This research investigates the risk spillover effects of crude oil prices on stock price indices in both oil-producing and consumer countries during the period 2000–2022. The research employs the GARCH Copula Quantile Regression (CQR) model, a method capable of capturing nonlinear dependencies and tail risks between crude oil prices and stock indices across different risk levels. The data includes daily crude oil prices (WTI) and stock indices of oil-producing countries (S&P500, TASI, MOEX, TSX) and consumer countries (SSE, BSE SENSEX, Nikkei 225). The findings reveal significant downside and upside risk spillovers from crude oil prices to stock indices, with oil-producing countries experiencing higher spillover risks compared to consumer countries. Notably, the TASI index exhibits the greatest risk spillover among producing countries, while the SSE index is most affected among consumer countries. These results highlight the asymmetrical nature of risk spillovers, with downside risks posing greater challenges than upside risks. This research contributes to the existing literature by providing a more detailed analysis of risk dependencies using the GARCH CQR model and offering practical insights for investors and policymakers to better manage risks in volatile markets. The study underscores the importance of understanding tail dependencies in financial markets affected by crude oil price fluctuations.
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