  The level crossing and inverse statistics analysis of DAX and oil price time
series are given. We determine the average frequency of positive-slope
crossings, $\nu_{\alpha}^+$, where $T_{\alpha} =1/\nu_{\alpha}^+ $ is the
average waiting time for observing the level $\alpha$ again. We estimate the
probability $P(K, \alpha)$, which provides us the probability of observing $K$
times of the level $\alpha$ with positive slope, in time scale $T_{\alpha}$.
For analyzed time series we found that maximum $K$ is about 6. We show that by
using the level crossing analysis one can estimate how the DAX and oil time
series will develop. We carry out same analysis for the increments of DAX and
oil price log-returns,(which is known as inverse statistics) and provide the
distribution of waiting times to observe some level for the increments.
