Applications of generalized likelihood ratio method to distribution sensitivities and steady-state simulation

L Lei, Y Peng, MC Fu, JQ Hu - Discrete Event Dynamic Systems, 2018 - Springer
We provide applications of the generalized likelihood ratio (GLR) method proposed in Peng
et al.(2016c) to distribution sensitivity estimation for both finite-horizon and steady-state …

On the asymptotic analysis of quantile sensitivity estimation by Monte Carlo simulation

Y Peng, MC Fu, PW Glynn, J Hu - 2017 Winter Simulation …, 2017 - ieeexplore.ieee.org
We provide a unified framework to treat the asymptotic analysis for the non-batched quantile
sensitivity estimators of Fu et al.(2009), Liu and Hong (2009), and Lei et al.(2017). With only …

Estimating quantile sensitivity for financial models with correlations and jumps

Y Peng, MC Fu, JQ Hu, L Lei - 2019 Winter Simulation …, 2019 - ieeexplore.ieee.org
We apply a generalized likelihood ratio (GLR) derivative estimation method in previous
works to estimate quantile sensitivity of financial models with correlations and jumps …

Sensitivity analysis of ranked data: from order statistics to quantiles

W Volk-Makarewicz, B Heidergott - Discrete Event Dynamic Systems, 2015 - Springer
In this paper we provide the mathematical theory for sensitivity analysis of order statistics of
continuous random variables, where the sensitivity is with respect to a distributional …

[PDF][PDF] ON THE ASYMPTOTIC ANALYSIS OF QUANTILE SENSITIVITY ESTIMATION BY MONTE CARLO SIMULATION

WKV Chan, A D'Ambrogio, G Zacharewicz, N Mustafee… - stanford.edu
We provide a unified framework to treat the asymptotic analysis for the non-batched quantile
sensitivity estimators of Fu et al.(2009), Liu and Hong (2009), and Lei et al.(2017). With only …