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Modelling Specific Interest Rate Risk with Estimation of Missing Data

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  • Thomas Siegl
  • Peter Quell
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    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.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/1350486042000297243
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Mathematical Finance.

    Volume (Year): 12 (2004)
    Issue (Month): 3 ()
    Pages: 283-309

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    Handle: RePEc:taf:apmtfi:v:12:y:2004:i:3:p:283-309

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    Web page: http://www.tandfonline.com/RAMF20

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    Related research

    Keywords: Statistical estimation with missing data; specific interest rate risk; multiple imputation; EM-algorithm; value at risk; copula functions;

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