Managing the risk of embedded options in non-traded credit using portfolio modeling

IF 0.6 Q4 BUSINESS, FINANCE
Bernd Engelmann
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Abstract

A framework for measuring and managing the risk of embedded options in non-traded credit is developed. For typical bank clients there is no market information related to their ability to pay (bond or CDS spreads) available. The absence of market information is a key assumption of this paper. In this case, a bank has to rely solely on statistical data to judge the credit quality of a borrower. To value a loan with embedded options like prepayment rights, a model is proposed that combines an interest rate derivatives pricing model with statistical information on default and recovery rates. Using this for evaluating the risk of embedded options in loans, it is shown how the concepts of credit risk management can be applied after defining a suitable concept of risk. It turns out that this modeling framework combines the theories of derivatives pricing and credit risk modeling in the sense that derivatives pricing theory measures the costs for hedging optional components in loans while credit risk modeling measures the risk that these hedging costs turn out to be inadequate. This risk depends not only on the single loan’s risk characteristics but also on the dependence structure and the granularity of the total loan portfolio.
利用投资组合建模管理非交易信贷中嵌入期权的风险
建立了一个衡量和管理非交易信贷中嵌入期权风险的框架。对于典型的银行客户来说,没有与他们的支付能力(债券或CDS价差)相关的市场信息。市场信息的缺失是本文的一个关键假设。在这种情况下,银行只能依靠统计数据来判断借款人的信用质量。为了对包含提前还款权等期权的贷款进行估值,提出了一个模型,该模型将利率衍生品定价模型与违约率和回收率的统计信息相结合。使用此方法评估贷款中嵌入期权的风险,显示了在定义合适的风险概念后如何应用信用风险管理的概念。结果表明,该模型框架结合了衍生品定价理论和信用风险建模理论,衍生品定价理论衡量的是对贷款中可选成分进行套期保值的成本,而信用风险建模衡量的是这些套期保值成本不足的风险。这种风险不仅取决于单个贷款的风险特征,还取决于整个贷款组合的依赖结构和粒度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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