基于农业发展银行的信用风险压力测试研究
发布时间：2018-08-28 06:57
【摘要】：随着社会主义新农村建设的全面推进和金融体制改革的不断深化,在农业农村经济中起着扶持、补充和引导功能的农业发展银行,一方面继续完成政府交予的农业政策性金融业务,形成了以支持国家粮棉购销储业务为主体,以支持农业产业化经营和农业农村基础设施建设为两翼的业务发展格局,另一方面在政策允许范围内自主选择兼顾社会效益和经济效益的商业性业务,逐步形成以满足“三农”需要和市场需求为中心的全方位、综合式服务。因而农业发展银行的信用风险不仅来自政策层面,还来自农业农村经济冲击。选择合适的模型评估和预测农业发展银行信用风险,提高农业发展银行的风险管理水平显得尤为重要。本文首先比较分析了诸如KMV、CreditMetrics、CPV等风险度量模型的特点、优点和缺点,了解各类信用风险度量模型的运用环境,深入分析了压力测试的实施框架,包括别风险因子,构建风险传导模型,选择合适的压力情景执行压力测试,分析压力测试报告。综合考虑其信用风险的特点和形成原因,最终选择采用CPV模型对信用风险执行压力测。在模型构造中,本文筛选出影响农业发展银行信用风险的宏观因子和行业因子,使用Logit模型将不良贷款率转化为中介指标Y,以指标Y作为因变量与宏观和行业因子进行多元线性回归分析,建立风险传导模型。通过自变量的自回归和残差项的蒙特卡洛模拟生成压力情景,进行宏观压力测试,定量分析宏观和行业因子在中压情景、强压情景下对农业发展银行不良贷款率的影响。结果发现:中央和地方财政支出增长率,农村居民人均纯收入对农发行不良贷款率的影响是显著的,特别是农村居民人均纯收入对农发行不良贷款率冲击较强。通过历史数据对宏观因子和行业因子的自回归,得出基准情境下,中央和地方财政支出增长率为13.75%,农村居民人均纯收入为10057.70元,此时农业发展银行的不良贷款率为0.45%,在中央和地方财政支出增长率的中压和强压冲击下,农业发展银行的不良贷款率分别为0.57%和0.68%。在农村居民人均纯收入的中压和强压冲击下不良贷款率分别为0.55%和0.78%。最后提出建议:(1)培育先进的风险管理文化。(2)完善内控机制。(3)完善信贷审批监控。(4)完善信用风险保障补偿机制。(5)完善信用风险配套设施。
[Abstract]:With the comprehensive development of the new socialist countryside construction and the deepening of the financial system reform, the Agricultural Development Bank, which plays a supporting, supplementary and guiding role in the agricultural rural economy, On the one hand, it continued to complete the agricultural policy-oriented financial business entrusted by the government, forming a business development pattern with supporting the national grain and cotton purchase, marketing and storage business as the main body, and supporting the agricultural industrialization operation and the construction of agricultural rural infrastructure as its two wings. On the other hand, the commercial business with social and economic benefits should be chosen independently within the scope of policy, and a comprehensive and comprehensive service should be formed to meet the needs of agriculture, rural areas and farmers and market demand. Therefore, the credit risk of the Agricultural Development Bank comes not only from the policy level, but also from the agricultural rural economic impact. It is very important to select appropriate models to evaluate and predict the credit risk of the Agricultural Development Bank and to improve the risk management level of the Agricultural Development Bank. In this paper, the characteristics, advantages and disadvantages of risk measurement models such as KMV,CreditMetrics,CPV are compared, and the application environment of various credit risk measurement models is understood. The implementation framework of stress testing, including specific risk factors, is analyzed in depth. Build a risk conduction model, select appropriate stress scenarios to perform stress tests, and analyze stress test reports. Considering the characteristics and reasons of credit risk, CPV model is used to test credit risk. In the model construction, the macro factors and industry factors that affect the credit risk of Agricultural Development Bank are screened out in this paper. The Logit model is used to transform the non-performing loan rate into the intermediary index Y, and the risk conduction model is established by using the index Y as the dependent variable and the macro and industry factors as multiple linear regression analysis. Through the autoregressive of independent variables and Monte Carlo simulation of residual terms to generate stress scenarios, the macro stress test was carried out to quantitatively analyze the impact of macro and industry factors on the non-performing loan ratio of Agricultural Development Bank under the medium pressure scenario and the strong pressure scenario. The results show that the growth rate of central and local fiscal expenditure and the per capita net income of rural residents have a significant impact on the ratio of non-performing loans, especially the impact of rural residents' per capita net income on the ratio of non-performing loans. Through the autoregression of historical data to macro factors and industry factors, it is concluded that the growth rate of central and local fiscal expenditure is 13.75 yuan, and the per capita net income of rural residents is 10057.70 yuan. At this time, the non-performing loan rate of the Agricultural Development Bank is 0.45. Under the impact of the middle and strong pressure of the growth rate of the central and local fiscal expenditure, the non-performing loan rate of the Agricultural Development Bank is 0.57% and 0.68% respectively. The non-performing loan ratio was 0.55% and 0.78% respectively under the impact of medium pressure and strong pressure on the per capita net income of rural residents. Finally, some suggestions are put forward: (1) to cultivate advanced risk management culture, (2) to perfect internal control mechanism, (3) to perfect credit approval and supervision, (4) to perfect credit risk guarantee and compensation mechanism, and (5) to perfect supporting facilities for credit risk.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.33
