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Approximating Unilateral CVA for Interest Rate Swap Portfolios

Saleem Almgren, Anton LU and Mozaffari, Saadat LU (2026) In Master's Theses in Mathematical Sciences FMSM01 20261
Mathematical Statistics
Abstract
This thesis investigates whether the unilateral credit valuation adjustment (CVA) of
plain-vanilla interest rate swap portfolios can be approximated accurately using a pre-
computed library of basis-swap CVAs, avoiding the cost of full Monte Carlo revaluation.
The approximation is constructed to require only a yield curve, a swaption volatility
surface, and counterparty CDS spreads as inputs. The method is evaluated against a
Monte Carlo benchmark for counterparties from three sectors and across four interest-rate
models: the Hull–White one-factor, Hull–White two-factor, shifted Cox–Ingersoll–Ross,
and a stochastic-volatility Hull–White model. The estimation achieves a mean absolute
percentage error of 20–24% across models.... (More)
This thesis investigates whether the unilateral credit valuation adjustment (CVA) of
plain-vanilla interest rate swap portfolios can be approximated accurately using a pre-
computed library of basis-swap CVAs, avoiding the cost of full Monte Carlo revaluation.
The approximation is constructed to require only a yield curve, a swaption volatility
surface, and counterparty CDS spreads as inputs. The method is evaluated against a
Monte Carlo benchmark for counterparties from three sectors and across four interest-rate
models: the Hull–White one-factor, Hull–White two-factor, shifted Cox–Ingersoll–Ross,
and a stochastic-volatility Hull–White model. The estimation achieves a mean absolute
percentage error of 20–24% across models. Introducing a scalar adjustment to the netting
ratio reduces the MAPE to 16.1%. The results indicate that the estimation could have
practical use for fast intraday calculation of CVA but as a complement rather than a
substitute for full Monte Carlo CVA. (Less)
Please use this url to cite or link to this publication:
author
Saleem Almgren, Anton LU and Mozaffari, Saadat LU
supervisor
organization
course
FMSM01 20261
year
type
H2 - Master's Degree (Two Years)
subject
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFMS-3564-2026
ISSN
1404-6342
other publication id
2026:E82
language
English
id
9239483
date added to LUP
2026-06-18 16:57:19
date last changed
2026-06-18 16:57:19
@misc{9239483,
  abstract     = {{This thesis investigates whether the unilateral credit valuation adjustment (CVA) of
plain-vanilla interest rate swap portfolios can be approximated accurately using a pre-
computed library of basis-swap CVAs, avoiding the cost of full Monte Carlo revaluation.
The approximation is constructed to require only a yield curve, a swaption volatility
surface, and counterparty CDS spreads as inputs. The method is evaluated against a
Monte Carlo benchmark for counterparties from three sectors and across four interest-rate
models: the Hull–White one-factor, Hull–White two-factor, shifted Cox–Ingersoll–Ross,
and a stochastic-volatility Hull–White model. The estimation achieves a mean absolute
percentage error of 20–24% across models. Introducing a scalar adjustment to the netting
ratio reduces the MAPE to 16.1%. The results indicate that the estimation could have
practical use for fast intraday calculation of CVA but as a complement rather than a
substitute for full Monte Carlo CVA.}},
  author       = {{Saleem Almgren, Anton and Mozaffari, Saadat}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master's Theses in Mathematical Sciences}},
  title        = {{Approximating Unilateral CVA for Interest Rate Swap Portfolios}},
  year         = {{2026}},
}