A Quantitative Study Of Loan-to-Value Ratios On GOODS PLEDGE

At present, small and medium-sized enterprises (SMEs) have become the "booster" of China’s fast growing economy. However, it is difficult for them to get traditional loans from the bank for lack of credit rating, guarantors and real estate. Now, more and more banks launch "Supply Chain Finance" (SCM) service providing support for SMEs in credit enhancement, procurement and capital turnover. For loan banks, risk control at the core of loan, where loan-to-value ratios (LTVs) become the core risk control indicators in SCM because of relative freedom setting. The essence of setting LTVs is to weigh the benefits and risks that can effectively control the loan risk in guarantee business. Meanwhile, the setting of LTVs and the characteristics of business model, guarantee inventory, default probability and loan interest rates are closely related, which can fully reflect the status of the risk of SCM. Therefore, this research makes quantitative research on LTVs from the features of the inventory. The main research contents are as follows:For seasonal goods, this paper considers the random fluctuation of market demand and endogenous default based on advance payment financing. Firstly, this paper focuses on the distributor optimal order quantity decision-making under default risk. On that basis, the method of downside-risk and Stackelberg dynamic game theory is used to investigate the decisions of LTVs under different risk preference. According to a numerical simulation, we find that LTVs is associated closely with order quantity, loan interest rate and financing maturity.For goods with stochastic fluctuations prices, LTVs decision is mainly affected by bank monitoring. The prevention of their price risk is particularly important. This paper gives the round steel LTVs research as example, using time series method to analyze the fluctuation characteristics and forecasting the long-term ES during the different finance maturity in the impawn period. By backing testing our model and ES, we find that ES is better to portray the market risk compare with VaR, and the cordon and open line setting can significantly improve the risk coverage of banks.On the combination of theoretical research and empirical research method as well as qualitative study and quantitative study, this paper gets the LTVs according with the risk exposure of banks, which put forward a dynamic impawn rate mode and framework for banks.