Abstract
The dynamics of generic stochastic Lotka-Volterra (discrete logistic) systems of the form is studied by computer simulations. The variables are the individual system components and is their average. The parameters and are constants, while is randomly chosen at each time step from a given distribution. Models of this type describe the temporal evolution of a large variety of systems such as stock markets and city populations. These systems are characterized by a large number of interacting objects and the dynamics is dominated by multiplicative processes. The instantaneous probability distribution of the system components turns out to fulfill a Pareto power law The time evolution of presents intermittent fluctuations parametrized by a Lévy-stable distribution with the same index showing an intricate relation between the distribution of the at a given time and the temporal fluctuations of their average.
- Received 26 February 1998
DOI:https://doi.org/10.1103/PhysRevE.58.1352
©1998 American Physical Society