The Longstaff--Schwartz algorithm for L\'evy models: Results on fast and slow convergence
Abstract
We investigate the Longstaff--Schwartz algorithm for American option pricing assuming that both the number of regressors and the number of Monte Carlo paths tend to infinity. Our main results concern extensions, respectively, applications of results by Glasserman and Yu [Ann. Appl. Probab. 14 (2004) 2090--2119] and Stentoft [Manag. Sci. 50 (2004) 1193--1203] to several L\'evy models, in particular the geometric Meixner model. A convenient setting to analyze this convergence problem is provided by the L\'evy--Sheffer systems introduced by Schoutens and Teugels.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.