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Int. J. Financial Stud. 2018, 6(2), 39;

Quantifying Correlation Uncertainty Risk in Credit Derivatives Pricing

Deutsche Bank, EC2N 2DB London, UK
The views expressed herein should not be considered as investment advice or promotion. They represent personal research of the author and do not purport to reflect the views of his employers (current or past), or the associates or affiliates thereof.
Received: 3 January 2018 / Revised: 24 March 2018 / Accepted: 27 March 2018 / Published: 3 April 2018
(This article belongs to the Special Issue Finance, Financial Risk Management and their Applications)
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We propose a simple but practical methodology for the quantification of correlation risk in the context of credit derivatives pricing and credit valuation adjustment (CVA), where the correlation between rates and credit is often uncertain or unmodelled. We take the rates model to be Hull–White (normal) and the credit model to be Black–Karasinski (lognormal). We summarise recent work furnishing highly accurate analytic pricing formulae for credit default swaps (CDS) including with defaultable Libor flows, extending this to the situation where they are capped and/or floored. We also consider the pricing of contingent CDS with an interest rate swap underlying. We derive therefrom explicit expressions showing how the dependence of model prices on the uncertain parameter(s) can be captured in analytic formulae that are readily amenable to computation without recourse to Monte Carlo or lattice-based computation. In so doing, we crucially take into account the impact on model calibration of the uncertain (or unmodelled) parameters. View Full-Text
Keywords: perturbation expansion; Green’s function; model risk; model uncertainty; credit derivatives; CVA; correlation risk perturbation expansion; Green’s function; model risk; model uncertainty; credit derivatives; CVA; correlation risk

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Turfus, C. Quantifying Correlation Uncertainty Risk in Credit Derivatives Pricing. Int. J. Financial Stud. 2018, 6, 39.

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Int. J. Financial Stud. EISSN 2227-7072 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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