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Long time behavior of diffusions with Markov switching
Jean-Baptiste Bardet 1, 2, Hélène Guerin 1, Florent Malrieu 1
(2009-12-16)

Let $Y$ be an Ornstein-Uhlenbeck diffusion governed by an ergodic finite state Markov process $X$: $dY_t=-\lambda(X_t)Y_tdt+\sigma(X_t)dB_t$, $Y_0$ given. Under ergodicity condition, we get quantitative estimates for the long time behavior of $Y$. We also establish a trichotomy for the tail of the stationary distribution of $Y$: 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.
1:  Institut de Recherche Mathématique de Rennes (IRMAR)
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
2:  Laboratoire de Mathématiques Raphaël Salem (LMRS)
CNRS : UMR6085 – Université de Rouen
Mathematics/Probability
Ornstein–Uhlenbeck diffusion – Markov switching – jump process – random difference equation – light tail – heavy tail – Laplace transform
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