Non-nested estimators for the central moments of a conditional expectation and their convergence properties

DOI10.1016/j.orl.2021.06.012OpenAlexW3174854297MaRDI QIDQ2060336

Hong-Fa Cheng, Kun Zhang

Publication date: 13 December 2021

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.orl.2021.06.012

zbMATH Keywords

convergence ratecentral limit theoremscentral momentsnested simulationnon-nested estimation

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Related Items (1)

Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement

Cites Work

• Unnamed Item
• Computing the variance of a conditional expectation via non-nested Monte Carlo
• Risk Estimation via Regression
• Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation
• Nested Simulation in Portfolio Risk Measurement
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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