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

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  • Jong-Min Kim and 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 and Hojin Jung, 2018. "Dependence Structure between Oil Prices, Exchange Rates, and Interest Rates," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
  • Handle: RePEc:aen:journl:ej39-2-jung
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    Cited by:

    1. F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti, 2020. "Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 373-395, June.
    2. Vincenzo Candila & Denis Maximov & Alexey Mikhaylov & Nikita Moiseev & Tomonobu Senjyu & Nicole Tryndina, 2021. "On the Relationship between Oil and Exchange Rates of Oil-Exporting and Oil-Importing Countries: From the Great Recession Period to the COVID-19 Era," Energies, MDPI, vol. 14(23), pages 1-18, December.
    3. Jin Shang & Shigeyuki Hamori, 2023. "Differential Tail Dependence between Crude Oil and Forex Markets in Oil-Importing and Oil-Exporting Countries during Recent Crisis Periods," Sustainability, MDPI, vol. 15(19), pages 1-24, October.
    4. Liu, Siyao & Fang, Wei & Gao, Xiangyun & Wang, Ze & An, Feng & Wen, Shaobo, 2020. "Self-similar behaviors in the crude oil market," Energy, Elsevier, vol. 211(C).
    5. Witold Orzeszko, 2021. "Nonlinear Causality between Crude Oil Prices and Exchange Rates: Evidence and Forecasting," Energies, MDPI, vol. 14(19), pages 1-16, September.
    6. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
    7. repec:mth:ijafr8:v:9:y:2019:i:1:p:298-316 is not listed on IDEAS
    8. Aganin, Artem & Peresetsky, Anatoly, 2018. "Volatility of ruble exchange rate: Oil and sanctions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 52, pages 5-21.
    9. Turgut Yokuş, 2024. "Early Warning Systems for World Energy Crises," Sustainability, MDPI, vol. 16(6), pages 1-18, March.
    10. Parul Bhatia, 2021. "Sustainability Of Exchange Rates And Crude Oil Prices Connection With Covid-19: An Investigation For Brics," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 5, pages 19-29, October.
    11. Kamesh Anand K & Aswini Kumar Mishra, 2023. "Market Connectedness and Volatility Spillovers: A Meta-Literature Review," Commodities, MDPI, vol. 2(3), pages 1-19, June.
    12. Sun, Qingru & An, Haizhong & Gao, Xiangyun & Guo, Sui & Wang, Ze & Liu, Siyao & Wen, Shaobo, 2019. "Effects of crude oil shocks on the PPI system based on variance decomposition network analysis," Energy, Elsevier, vol. 189(C).

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    JEL classification:

    • F0 - International Economics - - General

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