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Interacting discrete Markov processes with power-law probability distributions

During recent years there has been growing interest in the occurrence of long-tailed distributions, also known as heavy-tailed or fat-tailed distributions, which can exhibit power-law behaviour and often characterise physical systems that undergo very large fluctuations. In this paper we show that the interaction between two discrete Markov processes naturally generates a time-series characterised by such a distribution. This possibility is first demonstrated by numerical simulation and then confirmed by a mathematical analysis that enables the parameter range over which the power-law occurs to be quantified. The results are supported by comparison of numerical results with theoretical predictions and general conclusions are drawn regarding mechanisms that can cause this behaviour.