Relying on the D-Vine copula model, this paper delves into the hedging capabilities of Brent crude oil against the exchange rate of oil-exporting and oil-importing nations. The results affirm Brent crude oil’s role as a safeguard and a refuge against the fluctuations of major currencies. Furthermore, we reaffirm that oil retains its robust hedging and safe-haven attributes during times of crisis, with currency co-movements across all countries exhibiting greater correlation than during the entire dataset. Additionally, our empirical findings highlight an unusually positive correlation between Brent crude oil and the Russian exchange rate during the Russia-Ukraine conflict, demonstrating that oil functions as a less effective hedge and a less dependable refuge for the Russian exchange rate in such geopolitical turbulence.

1. Aas, K., Czado, C., Frigessi, A., et al. (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44(2), 182–198. https://doi.org/10.1016/j.insmatheco.2007.02.001
2. Akalpler, E., & BAKAR, A. N. (2018). The impact of oil price instability on economic growth: Evidence from Nigeria. Business Economics and Management Research Journal, 1(1), 39–53.
3. Alexander, J. M., Frey, R., Embrechts, P., Duffie, D., & Schaefer, S. (2005). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton University Press: Princeton and Oxford.
4. Ali, S. R. M., Mensi, W., Anik, K. I., et al. (2022). The impacts of COVID-19 crisis on spillovers between the oil and stock markets: Evidence from the largest oil importers and exporters. Economic Analysis and Policy, 73, 345–372. https://doi.org/10.1016/j.eap.2021.11.009
5. Aloui, R., Ben Aïssa, M. S., & Nguyen, D. K. (2013). Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach. Journal of International Money and Finance, 32, 719–738. https://doi.org/10.1016/j.jimonfin.2012.06.006
6. Amano, R. A., & Van Norden, S. (1998). Oil prices and the rise and fall of the US real exchange rate. Journal of international Money and finance, 17(2), 299–316.
7. Bagchi, B., & Paul, B. (2023). Effects of Crude Oil Price Shocks on Stock Markets and Currency Exchange Rates in the Context of Russia-Ukraine Conflict: Evidence from G7 Countries. Journal of Risk and Financial Management, 16(2), 64. https://doi.org/10.3390/jrfm16020064
8. Bal, D. P., & Rath, B. N. (2015). Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India. Energy Economics, 51, 149–156. https://doi.org/10.1016/j.eneco.2015.06.013
9. Basher, S. A., Haug, A. A., & Sadorsky, P. (2012). Oil prices, exchange rates and emerging stock markets. Energy Economics, 34(1), 227–240. https://doi.org/10.1016/j.eneco.2011.10.005
10. Beckmann, J., & Czudaj, R. (2013). Oil prices and effective dollar exchange rates. International Review of Economics & Finance, 27, 621–636. https://doi.org/10.1016/j.iref.2012.12.002
11. Beckmann, J., & Czudaj, R. L. (2022). Exchange rate expectation, abnormal returns, and the COVID-19 pandemic. Journal of Economic Behavior & Organization, 196, 1–25. https://doi.org/10.1016/j.jebo.2022.02.002
12. Beckmann, J., Czudaj, R. L., & Arora, V. (2020). The relationship between oil prices and exchange rates: Revisiting theory and evidence. Energy Economics, 88, 104772. https://doi.org/10.1016/j.eneco.2020.104772
13. Bedford, T., & Cooke, R. M. (2001). Probability density decomposition for conditionally dependent random variables modeled by vines. Annals of Mathematics and Artificial intelligence, 32, 245–268.
14. Bedford, T., & Cooke, R. M. (2002). Vines--a new graphical model for dependent random variables. The Annals of Statistics, 30(4). https://doi.org/10.1214/aos/1031689016
15. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307–327.
16. Boubaker, H., & Raza, S. A. (2016). On the dynamic dependence and asymmetric co-movement between the US and Central and Eastern European transition markets. Physica A: Statistical Mechanics and Its Applications, 459, 9–23. https://doi.org/10.1016/j.physa.2016.04.028
17. Boubaker, H., & Sghaier, N. (2013). Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach. Journal of Banking & Finance, 37(2), 361–377. https://doi.org/10.1016/j.jbankfin.2012.09.006
18. Bourghelle, D., Jawadi, F., & Rozin, P. (2021). Oil price volatility in the context of Covid-19. International Economics, 167, 39–49. https://doi.org/10.1016/j.inteco.2021.05.001
19. Bouyé, E., Durrleman, V., Nikeghbali, A., et al. (2000). Copulas for Finance - A Reading Guide and Some Applications. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1032533
20. Brander, J., & Krugman, P. (1983). A ‘reciprocal dumping’model of international trade. Journal of international economics, 15(3–4), 313–321.
