Abstract In the inventory financing business, an optimal impawn rate (loan-to-value ratio) can help the inventory financing providers (IFPs, she) maintain competitiveness in the inventory financing market. However, the literature has been silent on how IFPs can optimise the business through the optimisation of the impawn rate. This study examines the role of the optimal impawn rate in the inventory financing business. The key to setting the optimal impawn rate is first evaluating default probability and then incorporating this into the profit function. We use a data-driven approach to explore the copula model in setting the optimal impawn rate. Through numerical analysis, we find that the Clayton canonical vine copula has a better performance for the prediction of default probability than the multivariate normal distribution (MVN) and can thus be used to evaluate default probability. In addition, we uncover that setting multiple impawn rates for different collaterals allows inventory financing to yield a higher profit. Further, although the interest rate, industrial impawn rate, and optimal impawn rate have strong effects on inventory financing profit, interestingly, the relationship between them is marginally diminishing.

中文翻译：

---

库存融资中的质押率优化：基于规范藤蔓 copula 的方法

摘要 在库存融资业务中，最优的质押率（loan-to-value ratio）可以帮助库存融资提供者（IFPs，she）在库存融资市场中保持竞争力。然而，文献一直没有提及 IFP 如何通过优化抵押率来优化业务。本研究考察了最佳质押率在库存融资业务中的作用。设置最优抵押率的关键是首先评估违约概率，然后将其纳入利润函数。我们使用数据驱动的方法来探索 copula 模型来设置最佳抵押率。通过数值分析，我们发现 Clayton canonical vine copula 在预测违约概率方面比多元正态分布 (MVN) 具有更好的性能，因此可用于评估违约概率。此外，我们发现为不同的抵押品设置多个质押率可以使库存融资产生更高的利润。此外，虽然利率、产业质押率和最优质押率对存货融资利润的影响很大，但有趣的是，它们之间的关系是边际递减的。