How many inner simulations to compute conditional expectations with least-square Monte Carlo?

DOI10.1007/s11009-023-10038-xzbMath1517.65005arXiv2209.04153OpenAlexW4295159859MaRDI QIDQ6176176

Jérôme Lelong, Aurélien Alfonsi, Bernard Lapeyre

Publication date: 25 July 2023

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2209.04153

zbMATH Keywords

variance reductionleast square Monte Carloconditional expectation estimators

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05)

Cites Work

• Unnamed Item
• Unnamed Item
• A distribution-free theory of nonparametric regression
• Multilevel Monte Carlo for computing the SCR with the standard formula and other stress tests
• Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations
• A regression-based Monte Carlo method to solve backward stochastic differential equations
• Risk Estimation via Regression
• On the Calculation of the Solvency Capital Requirement Based on Nested Simulations
• Nested Simulation in Portfolio Risk Measurement
• Regression Methods for Stochastic Control Problems and Their Convergence Analysis
• Valuing American Options by Simulation: A Simple Least-Squares Approach
• A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black–Scholes Partial Differential Equations

This page was built for publication: How many inner simulations to compute conditional expectations with least-square Monte Carlo?