  We develop a scale-invariant truncated L\'evy (STL) process to describe
physical systems characterized by correlated stochastic variables. The STL
process exhibits L\'evy stability for the probability density, and hence shows
scaling properties (as observed in empirical data); it has the advantage that
all moments are finite (and so accounts for the empirical scaling of the
moments). To test the potential utility of the STL process, we analyze
financial data.
