本文選題：供應鏈融資 + 應收賬款融資�。� 參考：《安徽工業(yè)大學》2017年碩士論文

【摘要】：供應鏈金融是以解決中小企業(yè)融資難為目標的創(chuàng)新性金融產(chǎn)品,有效緩解了中小企業(yè)融資難融資貴。供應鏈金融的核心內(nèi)容供應鏈融資發(fā)展非常迅速,供應鏈融資主要包括應收賬款融資、融通倉融資和保兌倉融資三種模式。時常發(fā)生的供應鏈融資騙貸事件不僅造成難以估量的經(jīng)濟損失和社會影響,也給供應鏈融資業(yè)務帶來巨大的負面效應,同時在供應鏈融資的發(fā)展過程中存在實踐應用領先于理論研究的情形,供應鏈融資風險研究較為薄弱。因此,本文以供應鏈應收賬款融資為研究對象,主要從風險評價指標體系建立、評價指標權(quán)重衡量以及評價模型推廣應用三個方面進行研究。具體內(nèi)容如下:(1)建立供應鏈應收賬款融資風險指標體系。通過廣泛閱讀相關(guān)文獻和咨詢行業(yè)專家初步得到5個一級指標,11個二級指標,42個具體指標的指標體系;基于Wind中國企業(yè)庫和咨詢企業(yè)管理人員收集51條供應鏈應收賬款融資數(shù)據(jù);利用stata軟件對51條樣本數(shù)據(jù)進行相關(guān)性分析和敏感性分析分別刪除9個和7個具體指標,最終得到5個一級指標和26個具體指標的指標體系。(2)確定供應鏈應收賬款融資風險指標的組合權(quán)重。為保證指標權(quán)重的優(yōu)越性,本文采用主客觀組合賦權(quán)法確定融資風險指標權(quán)重。主觀賦權(quán)法收集七位行業(yè)專家的指標權(quán)重打分,利用yaahp軟件計算專家的AHP權(quán)重,matlab計算FAHP權(quán)重,對比結(jié)果認為FAHP的計算結(jié)果優(yōu)于AHP;客觀賦權(quán)法介紹熵權(quán)法及部分改進的熵權(quán)法,通過文獻分析認為本文的數(shù)據(jù)預處理方法和計算較多指標權(quán)重能夠克服熵值微小差異造成權(quán)重成倍波動這一問題,利用熵權(quán)法可得到較為理想的指標客觀權(quán)重;主客觀賦權(quán)法組合比重的確定是以風險評價值最小和最大熵原理為目標建立的比重計算模型,利用FAHP和熵權(quán)法的權(quán)重計算結(jié)果求出兩種賦權(quán)法的比重并最終求得組合權(quán)重,實例驗證組合權(quán)重優(yōu)于賦權(quán)法單獨使用;最后利用組合權(quán)重加權(quán)相乘得到51個樣本的風險值。(3)建立基于BP訓練權(quán)重和閾值的風險評估模型。為提高本文組合權(quán)重評估模型的便捷性,建立基于BP訓練權(quán)重和閾值的風險評估模型實現(xiàn)優(yōu)勢互補。采用實驗的方法確定BP訓練模型的網(wǎng)絡層次、輸入層和輸出層節(jié)點數(shù)、各層傳遞函數(shù)、訓練函數(shù)、隱含層節(jié)點數(shù)、學習速率等,建立基于BP訓練權(quán)重和閾值的正向計算評估模型,以組合權(quán)重風險評價值為期望輸出對評估模型進行檢驗,檢驗結(jié)果表明BP評價模型完全能夠達到供應鏈應收賬款融資風險評定的誤差要求,可在今后評價中小企業(yè)應收賬款融資的過程中推廣應用。本文所構(gòu)建的供應鏈應收賬款BP風險評價模型能夠較好地衡量供應鏈應收賬款融資行為的風險水平,為金融機構(gòu)開展此項業(yè)務提供一定的參考依據(jù)。
[Abstract]:Supply chain finance is an innovative financial product aimed at solving the financing difficulties of SMEs, which effectively alleviates the difficulty in financing SMEs. The core content of supply chain finance is the rapid development of supply chain financing. Supply chain financing mainly includes accounts receivable financing, finance warehouse financing and confirmed warehouse financing. The frequent supply chain financing fraud not only causes incalculable economic loss and social impact, but also brings huge negative effects to the supply chain financing business. At the same time, in the process of the development of supply chain financing, the practical application is ahead of the theoretical research, and the research of supply chain financing risk is relatively weak. Therefore, this paper takes the supply chain accounts receivable financing as the research object, mainly from the risk evaluation index system establishment, the evaluation index weight measurement and the evaluation model promotion application three aspects carries on the research. The concrete contents are as follows: 1) establishing the index system of supply chain accounts receivable financing risk. Through extensive reading of relevant literature and consulting industry experts get 5 primary indicators, 11 secondary indicators, 42 specific indicators of the index system; Based on the Wind Chinese enterprise bank and consulting enterprise managers collect 51 supply chain accounts receivable financing data, using stata software to carry out correlation analysis and sensitivity analysis of 51 sample data to delete 9 and 7 specific indicators, respectively. Finally, the index system of 5 primary indexes and 26 specific indexes is obtained) to determine the combined weight of supply chain accounts receivable financing risk index. In order to ensure the superiority of index weight, this paper adopts subjective and objective combination weighting method to determine the index weight of financing risk. The subjective weighting method collects the index weights of seven industry experts and calculates the AHP weights of the experts by using yaahp software. The comparison results show that the calculation results of FAHP are superior to those of AHP, and the objective weighting method introduces the entropy weight method and the partially improved entropy weight method. Through the literature analysis, it is concluded that the method of data preprocessing and the calculation of the weight of more indexes can overcome the problem of multiplying the weight caused by the slight difference in entropy value, and the objective weight of the index can be obtained by using the entropy weight method. The determination of combined weight of subjective and objective weighting method is based on the principle of minimum and maximum entropy of risk evaluation. By using the weight calculation results of FAHP and entropy weight method, the weight of two weighting methods is obtained and the combined weight is finally obtained. Finally, a risk assessment model based on BP training weight and threshold is established by multiplying the combined weights to get the risk value of 51 samples. In order to improve the convenience of the combined weight evaluation model, a risk assessment model based on BP training weight and threshold is established to achieve complementary advantages. The network layer, input layer and output layer node number, transfer function, training function, hidden layer node number, learning rate of BP training model are determined by experimental method. A forward calculation evaluation model based on BP training weight and threshold is established, and the risk evaluation value of combined weight is used as the expected output to test the evaluation model. The test results show that the BP evaluation model can completely meet the error requirements of the risk assessment of the supply chain accounts receivable financing, and can be widely used in the process of evaluating the accounts receivable financing of small and medium-sized enterprises in the future. The BP risk evaluation model of supply chain accounts receivable constructed in this paper can better measure the risk level of supply chain accounts receivable financing behavior and provide a certain reference for financial institutions to carry out this business.
【學位授予單位】：安徽工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP183;F275

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