Quantitative error estimates for a least-squares Monte Carlo algorithm for American option pricing

Abstract

We prove new error estimates for the Longstaff–Schwartz algorithm. We establish an O(log 1 2 (N)N− 2 ) convergence rate for the expected L2 sample error of this algorithm (where N is the number of Monte Carlo sample paths), whenever the approximation architecture of the algorithm is an arbitrary set of L2 functions with finite Vapnik–Chervonenkis dimension… (More)
DOI: 10.1007/s00780-013-0204-9

Topics

Cite this paper

@article{Zanger2013QuantitativeEE, title={Quantitative error estimates for a least-squares Monte Carlo algorithm for American option pricing}, author={Daniel Z. Zanger}, journal={Finance and Stochastics}, year={2013}, volume={17}, pages={503-534} }