Futures markets and the baltic dry index: A prediction study based on deep learning

Miao Su, Yufei Nie, Jiankun Li, Lin Yang and Woohyoung Kim

Research in International Business and Finance, 2024, vol. 71, issue C

Abstract: The Baltic Dry Index (BDI), representing the shipping sector, displays a notable sensitivity to Chinese commodity futures markets. Stakeholders must grasp the relationship between BDI and China’s commodity futures markets. However, there is currently a lack of comprehensive evaluation of Chinese futures’ forecasting performance. Therefore, we collected data on 17 major Chinese commodity futures from April 16, 2015, to December 27, 2022, and used CNN, BiLSTM, and AM to assess China’s futures market’s BDI prediction power. The CNN-BiLSTM-AM ensemble model emerged as the most accurate, R² value of 95.3 %. This study highlights the Chinese futures market’s ability to predict the global shipping index BDI and broadens our understanding of the financial market-maritime industry interplay. By monitoring fluctuations in China’s futures market, shipping companies and regulators can make precise BDI predictions, offering a scientific foundation for policy adjustments and decision-making amidst future BDI shifts.

Keywords: Shipping market; China commodity futures market; Forecasting; Baltic dry index; Deep learning; CNN-BiLSTM-AM (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:71:y:2024:i:c:s027553192400240x

DOI: 10.1016/j.ribaf.2024.102447

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