  This paper proves a Berry--Esseen theorem for sample quantiles of
strongly-mixing random variables under a polynomial mixing rate. The rate of
normal approximation is shown to be $O(n^{-1/2})$ as $n\to\infty$, where $n$
denotes the sample size. This result is in sharp contrast to the case of the
sample mean of strongly-mixing random variables where the rate $O(n^{-1/2})$ is
not known even under an exponential strong mixing rate. The main result of the
paper has applications in finance and econometrics as financial time series
data often are heavy-tailed and quantile based methods play an important role
in various problems in finance, including hedging and risk management.
