Snapshot article demonstrates efficient pricing of American options in a geometric Brownian motion model.
Quickly apply original, key PMR-published papers with Snapshots—a short article companion that distills PMR research into compressed, digestible takeaways, so you can put the paper’s core ideas to work in your investment process—fast. This Snapshot article is based on research arguing that a semi-analytical generalized integral transform (GIT) framework can accurately and efficiently price American options with continuous, discrete cash and proportional dividends within a time-inhomogeneous geometric Brownian motion (GBM) setting.
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Derived from original PMR research written by Mohamed Rochdi Keffala and Achaf Ben Abdallah using AI and an editor (2026) studied this question.
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