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.
引用
收藏
页数:25
相关论文
共 24 条
  • [21] Productivity and growth decomposition: a novel single-index smooth-coefficient stochastic frontier approach
    Sun, Kai
    Kumbhakar, Subal C.
    Lien, Gudbrand
    EUROPEAN REVIEW OF AGRICULTURAL ECONOMICS, 2024,
  • [22] Evaluation of severity changes of compound dry and hot events in China based on a multivariate multi-index approach
    Wu, Xinying
    Hao, Zengchao
    Zhang, Xuan
    Li, Chong
    Hao, Fanghua
    JOURNAL OF HYDROLOGY, 2020, 583 (583)
  • [23] Predicting dust pollution from dry bulk ports in coastal cities: A hybrid approach based on data decomposition and deep learning
    Wang, Wenyuan
    Liu, Bochi
    Tian, Qi
    Xu, Xinglu
    Peng, Yun
    Peng, Shitao
    ENVIRONMENTAL POLLUTION, 2024, 350
  • [24] Dynamic dependence between sectoral indexes of BRIC countries and the baltic dirty tanker index: An investigation using the generalized R2 approach
    Tok, Serife Akinci
    Tarkun, Savas
    BORSA ISTANBUL REVIEW, 2025, 25 (02) : 265 - 274