The asymmetric impact of oil price uncertainty on emerging market financial stress: A quantile regression approach

This study investigates the effects of the crude oil implied volatility index (OVX) upon emerging market financial stress (EMFS). We resort to a quantile regression framework as this approach is a better alternative to disentangle the relationship under different market conditions. Besides, we also examine how EMFS responds to the lags and asymmetries in the OVX. The empirical results show significantly positive impacts of OVX upon EMFS. Further, the effects of OVX become more assertive in the upper quantiles of EMFS, implying higher sensitivity to OVX when stress levels are high. In terms of the lagged effects, the relationship is transient as the OVX coefficients become weaker with increasing lag sizes. We further find that only positive impulses in OVX can significantly predict EMFS. Lastly, we report evidence that the Credit market stress is a crucial driver of EMFS.

Automated summary

This study investigates the effects of the crude oil implied volatility index (OVX) on emerging market financial stress (EMFS) using a quantile regression framework. The results show significant positive impacts of OVX on EMFS, with higher sensitivity to OVX when stress levels are high. The relationship is transient as the lag size increases, and only positive impulses in OVX can significantly predict EMFS. Furthermore, evidence suggests that credit market stress is a crucial driver of EMFS.