金融联结视角下农业龙头企业信用风险评估研究
发布时间：2018-09-09 12:37
【摘要】：农业是中国产业结构中的重要组成部分，农业龙头企业又是我国农业经济发展的突出代表,对我国农业龙头企业的信用风险进行评估具有重要的应用价值。参与金融联结的农业龙头企业，其与一般的企业不同，其凭借自身的经营生产能力，从正规金融机构获得资金，再以统贷统还、订单或担保的方式将资金转贷给农户，资金的真正使用者是农户，因此信用风险也存在差别。 本文首先以农业信贷补贴论、农村金融市场论、不完全竞争市场论等农村金融理论为理论基础，分析了农业龙头企业发展的基本情况，归纳了农业龙头企业参与金融联结的三种模式，总结了参与金融联结的农业龙头企业的特点，提出金融联结视角下农业龙头企业的信用风险来源于农业龙头企业自身、金融联结过程和外部环境等多方面。其次梳理了信用风险度量方法，通过对信用风险度量模型的比较，得出KMV模型是评价金融联结视角下农业龙头企业的信用风险较为可行的方法。然后运用KMV模型计算了47家农业上市企业2000年至2013年的违约距离，对违约距离进行分析得出如下结论： 1.农业龙头企业信用状况极差或极好的情况均为少数，绝大多数情况下是存在一定程度的信用风险。2.不同年份农业龙头企业的面临的信用风险不同，上市当年的违约距离较大，信用状况较好。3.不同地区的农业龙头企业的违约距离不同，东部的违约距离最大，，西部违约距离最小，经济越发达的地区信用风险越小。4.不同行业的农业龙头企业的违约距离不同，渔业的违约距离最大，林业的违约距离最小，渔业信用风险小，林业信用风险大。 本文提出金融机构应该建立农业龙头企业违约数据库，采用违约距离这一风险度量动态指标加强对参与金融联结的农业龙头企业的监测，并进一步验证违约距离的阙值，针对不同的地区、不同的行业的农业龙头企业金融机构应制定不同的信用风险评价标准，国家应积极规范和发展证券市场，为金融机构的信用风险管理创造良好的金融环境，提供真实有效的数据。 本文研究主要存在以下两个不足：一是本文为获得数据，只选取了上市的农业龙头企业作为样本来研究其信用风险，对于非上市公司本文中没有涉及到，事实上我国非上市公司众多，且非上市公司受到的信息更不透明，对非上市公司信用风险评价更加重要和迫切，二是本文只计算了47家农业上市龙头企业13年的违约距离，据此得到的分析结果虽有一定代表性，但数量相对还比较少，未能有效建立违约数据库，也有待更多的实证检验。
[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.
【学位授予单位】：中国海洋大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F324;F832.35
本文编号：2232392
[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.
【学位授予单位】：中国海洋大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F324;F832.35
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