随机挽回率下第n次违约互换的蒙特卡罗模拟定价

考虑到挽回率是违约互换定价的重要因素,同时获得准确的挽回率也是极其困难的,于是假设挽回率是随机的,并与对应资产违约时间呈Copula类相依结构.在该假设条件下提出一种对第n次违约互换定价的模拟算法.通过实证模拟发现,恒定挽回率,独立随机挽回率和Copula结构的挽回率对应的定价结果相差较大.     

改进的云重心评判法在高技术企业信用评价中的应用

提出一种改进的云重心评判法,并应用于高技术企业信用评价.首先,借鉴TOPSIS法的基本思想,基于理想状态和负理想状态,对综合云重心向量进行归一化,并采用修正的加权偏离度来衡量云重心的变化,从而克服了传统云重心评判法的不足.其次,针对高技术企业信用评价中的不确定性,运用改进的云重心评判法对高技术企业信用状态进行实证测评,结果证明了该方法的合理性和适用性.     

An incentive-compatible solution for trade credit term incorporating default risk

This paper studies the optimal trade credit term decision in an extended economic ordering quantity (EOQ) framework that incorporates a default risk component. A principal-agent bilevel programming model with costs minimization objectives is set up to derive the incentive-compatible credit term. The supplier determines the credit term as the leader in the first level programming, by balancing her/his financing capacity with the retailer’s default risk, order behavior and cost shifting. At the second level, the retailer makes decisions on ordering and payment time by reacting on the term offered by the supplier. A first order condition solution procedure is derived for the bilevel programming when credit term is confined within the practically feasible interval. Two key results are obtained – the condition to derive incentive-compatible credit term, and an equation system to derive threshold default risk criterion filtering retailers suitable for credit granting. Numerical experiments show that the capital cost of the supplier is the most important factor determining the credit term. Default risk acts like a filtering criterion for selecting retailers suitable for credit granting. Empirical evidence supporting our theoretical considerations is obtained by estimating three panel econometric models, using a dataset from China’s listed companies.     

基于公路运力信用结构的供应链金融授信分析

文章首先从信用入手,分析供应链金融增信的要素,剖析公路运力信用结构组成,构建主体信用、交易信用及监管信用的具体指标,并明确三者与供应链金融授信额度的关系。其次,以融资自偿为基础,通过分析公路运力成本的构成及统计数据,确定出授信比率的基础值以及监管信用对基础值的影响。通过物流企业货量服从正态分布的特征,模拟出公路运力运费收入以及交易信用对运费收入的影响。最后,结合两者构建出受主体信用现金流约束检验的授信额度模型,并就金融机构风险偏好为风险规避的情况进行了算例分析。     

Differential Replication for Credit Scoring in Regulated Environments

Differential replication is a method to adapt existing machine learning solutions to the demands of highly regulated environments by reusing knowledge from one generation to the next. Copying is a technique that allows differential replication by projecting a given classifier onto a new hypothesis space, in circumstances where access to both the original solution and its training data is limited. The resulting model replicates the original decision behavior while displaying new features and characteristics. In this paper, we apply this approach to a use case in the context of credit scoring. We use a private residential mortgage default dataset. We show that differential replication through copying can be exploited to adapt a given solution to the changing demands of a constrained environment such as that of the financial market. In particular, we show how copying can be used to replicate the decision behavior not only of a model, but also of a full pipeline. As a result, we can ensure the decomposability of the attributes used to provide explanations for credit scoring models and reduce the time-to-market delivery of these solutions.     

个人信用评分的Adaptive Lasso-Logistic回归分析

以个人信用风险为研究对象,分析影响个人信用评分的因素.利用某商业银行个人信用数据,并采用.Adaptive Lasso-Logistic回归模型对影响顾客的个人信用风险的因素进行分析,并与传统Logistic回归模型以及Lasso-Logistic回归模型进行比较.以对顾客"好"与"坏"的二分类结果的正确比例为主要衡量标准,实证发现以.Adaptive Lassi-Logistic回归方法建立的个人信用评分模型,在变量选择和解释上,以及预测的准确性上,均优于传统的Logistic和Lasso-Logistic方法.     

数据包络分析在信用评估中的应用

提出了一种基于拒绝案例集的数据包络分析模型和边界为分段线性分离超平面的分类方法，探讨了在只掌握单方面信息(信用差的单位)的情况下，如何对新单位进行信用评估的问题，并给出了评价决策单元信用状况的具体方法，应用实例表明所提出的模型和方法是可行的。     

学生成绩的学分绩与主成分排序模型

利用多元统计中的主成分分析研究学生成绩,发现第一主成分排序与学分绩排序结果基本相同,提出用第一主成分代替学分绩对学生进行综合评价更加合理.而且主成分还能反映教学过程中的优点和不足.对教学有一定的指导意义.     

基于随机市场需求的供应链融资模式研究

传统供应链融资模型大都在线性市场需求情形下分析零售商的商业信用、债权融资等内外部融资模式。本文同时了考虑零售商的股权融资、债权融资以及商业信用融资模式, 并引入随机市场需求因素, 针对一个供应商和两个具有资金约束零售商组成的两级供应链, 分析债权股权融资比例、商业信用等因素对零售商融资策略的影响, 并构建基于随机市场需求的融资模型;进一步, 利用数值示例和敏感性分析对此融资模型进行深入探讨。研究发现:当债权融资比例小于某临界值时, 零售商债权融资比例与订购量正相关, 反之债权融资比例与订购量负相关;对于一个服从均匀分布函数的随机市场需求而言, 若供应链采用外部融资模式, 那么随着其债权融资比例的增大, 利润将逐渐增加;若零售商采用商业信用融资模式, 那么其融资利率与利润负相关。相关研究结论对于供应链上中小企业融资模式的选择具有重要理论指导意义和实际引用价值。     

基于BP神经网络的行业间中小企业信用评估模型及应用

首先构建了行业间中小企业信用评估指标体系,然后利用安徽省不同行业的800家中小企业调查数据,将其分为训练样本集和测试样本集,对BP神经网络的构造进行讨论,确定BP神经网络的算法,建立起基于BP神经网络的行业间信用评估模型,并代入2003年度全国农业和工业的部分分行业数据进行实证,并对仿真结果做出分析,指出造成农、工行业信用较大差距的原因,并提出加强农业行业信用建设的建议.