Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper examines the volatility transmission from the oil market to Islamic banks' (IBs) share prices in two sets of data from oil exporters and importers. Our datasets comprise indices developed from banks' stocks of eight oil-exporting countries, including 41 IBs and 90 conventional banks (CBs), and five oil-importing countries, with 23 IBs and 63 CBs. We employ a trivariate version of the non-diagonal GARCH model, which allows for asymmetry in the variance-covariance matrix. Rather than relying on a single window, we perform the estimations through many recursive windows. The results reveal that oil volatility has higher predictive power (in majority recursive significant subsamples) in the exporter dataset compared to the importer dataset. We also find higher significant recursive subsamples for conventional counterparts in the same country. Holistically, IBs show greater bank stability during high oil price volatility horizons, a finding beneficial for policymakers, regulators, financial markets, IBs, and other concerned stakeholders.