We consider the problem of pricing European interest rate derivatives based on the LIBOR Market Model (LMM) with one driving factor. We derive a closed-form approximation of the transition probability density functions associated to the stochastic dynamical systems that describe the behaviour of the forward LIBOR interest rates in the LMM. These approximate formulae are based on a truncated power series expansion of the solutions of the Fokker–Planck equations associated to the LMM. The approximate probability density functions obtained are used to price European interest rate derivatives using the method of discounted expectations. The resulting integrals are low dimensional when the most commonly traded European interest rate derivatives are considered, and they can be computed efficiently using elementary numerical quadrature schemes (i.e. Simpson’s rule). The algorithm obtained is very well suited for parallel computing and is tested on the problem of pricing several derivatives including an European swaption and an interest rate spread option. In both cases, the method proposed in this paper appears to be accurate (i.e. relative error of order 10−2, 10−3, or even 10−4) and approximately between 278 and 63 000 times faster than previous methods based on the Monte Carlo simulation of the LMM stochastic dynamical systems. The website http://www.econ.univpm.it/pacelli/ballestra/finance/w2 contains material that helps the understanding of this paper and makes available to the interested users the computer programs that implement the numerical method proposed.

" A numerical method to price European derivatives based on factor LIBOR Market Model of interest rates"

PACELLI, GRAZIELLA;
2008

Abstract

We consider the problem of pricing European interest rate derivatives based on the LIBOR Market Model (LMM) with one driving factor. We derive a closed-form approximation of the transition probability density functions associated to the stochastic dynamical systems that describe the behaviour of the forward LIBOR interest rates in the LMM. These approximate formulae are based on a truncated power series expansion of the solutions of the Fokker–Planck equations associated to the LMM. The approximate probability density functions obtained are used to price European interest rate derivatives using the method of discounted expectations. The resulting integrals are low dimensional when the most commonly traded European interest rate derivatives are considered, and they can be computed efficiently using elementary numerical quadrature schemes (i.e. Simpson’s rule). The algorithm obtained is very well suited for parallel computing and is tested on the problem of pricing several derivatives including an European swaption and an interest rate spread option. In both cases, the method proposed in this paper appears to be accurate (i.e. relative error of order 10−2, 10−3, or even 10−4) and approximately between 278 and 63 000 times faster than previous methods based on the Monte Carlo simulation of the LMM stochastic dynamical systems. The website http://www.econ.univpm.it/pacelli/ballestra/finance/w2 contains material that helps the understanding of this paper and makes available to the interested users the computer programs that implement the numerical method proposed.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/32059
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