Tracking oil price shocks and airline stock reactions using entropy-based approaches

Abstract

The relationship between oil prices and the airline industry is economically important yet empirically complex, presenting significant challenges, with prior research yielding conflicting evidence on the nature, strength, and direction of their interaction. This study contributes to the literature moving beyond traditional linear assumptions, applying Shannon and Rényi transfer entropy to evaluate the nonlinear and state-dependent information flow between oil, oil volatility, and six international airline indices. The empirical findings reveal a significant but heterogeneous information flow between West Texas Intermediate (WTI) and airline indices, suggesting a relationship of mutual influence, where the directional information flow from WTI to airline indices consistently surpasses the reverse flow. In the case of the Crude Oil Volatility Index (OVX), results show a dominant flow of information from each airline index to the OVX index, indicating that sector-specific shocks can shape market expectations of oil volatility. The Rényi entropy analysis further uncovers tail-driven dynamics: at low orders of Rényi entropy, the entropy values remained predominantly negative between WTI and airline indices, while they remained predominantly positive, particularly from OVX to airline indices. However, at very high orders of entropy, there is a more traditional flow of information from WTI to airline indices. These findings enable policymakers to develop more effective, targeted, and economically sound energy policies for the transportation sector and the wider economy.