Exploring the Financial Potential of Fuel Hedging on Optimal Flight Networks

Abstract

In recent years, demand for air travel within the United States has been steadily rising. At the same time, the airline industry continues to exhibit low profit margins. Kerosene jet fuel makes up an estimated 30-50% of an airline's operating budget. Jet fuel prices are very volatile, which impacts an airline's ability to predict its future profits and losses and has great impact on an airline's financial state. One proposed method of predicting profit and managing volatility is cross-hedging the price of jet fuel with a highly correlated commodity, such as crude oil. Previous literature has examined the effectiveness of such cross-hedges and developed methods for estimating the ideal levels of hedging based on historical price data. Additionally, airlines frequently use network optimization models to determine the most profitable flight routes to operate. However, no existing literature directly applies optimal hedging practices to flight network planning. This thesis utilizes the Error Correction regression model to estimate the minimum variance hedging ratio for hedging the spot price of jet fuel with commodities futures. We then develop a network optimization model based on past financial and flight data and study the effects of hedging on the networks. We find that, based on results from the first three quarters of 2023, hedging can significantly impact both the size and shape of a flight network, but the optimal network is vulnerable to contraction if the hedge results in a loss.