本文编号：2208632
[Abstract]:With the comprehensive development of the new socialist countryside construction and the deepening of the financial system reform, the Agricultural Development Bank, which plays a supporting, supplementary and guiding role in the agricultural rural economy, On the one hand, it continued to complete the agricultural policy-oriented financial business entrusted by the government, forming a business development pattern with supporting the national grain and cotton purchase, marketing and storage business as the main body, and supporting the agricultural industrialization operation and the construction of agricultural rural infrastructure as its two wings. On the other hand, the commercial business with social and economic benefits should be chosen independently within the scope of policy, and a comprehensive and comprehensive service should be formed to meet the needs of agriculture, rural areas and farmers and market demand. Therefore, the credit risk of the Agricultural Development Bank comes not only from the policy level, but also from the agricultural rural economic impact. It is very important to select appropriate models to evaluate and predict the credit risk of the Agricultural Development Bank and to improve the risk management level of the Agricultural Development Bank. In this paper, the characteristics, advantages and disadvantages of risk measurement models such as KMV,CreditMetrics,CPV are compared, and the application environment of various credit risk measurement models is understood. The implementation framework of stress testing, including specific risk factors, is analyzed in depth. Build a risk conduction model, select appropriate stress scenarios to perform stress tests, and analyze stress test reports. Considering the characteristics and reasons of credit risk, CPV model is used to test credit risk. In the model construction, the macro factors and industry factors that affect the credit risk of Agricultural Development Bank are screened out in this paper. The Logit model is used to transform the non-performing loan rate into the intermediary index Y, and the risk conduction model is established by using the index Y as the dependent variable and the macro and industry factors as multiple linear regression analysis. Through the autoregressive of independent variables and Monte Carlo simulation of residual terms to generate stress scenarios, the macro stress test was carried out to quantitatively analyze the impact of macro and industry factors on the non-performing loan ratio of Agricultural Development Bank under the medium pressure scenario and the strong pressure scenario. The results show that the growth rate of central and local fiscal expenditure and the per capita net income of rural residents have a significant impact on the ratio of non-performing loans, especially the impact of rural residents' per capita net income on the ratio of non-performing loans. Through the autoregression of historical data to macro factors and industry factors, it is concluded that the growth rate of central and local fiscal expenditure is 13.75 yuan, and the per capita net income of rural residents is 10057.70 yuan. At this time, the non-performing loan rate of the Agricultural Development Bank is 0.45. Under the impact of the middle and strong pressure of the growth rate of the central and local fiscal expenditure, the non-performing loan rate of the Agricultural Development Bank is 0.57% and 0.68% respectively. The non-performing loan ratio was 0.55% and 0.78% respectively under the impact of medium pressure and strong pressure on the per capita net income of rural residents. Finally, some suggestions are put forward: (1) to cultivate advanced risk management culture, (2) to perfect internal control mechanism, (3) to perfect credit approval and supervision, (4) to perfect credit risk guarantee and compensation mechanism, and (5) to perfect supporting facilities for credit risk.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.33
【参考文献】
相关期刊论文 前1条
1 杨青;张亮亮;魏立新;;宏观经济变量影响下的银行极端操作风险研究[J];管理科学学报;2012年06期
，本文编号：2208632
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