Assessing the impact of wrong-way risk on valuation adjustments of a portfolio of interest rate swaps

Master thesis (2021)

Authors

W.N. Jonkman Electrical Engineering, Mathematics and Computer Science

Contributors

L.A. Grzelak Numerical Analysis - EEMCS (mentor)
C.W. Oosterlee Numerical Analysis - EEMCS (graduation committee member)
C. Kraaikamp Applied Probability - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Niels Jonkman
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Published Date

13-01-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

We study the impact of wrong-way risk (WWR) on the credit valuation adjustment (CVA) of a portfolio of interest rate swaps (IRSs), using an intensity-based reduced form model. To model WWR in IRSs we create a dependence between he underlying market risk factor of the IRS and the survival probability of the
counterparty. The focus lies on modeling the credit part of the CVA, choosing the most suitable default model. Using a Monte Carlo (MC) framework, we correlate the Brownian increments of the stochastic processes that describe the interest rate and the hazard rate. Assuming the correlation parameter is chosen based on historical data, we solve the problem of leaking correlation. Two
stochastic processes for the credit part are chosen, the CIR++ and the JCIR++, such that the influence of the model choice can be separated from the impact of WWR. With a case study, we vary the correlation parameter to quantify the impact of WWR on CVA of the portfolio. We show that the introduced dependence has a significant impact on the CVA, that depends on the calibration, the portfolio and the chosen correlation. Solving the leaking correlation problem can increase the impact of WWR on the CVA, especially using JCIR++ dynamics.