  The statistical properties of the return intervals $\tau_q$ between
successive 1-min volatilities of 30 liquid Chinese stocks exceeding a certain
threshold $q$ are carefully studied. The Kolmogorov-Smirnov (KS) test shows
that 12 stocks exhibit scaling behaviors in the distributions of $\tau_q$ for
different thresholds $q$. Furthermore, the KS test and weighted KS test shows
that the scaled return interval distributions of 6 stocks (out of the 12
stocks) can be nicely fitted by a stretched exponential function
$f(\tau/\bar{\tau})\sim e^{- \alpha (\tau/\bar{\tau})^{\gamma}}$ with
$\gamma\approx0.31$ under the significance level of 5%, where $\bar{\tau}$ is
the mean return interval. The investigation of the conditional probability
distribution $P_q(\tau | \tau_0)$ and the mean conditional return interval
$<\tau| \tau_0>$ demonstrates the existence of short-term correlation between
successive return interval intervals. We further study the mean return interval
$<\tau| \tau_0>$ after a cluster of $n$ intervals and the fluctuation $F(l)$
using detrended fluctuation analysis and find that long-term memory also exists
in the volatility return intervals.
