基于模糊突变理论的供应链金融信用风险评估

发布时间：2018-06-15 09:27

本文选题：供应链金融 + 信用风险评估　；参考：《武汉理工大学》2015年硕士论文

【摘要】：供应链金融作为解决中小企业融资难问题的一种有效途径,受到银行、中小企业、物流企业等多方面的关注。近些年,互联网、云计算等科技逐渐被应用到金融领域,催生了一些新的供应链金融模式及衍生产品,这使得相关的业务控制变得更加复杂,导致风险爆发的可能性增大。因此,科学客观的评价供应链金融的信用风险成为银行关注的焦点,也是银行成功实施供应链金融的基础,具有巨大现实意义。本文在对现有文献资料、研究成果进行深入分析归纳的基础上,阐述了供应链金融的概念和特征,通过对供应链金融信用风险进行分析,建立基于模糊突变理论的供应链金融信用风险评价模型,并设计了相应的评价指标体系,最后通过实证研究证明了该方法的有效性和适用性。供应链金融信用风险评估方法很多,本文在阐述和分析了多种风险评估方法后,对其各自的优缺点做了比较。由于供应链金融信用风险状况复杂,存在相对性、动态性、模糊性、突变性等不确定特质,其风险的变化往往是突然的、非连续性的,然而传统风险评价方法具有一定的局限性,突变理论作为研究非连续性变化的数学理论,对于研究信用风险这样具有非连续变化特征的事物具有一定的启发作用和开拓价值。本文首先介绍了突变理论的基本原理以及数理模型,分析了基于突变理论的供应链金融信用风险评估方法的可行性,并结合模糊数学理论,将其应用于供应链金融信用风险评估领域,建立了基于模糊突变的供应链金融信用风险评价模型,该模型仅需考虑评价指标的相对排序,有效降低了评价工作的主观性,提高了风险评价的准确性和效率。在建立风险评估模型后,本文综合运用频数统计法和专家打分法对供应链金融信用风险评价指标进行筛选,根据指标体系构建的原则,基于突变理论的特点,重点考察突变因素的影响,建立了基于模糊突变理论的供应链金融信用风险评价指标体系。本文最后结合四家乳制品集团2004-2010年的经营数据和行业状况,利用本文建立的模型对其供应链金融信用风险进行了度量。同时,将得到的评估结果与模糊综合评价法的评估结果进行比较,研究结果表明,基于突变理论的评估方法在信用风险评估中对突发风险反应更为灵敏,结果更符合实际情况,该理论模型不失为现有信用风险评估方法的有效补充,具有更好科学性与适用性。
[Abstract]:As an effective way to solve the financing problem of SMEs, supply chain finance is concerned by banks, small and medium-sized enterprises, logistics enterprises and so on. In recent years, Internet, cloud computing and other technologies have been gradually applied to the financial field, resulting in a number of new supply chain financial models and derivatives, which makes the related business control become more complex, leading to the increased likelihood of risk outbreak. Therefore, the scientific and objective evaluation of the credit risk of supply chain finance has become the focus of attention of banks, and is also the foundation of successful implementation of supply chain finance, which has great practical significance. Based on the deep analysis and induction of the existing literature and research results, this paper expounds the concept and characteristics of supply chain finance, and analyzes the credit risk of supply chain finance. The credit risk evaluation model of supply chain finance based on fuzzy catastrophe theory is established, and the corresponding evaluation index system is designed. Finally, the validity and applicability of this method are proved by empirical research. There are many methods of credit risk assessment in supply chain finance. After explaining and analyzing various risk assessment methods, this paper compares their advantages and disadvantages. Because of the complexity of credit risk in supply chain, there are some uncertain characteristics, such as relativity, dynamic, fuzziness, mutation and so on, so the change of risk is often sudden and discontinuous. However, the traditional risk assessment method has some limitations. The catastrophe theory, as a mathematical theory to study discontinuous change, has a certain enlightening effect and pioneering value for the study of discontinuous changes such as credit risk. This paper first introduces the basic principle and mathematical model of catastrophe theory, analyzes the feasibility of credit risk assessment method of supply chain finance based on catastrophe theory, and combines with fuzzy mathematics theory. Applying it to the field of supply chain financial credit risk assessment, a model of supply chain financial credit risk evaluation based on fuzzy mutation is established. The model only needs to consider the relative ranking of evaluation indexes, which effectively reduces the subjectivity of evaluation work. The accuracy and efficiency of risk evaluation are improved. After establishing the risk assessment model, this paper uses the frequency statistics method and the expert scoring method to screen the credit risk evaluation index of the supply chain finance, according to the principle of the index system construction, based on the characteristics of the catastrophe theory. Based on fuzzy catastrophe theory, the credit risk evaluation index system of supply chain finance is established. In the end, combined with the operating data and industry situation of four dairy groups from 2004 to 2010, this paper uses the model established in this paper to measure the credit risk of supply chain finance. At the same time, the evaluation results obtained are compared with the results of fuzzy comprehensive evaluation method. The results show that the assessment method based on catastrophe theory is more sensitive to the unexpected risk response in credit risk assessment, and the results are more in line with the actual situation. The theoretical model is an effective supplement to the existing credit risk assessment methods and has better scientific and applicability.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F274;F832.4

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