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Long time behavior of diffusions with Markov switching

Abstract

Let YY be an Ornstein-Uhlenbeck diffusion governed by an ergodic finite state Markov process XX: dYt=λ(Xt)Ytdt+σ(Xt)dBtdY_t=-\lambda(X_t)Y_tdt+\sigma(X_t)dB_t, Y0Y_0 given. Under ergodicity condition, we get quantitative estimates for the long time behavior of YY. We also establish a trichotomy for the tail of the stationary distribution of YY: it can be heavy (only some moments are finite), exponential-like (only some exponential moments are finite) or Gaussian-like (its Laplace transform is bounded below and above by Gaussian ones). The critical moments are characterized by the parameters of the model

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