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stat.ME2026
Conditional Leibniz Derivative Estimation with an Application to American Call Min-Options
Xingyu Ren, Michael C. Fu, Pierre L'Ecuyer
Leibniz derivative estimation is a Monte Carlo technique for estimating derivatives of a discontinuous sample performance in stochastic models with respect to parameters of interes…
stat.ME2025
Stochastic Derivative Estimation for Discontinuous Sample Performances: A Leibniz Integration Perspective
Xingyu Ren, Michael C. Fu, Pierre L'Ecuyer
We develop a novel stochastic derivative estimation framework for sample performance functions that are discontinuous in the parameter of interest, based on the multidimensional Le…
stat.ME2025★ 1 cited
Generalizing the Generalized Likelihood Ratio Method Through a Push-Out Leibniz Integration Approach
Xingyu Ren, Michael C. Fu
We generalize the generalized likelihood ratio (GLR) method through a novel push-out Leibniz integration approach. Extending the conventional push-out likelihood ratio (LR) method,…