The University of Southampton
University of Southampton Institutional Repository

Convergence of the stochastic mesh estimator for pricing Bermudan options

Avramidis, A.N. and Matzinger, H. (2004) Convergence of the stochastic mesh estimator for pricing Bermudan options Journal of Computational Finance, 7, (4), pp. 73-91.

Record type: Article


Broadie and Glasserman (2004) proposed a Monte Carlo algorithm they named “stochastic mesh” for pricing high-dimensional Bermudan options. Based on simulated states of the assets underlying the option at each exercise opportunity, the method produces an estimator of the option value at each sampled state. We derive an asymptotic upper bound on the probability of error of the mesh estimator under the mild assumption of the finiteness of certain moments. Both the error size and the probability bound are functions that vanish with increasing sample size. Moreover, we report the mesh method’s empirical performance on test problems taken from the recent literature. We find that the mesh estimator has large positive bias that decays slowly with the sample size.

PDF mesh_JCF_Final.pdf - Other
Download (789kB)

More information

Published date: 2004
Organisations: Operational Research


Local EPrints ID: 48878
ISSN: 1460-1559
PURE UUID: fa2918ad-f7d7-4dd4-9e00-3a224541d4c2

Catalogue record

Date deposited: 17 Oct 2007
Last modified: 17 Jul 2017 14:57

Export record


Author: A.N. Avramidis
Author: H. Matzinger

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.