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Dependence Structure between Oil Prices, Exchange Rates, and Interest Rates

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  • Jong-Min Kim
  • Hojin Jung

Abstract

This article unveils the dependence structure between crude oil prices, exchange rates, and the United States interest rates. We begin by using asymmetric GARCH models to examine the marginal behavior of the returns, and then various copulas are used to understand extreme market co-movements. We also investigate the causal relationship and the spillover effects by using the Granger causality test and the BEKK representation of a multivariate GARCH process. Over the 1998-2017 period, we find evidence of an inverse relationship between the U.S. interest rates and the crude oil prices. Oil-exchange rate linkages become stronger for most of the oil dependent countries considered in this article in the aftermath of the global financial crisis. There is also asymmetric tail dependence for almost all of the oil-exchange rate pairs. The results of Granger causality tests mainly indicate that crude oil prices Granger cause exchange rates. We also find that there are unidirectional volatility spillovers from WTI to exchange rates for oil exporting countries and to the U.S. interest rates. These findings provide important implications for investors to hedge the possible risk with international portfolio diversification.

Suggested Citation

  • Jong-Min Kim & Hojin Jung, 2018. "Dependence Structure between Oil Prices, Exchange Rates, and Interest Rates," The Energy Journal, , vol. 39(2), pages 259-280, March.
  • Handle: RePEc:sae:enejou:v:39:y:2018:i:2:p:259-280
    DOI: 10.5547/01956574.39.2.jkim
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    1. Jozef Baruník & Evžen KoÄ enda b,a & Lukáš Vácha, 2016. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, , vol. 37(1), pages 136-158, January.
    2. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2012. "Oil prices, exchange rates and emerging stock markets," Energy Economics, Elsevier, vol. 34(1), pages 227-240.
    3. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    4. Peter R. Hartley & Kenneth B. Medlock III, 2014. "The Relationship between Crude Oil and Natural Gas Prices: The Role of the Exchange Rate," The Energy Journal, , vol. 35(2), pages 25-44, April.
    5. Abhay Abhyankar, Bing Xu, and Jiayue Wang, 2013. "Oil Price Shocks and the Stock Market: Evidence from Japan," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    6. Cologni, Alessandro & Manera, Matteo, 2008. "Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries," Energy Economics, Elsevier, vol. 30(3), pages 856-888, May.
    7. Fornari, Fabio & Mele, Antonio, 1997. "Sign- and Volatility-Switching ARCH Models: Theory and Applications to International Stock Markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 49-65, Jan.-Feb..
    8. Takamitsu Kurita, 2010. "Time Series Analysis of Transatlantic Market Interactions: Evidence from Crude Oil and Gasoline Prices," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(2), pages 157-173, August.
    9. Fatum, Rasmus & Scholnick, Barry, 2006. "Do Exchange Rates Respond to Day-to-Day Changes in Monetary Policy Expectations When No Monetary Policy Changes Occur?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1641-1657, September.
    10. Arora, Vipin & Tanner, Matthew, 2013. "Do oil prices respond to real interest rates?," Energy Economics, Elsevier, vol. 36(C), pages 546-555.
    11. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    12. Klein, Tony & Walther, Thomas, 2016. "Oil price volatility forecast with mixture memory GARCH," Energy Economics, Elsevier, vol. 58(C), pages 46-58.
    13. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    14. Craig S. Hakkio, 1986. "Interest rates and exchange rates--what is the relationship?," Economic Review, Federal Reserve Bank of Kansas City, vol. 71(Nov), pages 33-43.
    15. 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.
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    2. Yan, Wan-Lin & Cheung, Adrian (Wai Kong), 2024. "Connectedness among Chinese climate policy uncertainty, exchange rate, Chinese and international crude oil markets: Insights from time and frequency domain analyses of high order moments," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).

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