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arxiv: math/0503527 · v1 · submitted 2005-03-24 · 🧮 math.PR

Tail of a linear diffusion with Markov switching

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keywords taildiffusionmarkovstationarybeencasecharacterizationconditions
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Let Y be an Ornstein-Uhlenbeck diffusion governed by a stationary and ergodic Markov jump process X: dY_t=a(X_t)Y_t dt+\sigma(X_t) dW_t, Y_0=y_0. Ergodicity conditions for Y have been obtained. Here we investigate the tail propriety of the stationary distribution of this model. A characterization of either heavy or light tail case is established. The method is based on a renewal theorem for systems of equations with distributions on R.

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