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Supply chain management based on volatility clustering: The effect of CBDC volatility

Ding, Shusheng; Cui, Tianxiang; Wu, Xiangling; Du, Min


Shusheng Ding

Tianxiang Cui

Xiangling Wu


A Central Bank Digital Currency (CBDC) launched by the Bank of England could enable businesses to directly make electronic payments. It can be argued that digital payment is helpful in supply chain management applications. However, the adoption of CBDC in the supply chain could bring new turbulence since the CBDC value may fluctuate. Therefore, this paper intends to optimize the production plan of manufacturing supply chain based on a volatility clustering model by reducing CBDC value uncertainty. We apply both GARCH model and machine learning model to depict the CBDC volatility clustering. Empirically, we employed Baltic Dry Index, Bitcoin and exchange rate as main variables with sample period from 2015 to 2021 to evaluate the performance of the two models. On this basis, we reveal that our machine learning model overwhelmingly outperforms the GARCH model. Consequently, our result implies that manufacturing companies’ performance can be strengthened through CBDC uncertainty reduction.

Journal Article Type Article
Acceptance Date May 25, 2022
Online Publication Date Jun 6, 2022
Publication Date 2022-12
Deposit Date Jun 15, 2022
Publicly Available Date Jun 15, 2022
Journal Research in International Business and Finance
Print ISSN 0275-5319
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 62
Article Number 101690
Keywords CBDC, Volatility clustering, Machine learning, Digital currency, Supply chain management
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