汽车ABS贷款水平数据:改进的风险分析

IF 0.4 Q4 BUSINESS, FINANCE

Journal of Structured Finance Pub Date : 2022-01-04 DOI:10.3905/jsf.2022.1.130

Yini Yang, Joy Zhang, Jiawei Zhang

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引用次数: 0

摘要

2014年，美国证券交易委员会的AB条例要求公开汽车贷款资产支持证券（ABS）的贷款水平数据。因此，2017年至2021年的贷款水平数据显示了一组丰富的贷款水平变量，这些变量揭示了抵押品的表现模式，并改进了风险分析，尤其是信贷风险。纳入这些贷款水平驱动因素的统计预测模型大大提高了汽车ABS贷款违约预测的准确性和粒度，并可以为使用这些模型的投资者和风险经理提供好处。

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Auto ABS Loan-Level Data: Improved Risk Analysis

In 2014, the US Securities and Exchange Commission’s Regulation AB mandated loan-level data disclosure for public auto loan asset-backed securities (ABS). As a result, the loan level data from 2017 to 2021 display a rich set of loan-level variables that shed light on collateral performance patterns and improve risk analysis, especially for credit risk. Statistical predictive models that incorporate these loan-level drivers substantially improve the accuracy and granularity of default forecasts for auto ABS loans, and can provide benefits for investors and risk managers who use them.

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来源期刊

Journal of Structured Finance BUSINESS, FINANCE-

CiteScore

0.60

自引率

25.00%

发文量

期刊介绍： The Journal of Structured Finance (JSF) is the only international, peer-reviewed journal devoted to empirical analysis and practical guidance on structured finance instruments, techniques, and strategies. JSF covers a wide range of topics including credit derivatives and synthetic securitization, secondary trading in the CDO market, securitization in emerging markets, trends in major consumer loan categories, accounting, regulatory, and tax issues in the structured finance industry.