A STATE‐SPACE PARTITIONING METHOD FOR PRICING HIGH‐DIMENSIONAL AMERICAN‐STYLE OPTIONS

DOI10.1111/j.1467-9965.2007.00309.xzbMath1186.91216OpenAlexW1980858784MaRDI QIDQ5427663

Xing Jin, Junhua Sun, Hwee Huat Tan

Publication date: 21 November 2007

Published in: Mathematical Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9965.2007.00309.x

zbMATH Keywords

Monte Carlo simulationstate space partitioningquasi-Monte Carlo sequenceAmerican-style option

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (8)

Counterparty Credit Exposures for Interest Rate Derivatives using the Stochastic Grid Bundling Method ⋮ Pricing Surrender Risk in Ratchet Equity-Index Annuities under Regime-Switching Lévy Processes ⋮ Pricing Bermudan options using low-discrepancy mesh methods ⋮ The stochastic grid bundling method: efficient pricing of Bermudan options and their Greeks ⋮ Pricing high-dimensional Bermudan options using the stochastic grid method ⋮ Generic improvements to least squares Monte Carlo methods with applications to optimal stopping problems ⋮ ALGORITHMIC COUNTERPARTY CREDIT EXPOSURE FOR MULTI-ASSET BERMUDAN OPTIONS ⋮ A computationally efficient state-space partitioning approach to pricing high-dimensional American options via dimension reduction

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• Monte Carlo valuation of American options
• Valuing American Options by Simulation: A Simple Least-Squares Approach

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