21. Carollo, S. (2011). Understanding oil prices: A guide to what drives the price of oil in today’s markets. John Wiley & Sons.
22. Chen, S.-S., & Chen, H.-C. (2007). Oil prices and real exchange rates. Energy Economics, 29(3), 390–404. https://doi.org/10.1016/j.eneco.2006.08.003
23. Coles, S., Heffernan, J., & Tawn, J. (1999). Dependence measures for extreme value analyses. Extremes, 2, 339–365.
24. Conover, C. M., Jensen, G. R., Johnson, R. R., et al. (2010). Is Now the Time to Add Commodities to Your Portfolio? The Journal of Investing, 19(3), 10–19. https://doi.org/10.3905/joi.2010.19.3.010
25. Cuñado, J., & de Gracia, F. P. (2003). Do oil price shocks matter? Evidence for some European countries. Energy economics, 25(2), 137–154.
26. Cunado, J., & Perez de Gracia, F. (2005). Oil prices, economic activity and inflation: evidence for some Asian countries. The Quarterly Review of Economics and Finance, 45(1), 65–83. https://doi.org/10.1016/j.qref.2004.02.003
27. Cunado, J., & Perez de Gracia, F. (2014). Oil price shocks and stock market returns: Evidence for some European countries. Energy Economics, 42, 365–377. https://doi.org/10.1016/j.eneco.2013.10.017
28. Czado, C., Schepsmeier, U., & Min, A. (2012). Maximum likelihood estimation of mixed C-vines with application to exchange rates. Statistical Modelling, 12(3), 229–255. https://doi.org/10.1177/1471082x1101200302
29. Ding, Z., Granger, C. W., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of empirical finance, 1(1), 83–106.
30. Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987. https://doi.org/10.2307/1912773
31. Fischer, M. J., & Dörflinger, M. (2006). A note on a non-parametric tail dependence estimator (No. 76/2006). Diskussionspapier.
32. Fratzscher, M., Schneider, D., & Van Robays, I. (2014). Oil Prices, Exchange Rates and Asset Prices. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2442276
33. Frunza, M. C. (2015). Introduction to the theories and varieties of modern crime in financial markets. Academic Press.
34. Genest, C., & Mackay, J. (1986). The Joy of Copulas: Bivariate Distributions with Uniform Marginals. The American Statistician, 40(4), 280–283. https://doi.org/10.1080/00031305.1986.10475414
35. Genest, C., & Rivest, L.-P. (1993). Statistical Inference Procedures for Bivariate Archimedean Copulas. Journal of the American Statistical Association, 88(423), 1034–1043. https://doi.org/10.1080/01621459.1993.10476372
36. Genest, C., Quessy, J. F., & Rémillard, B. (2006). Goodness‐of‐fit procedures for copula models based on the probability integral transformation. Scandinavian Journal of Statistics, 33(2), 337–366. Portico. https://doi.org/10.1111/j.1467-9469.2006.00470.x
37. Ghorbel, A., Hamma, W., & Jarboui, A. (2017). Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies. Journal of Applied Statistics, 44(9), 1509–1542. https://doi.org/10.1080/02664763.2016.1155107
38. Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779–1801. Portico. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
39. Golub, S. S. (1983). Oil Prices and Exchange Rates. The Economic Journal, 93(371), 576. https://doi.org/10.2307/2232396
40. Gumbel, E. J. (1958). Statistics of extremes. Columbia University Press.
41. Herrera, A. M., Karaki, M. B., & Rangaraju, S. K. (2017). Where do jobs go when oil prices drop? Energy Economics, 64, 469–482. https://doi.org/10.1016/j.eneco.2016.02.006
42. Hollander, M., Wolfe, D. A., & Chicken, E. (2013). Nonparametric statistical methods. John Wiley & Sons.
43. Hussain, M., Bashir, U., & Rehman, R. U. (2023). Exchange Rate and Stock Prices Volatility Connectedness and Spillover during Pandemic Induced-Crises: Evidence from BRICS Countries. Asia-Pacific Financial Markets, 31(1), 183–203. https://doi.org/10.1007/s10690-023-09411-0
44. Ielpo, F., Merhy, C., & Simon, G. (2017). Engineering investment process: making value creation repeatable. Elsevier.
