【摘要】：農(nóng)業(yè)是中國(guó)產(chǎn)業(yè)結(jié)構(gòu)中的重要組成部分，農(nóng)業(yè)龍頭企業(yè)又是我國(guó)農(nóng)業(yè)經(jīng)濟(jì)發(fā)展的突出代表,對(duì)我國(guó)農(nóng)業(yè)龍頭企業(yè)的信用風(fēng)險(xiǎn)進(jìn)行評(píng)估具有重要的應(yīng)用價(jià)值。參與金融聯(lián)結(jié)的農(nóng)業(yè)龍頭企業(yè)，其與一般的企業(yè)不同，其憑借自身的經(jīng)營(yíng)生產(chǎn)能力，從正規(guī)金融機(jī)構(gòu)獲得資金，再以統(tǒng)貸統(tǒng)還、訂單或擔(dān)保的方式將資金轉(zhuǎn)貸給農(nóng)戶，資金的真正使用者是農(nóng)戶，因此信用風(fēng)險(xiǎn)也存在差別。 本文首先以農(nóng)業(yè)信貸補(bǔ)貼論、農(nóng)村金融市場(chǎng)論、不完全競(jìng)爭(zhēng)市場(chǎng)論等農(nóng)村金融理論為理論基礎(chǔ)，分析了農(nóng)業(yè)龍頭企業(yè)發(fā)展的基本情況，歸納了農(nóng)業(yè)龍頭企業(yè)參與金融聯(lián)結(jié)的三種模式，總結(jié)了參與金融聯(lián)結(jié)的農(nóng)業(yè)龍頭企業(yè)的特點(diǎn)，提出金融聯(lián)結(jié)視角下農(nóng)業(yè)龍頭企業(yè)的信用風(fēng)險(xiǎn)來(lái)源于農(nóng)業(yè)龍頭企業(yè)自身、金融聯(lián)結(jié)過(guò)程和外部環(huán)境等多方面。其次梳理了信用風(fēng)險(xiǎn)度量方法，通過(guò)對(duì)信用風(fēng)險(xiǎn)度量模型的比較，得出KMV模型是評(píng)價(jià)金融聯(lián)結(jié)視角下農(nóng)業(yè)龍頭企業(yè)的信用風(fēng)險(xiǎn)較為可行的方法。然后運(yùn)用KMV模型計(jì)算了47家農(nóng)業(yè)上市企業(yè)2000年至2013年的違約距離，對(duì)違約距離進(jìn)行分析得出如下結(jié)論： 1.農(nóng)業(yè)龍頭企業(yè)信用狀況極差或極好的情況均為少數(shù)，絕大多數(shù)情況下是存在一定程度的信用風(fēng)險(xiǎn)。2.不同年份農(nóng)業(yè)龍頭企業(yè)的面臨的信用風(fēng)險(xiǎn)不同，上市當(dāng)年的違約距離較大，信用狀況較好。3.不同地區(qū)的農(nóng)業(yè)龍頭企業(yè)的違約距離不同，東部的違約距離最大，，西部違約距離最小，經(jīng)濟(jì)越發(fā)達(dá)的地區(qū)信用風(fēng)險(xiǎn)越小。4.不同行業(yè)的農(nóng)業(yè)龍頭企業(yè)的違約距離不同，漁業(yè)的違約距離最大，林業(yè)的違約距離最小，漁業(yè)信用風(fēng)險(xiǎn)小，林業(yè)信用風(fēng)險(xiǎn)大。 本文提出金融機(jī)構(gòu)應(yīng)該建立農(nóng)業(yè)龍頭企業(yè)違約數(shù)據(jù)庫(kù)，采用違約距離這一風(fēng)險(xiǎn)度量動(dòng)態(tài)指標(biāo)加強(qiáng)對(duì)參與金融聯(lián)結(jié)的農(nóng)業(yè)龍頭企業(yè)的監(jiān)測(cè)，并進(jìn)一步驗(yàn)證違約距離的闕值，針對(duì)不同的地區(qū)、不同的行業(yè)的農(nóng)業(yè)龍頭企業(yè)金融機(jī)構(gòu)應(yīng)制定不同的信用風(fēng)險(xiǎn)評(píng)價(jià)標(biāo)準(zhǔn)，國(guó)家應(yīng)積極規(guī)范和發(fā)展證券市場(chǎng)，為金融機(jī)構(gòu)的信用風(fēng)險(xiǎn)管理創(chuàng)造良好的金融環(huán)境，提供真實(shí)有效的數(shù)據(jù)。 本文研究主要存在以下兩個(gè)不足：一是本文為獲得數(shù)據(jù)，只選取了上市的農(nóng)業(yè)龍頭企業(yè)作為樣本來(lái)研究其信用風(fēng)險(xiǎn)，對(duì)于非上市公司本文中沒(méi)有涉及到，事實(shí)上我國(guó)非上市公司眾多，且非上市公司受到的信息更不透明，對(duì)非上市公司信用風(fēng)險(xiǎn)評(píng)價(jià)更加重要和迫切，二是本文只計(jì)算了47家農(nóng)業(yè)上市龍頭企業(yè)13年的違約距離，據(jù)此得到的分析結(jié)果雖有一定代表性，但數(shù)量相對(duì)還比較少，未能有效建立違約數(shù)據(jù)庫(kù)，也有待更多的實(shí)證檢驗(yàn)。
[Abstract]:Agriculture is an important part of China's industrial structure and the leading agricultural enterprises are the outstanding representatives of China's agricultural economic development. It is of great value to evaluate the credit risk of leading agricultural enterprises in China. In order to obtain funds from formal financial institutions, and then transfer the funds to farmers by means of unified loans, orders or guarantees, the real users of the funds are farmers, so the credit risk is also different.
