Composite cross hedging for truckload spot freight rates using commodity futures

Abstract

This study proposes a generalized multi-instrument composite cross hedging framework designed to minimize the volatility of spot assets without a direct hedging instrument. Extending traditional two-instrument minimum-variance composite cross hedging models, the proposed method constructs optimal hedging portfolios of any size. To evaluate the performance of the proposed model, it is applied to minimize the volatility of three types of truckload freight rates. In addition, six hedging models with both homoskedastic and heteroskedastic assumptions are also evaluated. By comparing static and dynamic cross hedging models, results show that the Dynamic Conditional Correlation (DCC) GARCH model achieves superior hedging effectiveness by adapting dynamic hedge ratios over time. Further diversification of the hedging portfolio with more instruments does not necessarily yield improved hedging performance. Our findings demonstrate that composite cross hedging improves overall hedging efficiency and outperforms all single-instrument models, especially in downward-trending markets for spot freight rates. NYH ULSD diesel futures consistently demonstrate positive additive and substitution effects on hedging effectiveness due to their correlation with fuel surcharges in spot freight rates. Lastly, the study indicates that hedging effectiveness and optimal portfolio size are not equivalent under upward-trending and downward-trending market conditions, with better results observed in declining spot freight rate environments. This research offers novel insights into identifying optimal size and suitable hedging instruments for constructing effective composite cross hedging portfolios for spot assets under different market conditions.