Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement
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Publication:6066180
DOI10.1016/j.ejor.2023.07.040MaRDI QIDQ6066180
Xing Yan, Kun Zhang, Xiaoyu Liu
Publication date: 15 November 2023
Published in: European Journal of Operational Research (Search for Journal in Brave)
Cites Work
- Unnamed Item
- MCMC design-based non-parametric regression for rare event. application to nested risk computations
- New bandwidth selection for kernel quantile estimators
- Relative deficiency of kernel type estimators of quantiles
- Computing the variance of a conditional expectation via non-nested Monte Carlo
- Non-nested estimators for the central moments of a conditional expectation and their convergence properties
- Efficient estimation of a risk measure requiring two-stage simulation optimization
- Risk Estimation via Regression
- Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation
- A Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation
- A Confidence Interval Procedure for Expected Shortfall Risk Measurement via Two-Level Simulation
- Nested Simulation in Portfolio Risk Measurement
- Kernel Quantile Estimators
- Nonparametric Statistical Data Modeling
- Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement
- Technical Note—Bootstrap-based Budget Allocation for Nested Simulation
- Efficient Risk Estimation via Nested Sequential Simulation
- Technical note—Constructing confidence intervals for nested simulation