关键词: 供应链金融, 质物组合, 长期价格风险, Copula, CVaR

Abstract: In this paper, we select silver, aluminum and copper three germplasm as the research objects. Based on the analysis of the statistical characteristics of the yield of pledge in supply chain finance, the Copula model is introduced to describe the typical characteristics of the “peak and heavy tail” of the yield of pledge and the nonlinear correlation structure between the yield of pledge in supply chain finance. And the Monte Carlo simulation method is used to measure the price risk value CVaR of the pledge portfolio under extreme conditions. At the same time we use the square root rule of time to measure the price risk of pledge portfolio under long term perspective. In order to select the best measure of long-term price risk model of supply chain financial pledge portfolio, we compare the results of CVaR and VaR, compare the short-term price risk and the long-term price risk, and also compare the price risk value measured by the Copula model and the traditional risk measurement method. The results show that: from the volatility of single commodity price, the yield of the three types of pledges has the characteristics of non normal distribution and “peak thick tail”, so it has the characteristics of the return distribution of general financial assets. From the validity of the model, first, CVaR can better and comprehensively measure the price risk of supply chain finance pledge portfolio than VaR. Second, the accuracy of risk measurement based on the Copula model results is better than traditional integrated risk measurement results. Third, the square Euclidean distance method shows that the t-Copula model is the best characterization of the dependent structure of the pledge portfolio in the five Copula models. From the long-term risk measure, with the increase of risk period, pledge portfolio price risk value increases, therefore, the short-term risk measurement in the past research will underestimate the price risk faced by commercial banks, which is not conducive to the optimal allocation of commercial banks' funds and credit. The conclusion provides quantitative support for commercial banks to carry out supply chain financial business to prevent price risk.

Key words: supply chain finance, pledge portfolio, long-term price risk, Copula, CVaR