Forecasting Maritime and Financial Market Trends: Leveraging CNN-LSTM Models for Sustainable Shipping and China’s Financial Market Integration

Zihui Han, Xiangcheng Zhu and Zhenqing Su ()
Additional contact information
Zihui Han: The Graduate School of Global Business, Sejong University, Seoul-si 03773, Republic of Korea
Xiangcheng Zhu: Department of Pedagogy, Bashkir State Pedagogical University n.a. M. Akmulla, Ufa 450008, Russia
Zhenqing Su: The Graduate School of Global Business, Kyonggi University, Suwon-si 16227, Republic of Korea

Sustainability, 2024, vol. 16, issue 22, 1-24

Abstract: With the acceleration of economic globalization, China’s financial market has emerged as a vital force in the global financial system. The Baltic Dry Index (BDI) and China Container Freight Index (CCFI) serve as key indicators of the shipping sector’s health, reflecting their sensitivity to shifts in China’s financial landscape. This study utilizes an innovative CNN-LSTM deep learning model to forecast the BDI and CCFI, using 25,974 daily data points from the Chinese financial market between 5 May 2015 and 30 November 2022. The model achieves high predictive accuracy across diverse samples, frequencies, and structural variations, with an R 2 of 97.2%, showcasing its robustness. Beyond its predictive strength, this research underscores the critical role of China’s financial market in advancing sustainable practices within the global shipping industry. By merging advanced analytics with sustainable shipping strategies, the findings offer stakeholders valuable tools for optimizing operations and investments, reducing emissions, and promoting long-term environmental sustainability in both sectors. Additionally, this study enhances the resilience and stability of financial and shipping ecosystems, laying the groundwork for an eco-friendly, efficient, and sustainable global logistics network in the digital era.

Keywords: China’s financial market; Baltic Dry Index (BDI); China Container Freight Index (CCFI); CNN-LSTM model; deep learning; sustainable shipping (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/22/9853/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/22/9853/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:22:p:9853-:d:1519157

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().