Linear diffusion with stationary switching regime

Xavier Guyon; Serge Iovleff; Jian-Feng Yao

ESAIM: Probability and Statistics (2010)

  • Volume: 8, page 25-35
  • ISSN: 1292-8100

Abstract

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Let Y be a Ornstein–Uhlenbeck diffusion governed by a stationary and ergodic process X : dYt = a(Xt)Ytdt + σ(Xt)dWt,Y0 = y0. We establish that under the condition α = Eµ(a(X0)) < 0 with μ the stationary distribution of the regime process X, the diffusion Y is ergodic. We also consider conditions for the existence of moments for the invariant law of Y when X is a Markov jump process having a finite number of states. Using results on random difference equations on one hand and the fact that conditionally to X, Y is Gaussian on the other hand, we give such a condition for the existence of the moment of order s ≥ 0. Actually we recover in this case a result that Basak et al. [J. Math. Anal. Appl. 202 (1996) 604–622] have established using the theory of stochastic control of linear systems.

How to cite

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Guyon, Xavier, Iovleff, Serge, and Yao, Jian-Feng. "Linear diffusion with stationary switching regime." ESAIM: Probability and Statistics 8 (2010): 25-35. <http://eudml.org/doc/104320>.

@article{Guyon2010,
abstract = { Let Y be a Ornstein–Uhlenbeck diffusion governed by a stationary and ergodic process X : dYt = a(Xt)Ytdt + σ(Xt)dWt,Y0 = y0. We establish that under the condition α = Eµ(a(X0)) < 0 with μ the stationary distribution of the regime process X, the diffusion Y is ergodic. We also consider conditions for the existence of moments for the invariant law of Y when X is a Markov jump process having a finite number of states. Using results on random difference equations on one hand and the fact that conditionally to X, Y is Gaussian on the other hand, we give such a condition for the existence of the moment of order s ≥ 0. Actually we recover in this case a result that Basak et al. [J. Math. Anal. Appl. 202 (1996) 604–622] have established using the theory of stochastic control of linear systems. },
author = {Guyon, Xavier, Iovleff, Serge, Yao, Jian-Feng},
journal = {ESAIM: Probability and Statistics},
keywords = {Ornstein–Uhlenbeck diffusion; Markov switching; jump process; random difference equations; ergodicity; existence of moments.; Ornstein-Uhlenbeck diffusion; jump process; ergodicity; existence of moments},
language = {eng},
month = {3},
pages = {25-35},
publisher = {EDP Sciences},
title = {Linear diffusion with stationary switching regime},
url = {http://eudml.org/doc/104320},
volume = {8},
year = {2010},
}

TY - JOUR
AU - Guyon, Xavier
AU - Iovleff, Serge
AU - Yao, Jian-Feng
TI - Linear diffusion with stationary switching regime
JO - ESAIM: Probability and Statistics
DA - 2010/3//
PB - EDP Sciences
VL - 8
SP - 25
EP - 35
AB - Let Y be a Ornstein–Uhlenbeck diffusion governed by a stationary and ergodic process X : dYt = a(Xt)Ytdt + σ(Xt)dWt,Y0 = y0. We establish that under the condition α = Eµ(a(X0)) < 0 with μ the stationary distribution of the regime process X, the diffusion Y is ergodic. We also consider conditions for the existence of moments for the invariant law of Y when X is a Markov jump process having a finite number of states. Using results on random difference equations on one hand and the fact that conditionally to X, Y is Gaussian on the other hand, we give such a condition for the existence of the moment of order s ≥ 0. Actually we recover in this case a result that Basak et al. [J. Math. Anal. Appl. 202 (1996) 604–622] have established using the theory of stochastic control of linear systems.
LA - eng
KW - Ornstein–Uhlenbeck diffusion; Markov switching; jump process; random difference equations; ergodicity; existence of moments.; Ornstein-Uhlenbeck diffusion; jump process; ergodicity; existence of moments
UR - http://eudml.org/doc/104320
ER -

References

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  12. Y. Ji and H.J. Chizeck, Controllability, stabilizability and continuous-time Markovian jump linear quadratic control. IEEE Trans. Automat. Control35 (1990) 777-788.  
  13. I. Karatzas and S.E. Shreve, Brownian Motion and Stochastic calculus, 2nd Ed. Springer, New York (1991).  
  14. M. Mariton,  Jump linear systems in Automatic Control. Dekker (1990).  
  15. R.E. McCullogh and R.S. Tsay, Statistical analysis of econometric times series via Markov switching models, J. Time Ser. Anal. 15 (1994) 523-539.  
  16. B. Øksendal, Stochastic Differential Equations, 5th Ed. Springer-Verlag, Berlin (1998).  
  17. J.F. Yao and J.G. Attali, On stability of nonlinear AR processes with Markov switching. Adv. Appl. Probab.32 (2000) 394-407.  

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