We investigate the rate of convergence of the direct-simulation estimator $\hat{x}$ of a large quantile $x_p$ of the Pareto and Gamma distributions. The upper bound of the probability $P \{| \hat{x_p}(n) - x_p | \geq \epsilon \}$ is determined.