JOURNAL ARTICLE
Inventory as a Financial Instrument: Evidence from China's Metal Industries.
Published In: Management Science (INFORMS), 2024, v. 70, n. 6. P. 3645 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Hsu, Vernon; Wu, Jing 3 of 3
Abstract
This article investigates how inventory can serve as a financial instrument to exploit arbitrage opportunities in financial markets with restricted capital mobility, focusing on China’s metal processing industries. Using country-level data on imported metals (copper, aluminum, zinc) and firm-level data from publicly listed Chinese manufacturing firms, the study finds that higher interest rate spreads between domestic (Chinese yuan) and overseas (U.S. dollar) markets are positively associated with increased inventory levels and short-term borrowing. Firms with greater borrowing capacity—measured by liquidation value, size, and sales growth—are more likely to use inventory for quasi-arbitrage financial gains. A regulatory crackdown on disguised trade financing in 2013 serves as a quasi-natural experiment, showing that firms reliant on inventory-based arbitrage reduced their inventory levels significantly after the policy change. The findings extend classic inventory theory by identifying financial arbitrage motives as a significant driver of inventory decisions in environments with capital controls, with implications for supply chain stability and regulatory policy in emerging economies.
Additional Information
- Source:Management Science (INFORMS). 2024/06, Vol. 70, Issue 6, p3645
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:0025-1909
- DOI:10.1287/mnsc.2023.4873
- Accession Number:177878309
- Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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