  Quantile is an important risk measure quantifying the stochastic system
random behaviors. This paper studies a pooled quantile estimator, which is the
sample quantile of detailed simulation outputs after directly pooling
independent sample paths together. We derive the asymptotic representation of
the pooled quantile estimator and further prove its normality. By comparing
with the classical quantile estimator used in stochastic simulation, both
theoretical and empirical studies demonstrate the advantages of the proposal
under the context of parallel simulation.
