Convergence of a Least‐Squares Monte Carlo Algorithm for Bounded Approximating Sets
type: Item
instance of: scholarly article
title: Convergence of a Least‐Squares Monte Carlo Algorithm for Bounded Approximating Sets
zbMATH Open document ID: 1169.91346
DOI: 10.1080/13504860802516881
published in: Applied Mathematical Finance
publication date: 2009-09-13T00:00:00Z
Mathematics Subject Classification ID: 91B24
zbMATH DE Number: 5603426
zbMATH Keywords: least-squares Monte Carlo
zbMATH Keywords: Longstaff-Schwartz algorithm
zbMATH Keywords: American options
zbMATH Keywords: optimal stopping
zbMATH Keywords: statistical learning
author: Daniel Z. Zanger
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1080/13504860802516881
OpenAlex ID: W2083948485
cites work: An analysis of a least squares regression method for American option pricing
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cites work: Sphere packing numbers for subsets of the Boolean \(n\)-cube with bounded Vapnik-Chervonenkis dimension
cites work: Valuing American Options by Simulation: A Simple Least-Squares Approach
cites work: Convergence of stochastic processes
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description: scientific article