Journal of Credit Risk
ISSN:
1755-9723 (online)
Editor-in-chief: Linda Allen and Jens Hilscher
Enhancing small and medium-sized enterprise factoring: a Stackelberg game-based hybrid pricing model
Need to know
- Sellers face credit risk due to delayed payments; factoring helps transfer this risk but is usually offered on a whole turnover basis, while SMEs prefer single debt financing, leading to adverse selection.
- A hybrid linear pricing model is developed using a min-max approach with a Lévy-frailty multivariate default model, incorporating static and dynamic components.
- A two-player Stackelberg game is analyzed, and a supplier’s portfolio optimization problem is solved via an SGD algorithm, yielding an upper bound for the price.
- The price interval is determined by combining the upper bound with a cost-covering condition, and a data-rich approach is used to model the dynamic part.
Abstract
In supply chain management and trade credit, buyers of goods or services are often granted a delayed payment goal, and the sellers of the respective goods or services are thus exposed to credit risk. Factoring is a financing decision by which sellers can eliminate this risk from their balance sheet. This service is typically offered on a whole turnover basis; however, most small and medium-sized enterprises prefer financing on a single debt level, and hence adverse selection emerges as an additional source of risk. By employing a game-theoretical min–max approach including a Lévy-frailty ansatz for the multivariate default model, we develop a hybrid linear pricing model for the factor, consisting of a static component and a dynamic component. As part of the derivation, we analyze a two-player Stackelberg game and develop a portfolio optimization problem for the supplier, based on a stochastic gradient descent algorithm, which results in an upper bound for the price. Combining this with a cost-covering condition based on the factor provides the proposed price interval. Finally, we embed into the model the simplest data-rich modeling approach for the dynamic part of our analysis.
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