  Ito stochastic differential equation governs one-dimensional diffusive Markov
process. Geoelectrical signals measured in seismic areas can be considered as
the result of competitive and collective interactions among system elements.
The Ito equation may constitute a good macroscopic model of such phenomenon in
which microscopic interactions are adequately averaged. The present study shows
how to construct Ito model for a geoelectrical time series measured in a
seismic area of southern Italy. Our results reveal that Ito model describes
quite well the whole time series, but performs better when one considers
fragments of the data set with lower variability range (absent or rare large
fluctuations) . Our findings show that generally detrended geoelectrical time
series can be considered as an approximation of the Markov diffusion process.
