This study investigates the nonlinear dependence between the daily logarithmic returns of global WTI crude oil prices and exchange rates in three major Asian oil-importing economies-China (CNY/USD), India (INR/USD), and Japan (JPY/USD) -over the period 2000–2024. A two-stage GARCHCopula framework is employed, in which the marginal distributions are modeled using a GARCH(1,1) model with a skewed Student's t distribution, followed by the estimation of Gaussian, Student's t, Frank, Plackett, Clayton, and Gumbel copulas to characterize the dependence structure. Results indicate that the oil price–exchange rate relationship is nonlinear in all three countries, although its strength and pattern differ substantially across economies.The Gumbel copula provides the best fit for India, indicating asymmetric dependence with pronounced upper-tail dependence, whereas the Student's t copula is selected for both Japan and China, revealing symmetric tail dependence.

However, the dependence in China is considerably weaker than that observed in India and Japan, suggesting a more limited transmission of oil price shocks to its foreign exchange market. Overall, the findings demonstrate that the transmission of oil price shocks is heterogeneous across the three economies, with the observed differences being broadly consistent with country-specific structural characteristics, including energy import dependence and exchange rate regimes.From a policy perspective, the results suggest that India should strengthen oil price risk hedging and exchange rate risk management, while Japan and China should continue to monitor tail risks and maintaining exchange rate stability during periods of market stress. These findings Highlight nonlinear and tail dependence in oil–exchange rate dynamics.