We examine the presence of connectedness between shipping freights, agricultural and energy commodities across extreme quantile return distribution. Data for our analysis ranges from November 13, 2012, to November 9, 2022 on daily frequency. Our spillover results highlight that freight indices transmit changes during the normal and bullish periods whereas the energy market transmits changes during bearish market conditions. We also use the network connectedness approach to measure connectedness which suggests the sensitivity of the shipping industry to other commodity markets. Our results carry important implications for investors, policymakers and traders in understanding the linkages between the shipping industry, energy and agriculture commodities.
Kang et al. (2026) studied this question.