A computational approach to pricing a bank credit line

Stanhouse, Bryan; Schwarzkopf, Al; Ingram, Matt

doi:10.1016/j.jbankfin.2010.10.002

Cited by 10 publications

(6 citation statements)

References 24 publications

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“…Also, since the interest rate on most credit lines is based on a fixed markup over a benchmark such as the prime rate or the London interbank offered rate (Libor), although the cost of credit-line borrowing varies with changes in the benchmark, the fixed markup protects the borrower from rate increases in the spot market caused by widening of market-wide credit spreads (Stanhouse et al, 2010;Plaut, 1986, 1987). Thus, models that are based on an assumption that lines of credit provide insurance against fluctuations in the level of interest rates are likely to have limited applicability in explaining the use of most lines of credit.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

The use of bank lines of credit in corporate liquidity management: A review of empirical evidence

Demiroglu

James

2011

Journal of Banking & Finance

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Section: Theoretical Backgroundmentioning

confidence: 99%

The use of bank lines of credit in corporate liquidity management: A review of empirical evidence

Demiroglu

James

2011

Journal of Banking & Finance

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“…According to the characteristics of the domestic financial market and bank credit risk management, Cheng Gong and Zhang Wei (2008) [22] built a structured model of noise,and on this basis, they put forward a new method to calculate the customer's risk limit. Zhou Minghao and Wang Xiaoying (2010) [23] introduced some problems existing in the current credit quota calculation, and put forward the methods to improve the credit loan amount.Assuming that the financial needs of customers at different times are subject to the Brown movement, Stanhouse, Schwarzkopf & Ingram (2011) [24] set up the credit line determination model of commercial banks from the perspective of the customer's financial needs. On the basis of flexible financial management theory, Miao Xilin (2014) [25] adjusted the basis for the design of short-term loan amount calculation method by giving full play to people's subjective initiative and taking credit risk as a target.…”

Section: (4) the Methods For Determining Loan Limitation Of Commercialmentioning

confidence: 99%

Review of the Management Theory and Method of Loan Limitation

Zhang¹,

Wang²

2018

Proceedings of the 2nd International Forum on Management, Education and Information Technology Application (IFMEITA 2017)

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Abstract. Reasonably determining and using the loan limitation granted by commercial banks to their corporate clients, it has important theory meaning and realistic meaning for commercial banks to strengthen risk prevention and for lenders and borrowers to improve operational performance. In this paper, we summarized the domestic and foreign research status of the loan limitation of commercial banks from three aspects, such as the influencing factors of the loan limitation of commercial banks, the determining method of the loan limitation of commercial banks, and the utilization efficiency of the loan limitation of commercial banks and so on. The aim of our study is to promote the application and development of the loan limitation management theory and method.

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“…Ariccia and Marquez [26] provide a formal framework to study bank credit allocation under asymmetric information. Stanhouse et al [27] build a model to determine credit lines from the perspective of clients' demand information under the assumption that the funding need is characterized by trended Brownian motion.…”

Section: Credit Line Modelsmentioning

confidence: 99%

Credit Line Models for Supply Chain Enterprises with Channel Background and Soft Information

Wang

Yang

et al. 2019

Sustainability

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Credit lines have been widely adopted by banks to grant credit to small and medium-sized enterprises (SMEs). However, there often exists a gap between the credit lines granted by banks and the actual funding needs of SMEs. In addition, existing credit line models treat each SME as a stand-alone entity instead of considering it within its supply chain system. But an SME’s supply chain relations have a significant impact on its credit-worthiness. To offer banks a holistic assessment, this paper first constructs a base credit line model for SMEs by considering their supply chain background. Next, by accounting for the unique advantage of soft information processing in a supply chain context, we put forward an extended credit line model for supply chain enterprises with soft information. The base and extended credit line models proposed in this paper aim to reduce information asymmetry between banks and SMEs via the core enterprise in the supply chain, thereby helping banks to secure a sustainable source of profit at a lower risk level and SMEs to obtain more credit to support their sustainable growth. A case study is furnished to illustrate how the proposed models can be applied in practice and an empirical analysis further verifies their validity.

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A computational approach to pricing a bank credit line

Cited by 10 publications

References 24 publications

The use of bank lines of credit in corporate liquidity management: A review of empirical evidence

The use of bank lines of credit in corporate liquidity management: A review of empirical evidence

Review of the Management Theory and Method of Loan Limitation

Credit Line Models for Supply Chain Enterprises with Channel Background and Soft Information

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