Impawn rate optimisation in inventory financing: A canonical vine copula-based approach

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.