Firstly, based on the theories of agricultural credit subsidy, rural financial market and imperfect competitive market, this paper analyzes the basic situation of the development of agricultural leading enterprises, sums up the three modes of agricultural leading enterprises participating in financial links, summarizes the characteristics of agricultural leading enterprises participating in financial links, and puts forward the gold The credit risk of agricultural leading enterprises from the perspective of financial linkage comes from the agricultural leading enterprises themselves, the process of financial linkage and the external environment, etc. Secondly, it combs the credit risk measurement methods, and through the comparison of credit risk measurement models, it is concluded that the KMV model is more suitable for evaluating the credit risk of agricultural leading enterprises from the perspective of financial linkage. Then, using KMV model, the default distance of 47 listed agricultural enterprises from 2000 to 2013 is calculated, and the analysis of the default distance draws the following conclusions:
1. Agricultural leading enterprises'credit status is very poor or excellent in a few cases, and there is a certain degree of credit risk in the vast majority of cases. 2. Agricultural leading enterprises in different years face different credit risks, listed in the year of default distance is larger, credit situation is better. 3. Agricultural leading enterprises in different regions of the default distance is different. The largest distance of breach of contract is in the east, the smallest distance of breach of contract is in the west, and the smaller the credit risk is in the economically developed areas.
This paper suggests that financial institutions should establish a default database of agricultural leading enterprises, adopt default distance as a dynamic risk measurement index to strengthen the monitoring of agricultural leading enterprises participating in financial links, and further verify the default distance. According to different regions, financial institutions of agricultural leading enterprises in different industries should formulate no default. With the same credit risk assessment criteria, the state should actively regulate and develop the securities market, create a good financial environment for the credit risk management of financial institutions, and provide real and effective data.
There are two main shortcomings in this paper: first, in order to obtain data, this paper only selects listed agricultural leading enterprises as a sample to study their credit risk, for non-listed companies this article does not involve, in fact, there are many non-listed companies in China, and the information of non-listed companies is more opaque, the trust of non-listed companies. It is more important and urgent to use risk assessment. Secondly, this paper only calculates the 13-year default distance of 47 leading agricultural listed enterprises. Although the results obtained from this analysis are representative, the number is relatively small, and the database of default can not be effectively established. More empirical tests are needed.
【學(xué)位授予單位】：中國(guó)海洋大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F324;F832.35

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