Least Square Regression Methods for Bermudan Derivatives and Systems of Functions

DOI10.1007/978-4-431-55489-9_3zbMath1408.91234OpenAlexW2101369416MaRDI QIDQ3463646

Yusuke Morimoto, Shigeo Kusuoka

Publication date: 19 January 2016

Published in: Advances in Mathematical Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-4-431-55489-9_3

zbMATH Keywords

Malliavin calculusoption pricingcomputational financeleast square regression methods

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Stopping times; optimal stopping problems; gambling theory (60G40) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (1)

Implicit American Monte Carlo methods for nonlinear functional of future portfolio value

Cites Work

• Unnamed Item
• Pricing Bermudan options by nonparametric regression: optimal rates of convergence for lower estimates
• Convex analysis and measurable multifunctions
• An analysis of a least squares regression method for American option pricing
• A quantization algorithm for solving multidimensional discrete-time optimal stopping problems
• A regression-based Monte Carlo method to solve backward stochastic differential equations
• Stochastic Mesh Methods for Hörmander Type Diffusion Processes
• Valuing American Options by Simulation: A Simple Least-Squares Approach

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