Tail of a linear diffusion with Markov switching
Probability
2007-05-23 v1
Abstract
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.
Cite
@article{arxiv.math/0503527,
title = {Tail of a linear diffusion with Markov switching},
author = {Benoite de Saporta and Jian-Feng Yao},
journal= {arXiv preprint arXiv:math/0503527},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/105051604000000828 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)