基于BP神经网络的资产证券化信用风险评测

发布时间：2018-01-10 04:20

本文关键词：基于BP神经网络的资产证券化信用风险评测　出处：《商业时代》2014年05期 　论文类型：期刊论文

【摘要】：资产证券化是依托特定的资产组合或者现金流为支撑而发行的债券,也是融资途径的一种方式,它可以将流动性差、可产生预见稳定现金流的资产转换成有较强流动性的债券形式,从而在市场上流通。资产证券化的这种优势给金融机构提供了快速处置不良资产的有效途径。资产证券化这种金融衍生品近年来在我国得以应用,其优良的特性使其受到广泛的关注。资产池信用评测在资产证券化过程中发挥着至关重要的作用,本文的思路是构建一个尽可能涵盖资产证券化各参与方的风险控制体系,以可测量的指标来反映资产证券化信用违约率。运用BP神经网络模型对资产证券化资产池信用进行测评,从债务方、发起方、信托机构三方,选取不同的影响因素,对我国资产证券化实例进行实证分析,以期能够为我国资产证券化信用风险评测提供参考。
[Abstract]:Asset securitization is a bond issued on the basis of a specific portfolio or cash flow. It is also a way of financing, it can be poor liquidity. Assets that generate predictable stable cash flows are converted into bonds with strong liquidity. Thus, the advantage of asset securitization in the market provides an effective way for financial institutions to deal with non-performing assets quickly. Asset securitization, a financial derivative, has been applied in China in recent years. Asset pool credit evaluation plays an important role in the process of asset securitization. The idea of this paper is to construct a risk control system that covers the participants of asset securitization as much as possible. The credit default rate of asset securitization is reflected by measurable index. The credit of asset pool of asset securitization is evaluated by BP neural network model. The credit of asset pool of asset securitization is measured from debt party, sponsor party and trust organization. In order to provide a reference for the credit risk evaluation of asset securitization in China, the empirical analysis of asset securitization cases in China is carried out by selecting different influencing factors.
【作者单位】：郑州华信学院商学院;
【分类号】：F830.91;F224
【正文快照】： 引言资产证券化是依托特定的资产组合或者现金流为支撑而发行的债券,也是融资途径的一种方式,它可以将流动性差、可产生预见稳定现金流的资产转换成有较强流动性的债券形式,从而在市场上流通。资产证券化的这种优势给金融机构提供了快速处置不良资产的有效途径。资产证券化是

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