Dynamic Optimality of Airline Fuel Cost Hedging
71 Pages Posted: 27 Nov 2019 Last revised: 16 Dec 2019
Date Written: November 16, 2019
Hedging creates value only when the policy is near optimal but can be harmful otherwise. This paper takes the US airline industry as an example and derives the optimal fuel cost hedging ratio as a function of firm-specific revenue and cost sensitivities, as well as the relative composition of demand and supply shocks in the oil price movement. We construct a market hedging demand index based on rolling-window regression of crude futures returns on equity index returns and use the index to capture the time-variation in the fuel cost hedging demand for a typical airline. By regressing the logarithm of Tobin's Q against the hedging ratio under different market conditions, we show that fuel cost hedging increases firm value only when the market hedging demand is high. More important, we use the time-series correlation between an airline's hedging ratio and the market hedging demand to measure the dynamic optimality of the airline's fuel hedging practice. Out of the 33 US airlines in our sample over a 25-year period, one third do not hedge at all, while the hedging ratios for more than another one third move in the opposite direction of the market hedging demand. Only less than one third of airlines show positive dynamic optimality for their hedging practice. The cross-sectional diversity of the optimality estimates highlights the inherent difficulty of implementing an optimal policy. Still, we find strong value in staying dynamically optimal in an airline's fuel cost hedging practice: The dynamic optimality of each airline's hedging practice strongly and positively predicts its valuation as measured by the logarithm of its Tobin's Q. The value increase comes from both reduced variation in its return on asset and increased average return. Airlines with negative hedging dynamic optimality not only are ineffective in reducing their return on asset variation, but also incur extra costs from setting up and maintaining a costly hedging program and from entering and exiting hedging positions. Such extra costs lower the airlines' average return and hurt their valuation. As a result, their average Tobin's Q is even lower than the average for airlines that do not hedge at all.
Keywords: hedging dynamic optimality; crude futures; supply shocks; demand shocks; airline industry; optimal fuel cost hedging
JEL Classification: C13, G32, L93, Q41, Q47
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