Efficient Monte Carlo simulation of security prices
type: Item
instance of: scholarly article
title: Efficient Monte Carlo simulation of security prices
zbMATH Open document ID: 0877.65099
author: Peter W. Glynn
author: Darrell Duffie
published in: The Annals of Applied Probability
publication date: 1997-11-27T00:00:00Z
review text: Monte Carlo simulation schemes for solving stochastic differential equations of Itô type are considered. The authors study first- and second-order schemes of approximation of the stochastic equation. The main result of the paper consists in determining the optimal tradeoff between the stepsize \(h\) of the scheme and the order of convergence \(k\). The tradeoff between increasing the number of time-intervals and increasing the number of simulations is resolved for first-order discretization schemes as well as for second- and higher-order schemes. The results are illustrated by a simple option pricing example, an application of Monte Carlo methods to an asset pricing problem in continuous time security prices.
Mathematics Subject Classification ID: 65C99
Mathematics Subject Classification ID: 65C05
Mathematics Subject Classification ID: 91G60
Mathematics Subject Classification ID: 60H10
zbMATH DE Number: 898161
zbMATH Keywords: finance
zbMATH Keywords: stochastic differential equations of Itô type
zbMATH Keywords: convergence
zbMATH Keywords: option pricing
zbMATH Keywords: Monte Carlo methods
zbMATH Keywords: security prices
reviewed by: I. Dimov
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aoap/1177004598
OpenAlex ID: W2017829019
DOI: 10.1214/AOAP/1177004598
description: scientific article; zbMATH DE number 898161