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

Authors
Su, MiaoNie, YufeiLi, JiankunYang, LinKim, Woohyoung
Issue Date
Aug-2024
Publisher
JAI Press
Keywords
Shipping market; China commodity futures market; Forecasting; Baltic dry index; Deep learning; CNN-BiLSTM-AM
Citation
Research in International Business and Finance, v.71, pp 1 - 20
Pages
20
Indexed
SSCI
SCOPUS
Journal Title
Research in International Business and Finance
Volume
71
Start Page
1
End Page
20
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/209843
DOI
10.1016/j.ribaf.2024.102447
ISSN
0275-5319
1878-3384
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.
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서울 기술경영전문대학원 > 서울 기술경영학과 > 1. Journal Articles

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GRADUATE SCHOOL OF TECHNOLOGY & INNOVATION MANAGEMENT (DEPARTMENT OF TECHNOLOGY MANAGEMENT)
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