Fluctuation properties of the Langevin equation including a multiplicative,
power-law noise and a quadratic potential are discussed. The noise has the Levy
stable distribution. If this distribution is truncated, the covariance can be
derived in the limit of large time; it falls exponentially. Covariance in the
stable case, studied for the Cauchy distribution, exhibits a weakly stretched
exponential shape and can be approximated by the simple exponential. The
dependence of that function on system parameters is determined. Then we
consider a dynamics which involves the above process and obey the generalised
Langevin equation, the same as for Gaussian case. The resulting distributions
possess power-law tails - that fall similarly to those for the driving noise -
whereas central parts can assume the Gaussian shape. Moreover, a process with
the covariance 1/t at large time is constructed and the corresponding dynamical
equation solved. Diffusion properties of systems for both covariances are
discussed.Comment: 12 pages, 7 figure