Understanding the Baltic Dry Index (BDI): an explainable decomposition approach

被引:0
|
作者
Guan, Linfei [1 ]
Zhao, Ziao [2 ]
Sun, Qinghe [2 ]
机构
[1] Northwestern Polytech Univ, Sch Management, Xian, Peoples R China
[2] Hong Kong Polytech Univ, Fac Business, Dept Logist & Maritime Studies, Kowloon, Hong Kong, Peoples R China
关键词
Shipping finance; maritime freight; seasonality; Prophet forecasting; explainable AI; VOLATILITY; MARKETS; TRENDS; MODEL;
D O I
10.1080/03088839.2024.2448446
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The Baltic Dry Index (BDI) is a crucial indicator of the dry bulk freight market, offering insights into the shipping industry's health and activity levels. In this study, we introduce an explainable decomposition framework to unveil the underlying mechanisms of BDI dynamics. Utilizing historical data from 1 November 1999, to 5 March 2024, we decompose BDI into trends, seasonal fluctuations, and externally derived influences. Our experiments have identified the magnitude of trend changes from major global events over the past two decades. Intriguingly, we find that advancements in industry and technology contribute significantly to upward trends in BDI. We also explore BDI's seasonality, identifying distinct cyclical patterns within a year, including the Christmas and Chinese New Year effects, and more interestingly, a trough in late June due to the receding in shipping demand for the three major bulk. Our findings further offer valuable insights into understanding BDI fluctuations, aiding decision-making processes in the maritime freight market. We find that Natural Gas and the Dollar Index are potent signals for BDI one week to one month ahead, while the NASDAQ 100 Index emerges as a leading indicator for longer forecasting horizons.
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页数:25
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