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Modelling Specific Interest Rate Risk with Estimation of Missing Data
Authors:Thomas Siegl
Institution:DZ BANK AG , Platz der Republik , D‐60265, Frankfurt/Main, Germany
Abstract:For the treatment of specific interest rate risk, a risk model is suggested, quantifying and combining both market and credit risk components consistently. The market risk model is based on credit spreads derived from traded bond prices. Though traded bond prices reveal a maximum amount of issuer specific information, illiquidity problems do not allow for classical parameter estimation in this context. To overcome this difficulty an efficient multiple imputation method is proposed that also quantifies the amount of risk associated with missing data. The credit risk component is based on event risk caused by correlated rating migrations of individual bonds using a Copula function approach.
Keywords:Statistical estimation with missing data  specific interest rate risk  multiple imputation  EM‐algorithm  value at risk  copula functions
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