Machine learningMonte Carlo Methods

Longstaff-Schwartz Method

The Longstaff-Schwartz method (2001) is a Monte Carlo algorithm for pricing American options and Bermudan swaptions by approximating the optimal exercise boundary via least-squares regression. It has become the industry standard for pricing path-dependent derivatives where analytical solutions do not exist.

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Sources

  1. Longstaff, F. A., & Schwartz, E. S. (2001). Valuing American options by simulation: A simple least-squares approach. Review of Financial Studies, 14(1), 113-147. DOI: 10.1093/rfs/14.1.113
  2. Clements, D. J., & Minca, A. (2008). A simulation approach to estimating near-optimal valuation functions for Bermudan options. Journal of Computational Finance, 12(2), 73-96. link

Related methods

ScholarGateLongstaff-Schwartz Method (Longstaff-Schwartz Least-Squares Monte Carlo). Retrieved 2026-06-04 from https://scholargate.app/en/quantitative-finance/longstaff-schwartz-method