45. Isah, K. O., & Ekeocha, P. (2023). Modelling exchange rate volatility in turbulent periods: The role of oil prices in Nigeria. Scientific African, 19, e01520. https://doi.org/10.1016/j.sciaf.2022.e01520
46. Jain, A., Biswal, P. C., & Ghosh, S. (2016). Volatility–volume causality across single stock spot–futures markets in India. Applied Economics, 48(34), 3228–3243. https://doi.org/10.1080/00036846.2015.1136401
47. Jiang, Y., Feng, Q., Mo, B., et al. (2020). Visiting the effects of oil price shocks on exchange rates: Quantile-on-quantile and causality-in-quantiles approaches. The North American Journal of Economics and Finance, 52, 101161. https://doi.org/10.1016/j.najef.2020.101161
48. Joe, H. (1997). Multivariate models and multivariate dependence concepts. CRC Press.
49. Karaki, M. B. (2017). Nonlinearities in the response of real GDP to oil price shocks. Economics Letters, 161, 146-148.
50. Karmous, A., Boubaker, H., & Belkacem, L. (2021). Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas. Computational Economics, 58(2), 461-482.
51. Krugman, P. (1983). Oil shocks and exchange rate dynamics. In Exchange rates and international macroeconomics (pp. 259-284). University of Chicago Press.
52. Kruskal, W. H. (1958). Ordinal measures of association. Journal of the American Statistical Association, 53(284), 814-861..
53. Kyophilavong, P., Abakah, E. J. A., & Tiwari, A. K. (2023). Cross-spectral coherence and co-movement between WTI oil price and exchange rate of Thai Baht. Resources Policy, 80, 103160. https://doi.org/10.1016/j.resourpol.2022.103160
54. Lehmann, E. L., & D’Abrera, H. J. (1975). Nonparametrics: Statistical methods based on ranks. Holden-day.
55. Lei, L., Aziz, G., Sarwar, S., Waheed, R., & Tiwari, A. K. (2023). Spillover and portfolio analysis for oil and stock market: A new insight across financial crisis, COVID-19 and Russian-Ukraine war. Resources Policy, 85, 103645. https://doi.org/10.1016/j.resourpol.2023.103645
56. Liu, C., Naeem, M. A., Rehman, M. U., et al. (2020). Oil as Hedge, Safe-Haven, and Diversifier for Conventional Currencies. Energies, 13(17), 4354. https://doi.org/10.3390/en13174354
57. Ma, R. R., Xiong, T., & Bao, Y. (2021). The Russia-Saudi Arabia oil price war during the COVID-19 pandemic. Energy Economics, 102, 105517. https://doi.org/10.1016/j.eneco.2021.105517
58. Malik, F., & Ewing, B. T. (2009). Volatility transmission between oil prices and equity sector returns. International Review of Financial Analysis, 18(3), 95–100. https://doi.org/10.1016/j.irfa.2009.03.003
59. Malik, F., & Umar, Z. (2019). Dynamic connectedness of oil price shocks and exchange rates. Energy Economics, 84, 104501. https://doi.org/10.1016/j.eneco.2019.104501
60. Martínez Raya, A., Segura de la Cal, A., & Rodríguez Oromendía, A. (2023). Financialization of Real Estate Assets: A Comprehensive Approach to Investment Portfolios through a Gender-Based Study. Buildings, 13(10), 2487. https://doi.org/10.3390/buildings13102487
61. Mensi, W., Hammoudeh, S., Shahzad, S. J. H., et al. (2017). Oil and foreign exchange market tail dependence and risk spillovers for MENA, emerging and developed countries: VMD decomposition based copulas. Energy Economics, 67, 476–495. https://doi.org/10.1016/j.eneco.2017.08.036
62. Mikhaylov, A., Bhatti, I. M., Dinçer, H., et al. (2024). Integrated decision recommendation system using iteration-enhanced collaborative filtering, golden cut bipolar for analyzing the risk-based oil market spillovers. Computational Economics, 63(1), 305–338. https://doi.org/10.1007/s10614-022-10341-8
63. Nandelenga, M. W., & Simpasa, A. M. (2020). Oil price and exchange rate dependence in selected countries. African Development Bank.
64. Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347. https://doi.org/10.2307/2938260
65. Nusair, S. A., & Olson, D. (2019). The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis. Energy Economics, 78, 44–63. https://doi.org/10.1016/j.eneco.2018.11.009
66. Opoku, R. T., Adam, A. M., Isshaq, Z. M., et al. (2023). Time-varying connectedness and contagion between commodity prices and exchange rate in Sub-Saharan Africa. Cogent Economics & Finance, 11(2). https://doi.org/10.1080/23322039.2023.2237714
67. Reboredo, J. C. (2012). Modelling oil price and exchange rate co-movements. Journal of Policy Modeling, 34(3), 419–440. https://doi.org/10.1016/j.jpolmod.2011.10.005
68. Reboredo, J. C., & Rivera-Castro, M. A. (2013). A wavelet decomposition approach to crude oil price and exchange rate dependence. Economic Modelling, 32, 42–57. https://doi.org/10.1016/j.econmod.2012.12.028
69. Regnier, E. (2007). Oil and energy price volatility. Energy Economics, 29(3), 405–427. https://doi.org/10.1016/j.eneco.2005.11.003
70. Salisu, A. A., Olaniran, A., & Tchankam, J. P. (2022). Oil tail risk and the tail risk of the US Dollar exchange rates. Energy Economics, 109, 105960. https://doi.org/10.1016/j.eneco.2022.105960
71. Sebai, S., & Naoui, K. (2015). A study of the interactive relationship between oil price and exchange rate: A copula approach and a DCC-MGARCH model. The Journal of Economic Asymmetries, 12(2), 173–189. https://doi.org/10.1016/j.jeca.2015.09.002
72. Shang, J., & Hamori, S. (2023). Differential Tail Dependence between Crude Oil and Forex Markets in Oil-Importing and Oil-Exporting Countries during Recent Crisis Periods. Sustainability, 15(19), 14445. https://doi.org/10.3390/su151914445
73. Shih, J. H., & Louis, T. A. (1995). Inferences on the Association Parameter in Copula Models for Bivariate Survival Data. Biometrics, 51(4), 1384. https://doi.org/10.2307/2533269
74. Sklar, M. (1959). N-dimensional distribution functions and their margins (French). Annales de l’ISUP, 8(3), 229–231.
75. Sokhanvar, A., & Bouri, E. (2023). Commodity price shocks related to the war in Ukraine and exchange rates of commodity exporters and importers. Borsa Istanbul Review, 23(1), 44–54. https://doi.org/10.1016/j.bir.2022.09.001
76. Su, C.-W., Qin, M., Tao, R., et al. (2020). Factors driving oil price—from the perspective of United States. Energy, 197, 117219. https://doi.org/10.1016/j.energy.2020.117219
77. Synthetic Complex Data Generation Using. (2021). In: Proceedings of the 23rd International Workshop on Design, Optimization, Languages.
78. Tiwari, A. K., Shahbaz, M., Khalfaoui, R., et al. (2022). Directional predictability from energy markets to exchange rates and stock markets in the emerging market countries (E7 + 1): New evidence from cross‐quantilogram approach. International Journal of Finance & Economics, 29(1), 719–789. Portico. https://doi.org/10.1002/ijfe.2706
79. Umar, Z., Aziz, M. I. A., Zaremba, A., et al. (2023). Modelling dynamic connectedness between oil price shocks and exchange rates in ASEAN+3 economies. Applied Economics, 55(23), 2676–2693. https://doi.org/10.1080/00036846.2022.2104801
80. Wang, X., Wu, X., & Zhou, Y. (2022). Conditional Dynamic Dependence and Risk Spillover between Crude Oil Prices and Foreign Exchange Rates: New Evidence from a Dynamic Factor Copula Model. Energies, 15(14), 5220. https://doi.org/10.3390/en15145220
81. Zaremba, A., Umar, Z., & Mikutowski, M. (2021). Commodity financialisation and price co-movement: Lessons from two centuries of evidence. Finance Research Letters, 38, 101492. https://doi.org/10.1016/j.frl.2020.101492
82. Zeng, H., Ahmed, A. D., Lu, R., et al. (2022). Dependence and spillover among oil market, China’s stock market and exchange rate: new evidence from the Vine-Copula-CoVaR and VAR-BEKK-GARCH frameworks. Heliyon, 8(11), e11737. https://doi.org/10.1016/j.heliyon.2022.e11737
83. Zorgati, M. B. S. (2023). Risk Measure between Exchange Rate and Oil Price during Crises: Evidence from Oil-Importing and Oil-Exporting Countries. Journal of Risk and Financial Management, 16(4), 250. https://doi.org/10.3390/jrfm16040250