Abstract
The Baltic Dry Index (BDI) is a unique gauge for measuring the marine transportation of major dry bulk shipments. Increased sea freight is a precursor to the increase in economic activities. The volumes of sea trade and freight rates are influenced by import–export dynamics and changes in commodity prices. So, levels of commodity prices are monitored to gain insight into the anticipated demand for bulk shipments. In this study, the causality-in-quantiles (CiQ) model is used to model the causal relationship between BDI spot values and spot price of major dry bulk commodities like iron ore, aluminum, copper, agricultural products by considering 12 years of daily data. CiQ model is superior compared to other linear causality models as it helps in capturing the asymmetry and nonlinearity in causality based on different quantiles or market conditions i.e., bearish, normal, and bullish market conditions. Also, it captures the causality-in-mean as well as variance and helps in exploring the causal relationship in returns as well as volatility transmission between BDI and commodity prices. The finding of the paper throws interesting light on the asymmetric relationship between BDI and commodity prices- commodity prices are causing BDI in all market conditions, but the influence is stronger in normal periods than bearish and bullish periods. The causality from commodity to BDI follows a common pattern across most of the commodities. However, the effect of BDI on commodities considerably varies across the range of commodities and across market conditions. So, this model provides a plethora of information that will help commodity market participants to hedge the risk of variations in commodity price and freight rates effectively.
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