, 2000. "Are oil markets chaotic? A non-linear dynamic analysis," Energy Economics, Elsevier, vol. 22(5), pages 549-568, October.
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    More about this item

    Keywords

    Crude Oil Prices; Exchange Rate; Cointegration; Forecast Models; Bayesian Inference.;
    All these 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

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