Valuing Early Exercise Interest Rate Options with Multi-Factor Affine Models

27 Pages Posted: 4 Mar 2010 Last revised: 27 Apr 2015

See all articles by Sebastian Jaimungal

Sebastian Jaimungal

University of Toronto - Department of Statistics

Vladimir Surkov

RBC Capital Markets

Date Written: October 30, 2012

Abstract

Multi-factor interest-rate models are widely used. Contingent claims with early-exercise features are often valued by resorting to trees, finite-difference schemes and Monte Carlo simulations. When jumps are present, however, these methods are less effective. In this work we develop an algorithm based on a sequence of measure changes coupled with Fourier transform solutions of the pricing partial integro-differential equation to solve the pricing problem. The new algorithm, which we call the irFST method, also neatly computes option sensitivities. Furthermore, we develop are able to obtain closed-form formulae for accrual swaps and accrual range notes. We demonstrate the versatility and precision of the method through numerical experiments on European, Bermudan and callable bond options, accrual swaps and accrual range notes.

Keywords: Option pricing, interest-rate derivatives, affine models, fourier space time-stepping, accrual swaps, range notes

JEL Classification: G12, G13, C63

Suggested Citation

Jaimungal, Sebastian and Surkov, Vladimir, Valuing Early Exercise Interest Rate Options with Multi-Factor Affine Models (October 30, 2012). Jaimungal, Sebastian, and Vladimir Surkov. "Valuing Early-Exercise Interest-Rate Options With Multi-Factor Affine Models." International Journal of Theoretical and Applied Finance 16.06 (2013)., Available at SSRN: https://ssrn.com/abstract=1562638 or http://dx.doi.org/10.2139/ssrn.1562638

Sebastian Jaimungal

University of Toronto - Department of Statistics ( email )

100 St. George St.
Toronto, Ontario M5S 3G3
Canada

HOME PAGE: http://http:/sebastian.statistics.utoronto.ca

Vladimir Surkov (Contact Author)

RBC Capital Markets ( email )

New York, NY
United States

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