Application of kernel-based stochastic gradient algorithms to option pricing

DOI10.1515/MCMA.2008.006zbMath1146.91003MaRDI QIDQ3516785

Kengy Barty, Cyrille Strugarek, Pierre Girardeau, Jean-Sébastien Roy

Publication date: 11 August 2008

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

zbMATH Keywords

American option pricingMonte Carlo methodsstochastic algorithmkernel approximation

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Research exposition (monographs, survey articles) pertaining to game theory, economics, and finance (91-02) Stochastic learning and adaptive control (93E35) Stopping times; optimal stopping problems; gambling theory (60G40) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items

Pricing of American options in discrete time using least squares estimates with complexity penalties, PRICING OF HIGH-DIMENSIONAL AMERICAN OPTIONS BY NEURAL NETWORKS, The residual-based ESG algorithm and its performance analysis

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