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arxiv: 1111.1306 · v1 · pith:GLPFMQHOnew · submitted 2011-11-05 · 🌊 nlin.AO · physics.data-an

Herding model and 1/f noise

classification 🌊 nlin.AO physics.data-an
keywords herdingbetanoisenon-linearbehaviordifferentialequationsmicroscopic
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We provide evidence that for some values of the parameters a simple agent based model, describing herding behavior, yields signals with 1/f power spectral density. We derive a non-linear stochastic differential equation for the ratio of number of agents and show, that it has the form proposed earlier for modeling of 1/f^beta noise with different exponents beta. The non-linear terms in the transition probabilities, quantifying the herding behavior, are crucial to the appearance of 1/f noise. Thus, the herding dynamics can be seen as a microscopic explanation of the proposed non-linear stochastic differential equations generating signals with 1/f^beta spectrum. We also consider the possible feedback of macroscopic state on microscopic transition probabilities strengthening the non-linearity of equations and providing more opportunities in the modeling of processes exhibiting power-law statistics.

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