On the rates of convergence of simulation-based optimization algorithms for optimal stopping problems

DOI10.1214/10-AAP692zbMath1234.60043arXiv0909.3570MaRDI QIDQ627243

Denis Belomestny

Publication date: 21 February 2011

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0909.3570

zbMATH Keywords

optimal stoppingempirical processesexponential inequalities\(\delta \)-entropy with bracketingsimulation-based algorithms

Mathematics Subject Classification ID

Discrete-time Markov processes on general state spaces (60J05) Stopping times; optimal stopping problems; gambling theory (60G40) Financial applications of other theories (91G80)

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Randomized Optimal Stopping Algorithms and Their Convergence Analysis ⋮ Deep optimal stopping ⋮ Pricing American options by exercise rate optimization ⋮ ON THE CONSISTENCY OF REGRESSION‐BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS ⋮ Solving high-dimensional optimal stopping problems using deep learning

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