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Numerical integration of mean reverting stochastic systems with applications to interest rate term structure simulation

Numerical integration of mean reverting stochastic systems with applications to interest rate... A proof of convergence is presented for a simplified numerical integration method for solving systems of correlated stochastic differential equations describing mean reverting geometric Brownian motion. Such systems arise in modelling the time evolution of interest rate term structures. For time discretization of size Δt, the method leads to global error in time of O (Δt 2) and no error accumulation. The result is shown to extend to the case when principal components analysis is used to reduce the number of underlying stochastic factors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Mathematical Finance Taylor & Francis

Numerical integration of mean reverting stochastic systems with applications to interest rate term structure simulation

Applied Mathematical Finance , Volume 6 (1): 10 – Mar 1, 1999
10 pages

Numerical integration of mean reverting stochastic systems with applications to interest rate term structure simulation

Abstract

A proof of convergence is presented for a simplified numerical integration method for solving systems of correlated stochastic differential equations describing mean reverting geometric Brownian motion. Such systems arise in modelling the time evolution of interest rate term structures. For time discretization of size Δt, the method leads to global error in time of O (Δt 2) and no error accumulation. The result is shown to extend to the case when principal components analysis is...
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Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1466-4313
eISSN
1350-486X
DOI
10.1080/135048699334591
Publisher site
See Article on Publisher Site

Abstract

A proof of convergence is presented for a simplified numerical integration method for solving systems of correlated stochastic differential equations describing mean reverting geometric Brownian motion. Such systems arise in modelling the time evolution of interest rate term structures. For time discretization of size Δt, the method leads to global error in time of O (Δt 2) and no error accumulation. The result is shown to extend to the case when principal components analysis is used to reduce the number of underlying stochastic factors.

Journal

Applied Mathematical FinanceTaylor & Francis

Published: Mar 1, 1999

Keywords: Numerical Integration; Stochastic Differential Systems; Mean Reversion; Term Structure; Simulation; Value-at-risk

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