×

Invariant measures and Euler-Maruyama’s approximations of state-dependent regime-switching diffusions. (English) Zbl 1409.60123

Summary: Regime-switching processes contain two components: continuous component and discrete component, which can be used to describe a continuous dynamical system in a random environment. Such processes have many different properties other than general diffusion processes, and many more difficulties are needed to be overcome due to the intensive interaction between continuous and discrete components. In this work we give conditions for the existence and uniqueness of invariant measures for state-dependent regime-switching diffusion processes. Also, the strong convergence in the \(L^1\)-norm of a numerical approximation is established and its convergence rate is provided. A refined application of Skorokhod’s representation of jumping processes plays a substantial role in this work.

MSC:

60J60 Diffusion processes
65C30 Numerical solutions to stochastic differential and integral equations
60H30 Applications of stochastic analysis (to PDEs, etc.)

References:

[1] L. Ambrosio, N. Gigli, and G. Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures, Lectures in Math. ETH Zürich, Birkhäuser, Basel, 2005. · Zbl 1090.35002
[2] G.K. Basak, A. Bisi, and M.K. Ghosh, Stability of a random diffusion with linear drift, J. Math. Anal. Appl., 202 (1996), pp. 604–622. · Zbl 0856.93102
[3] G.K. Basak, A. Bisi, and M.K. Ghosh, Stability of a degenerate diffusions with state-dependent switching, J. Math. Anal. Appl., 240 (1999), pp. 219–248. · Zbl 0939.93038
[4] J. Bao and J. Shao, Permanence and extinction of regime-switching predator-prey models, SIAM J. Math. Anal., 48 (2016), pp. 725–739. · Zbl 1337.60147
[5] J. Bao, J. Shao, and C. Yuan, Approximation of invariant measures for regime-switching diffusions, Potential Anal., 44 (2016), pp. 707–727. · Zbl 1342.60087
[6] J. Bao, J. Shao, and C. Yuan, Invariant Measures for Path-Dependent Random Diffusions, preprint, arXiv:1706.05638, 2017.
[7] J. Bardet, H. Guerin, and F. Malrieu, Long time behavior of diffusions with Markov switching, ALEA Lat. Am. J. Probab. Math. Stat., 7 (2010), pp. 151–170. · Zbl 1276.60084
[8] M. Benaim, S. Le Borgne, F. Malrieu, and P.-A. Zitt, Quantitative ergodicity for some switched dynamical systems, Electron. Commun. Probab., 17 (2012), pp. 1–14. · Zbl 1347.60118
[9] M.-F. Chen, From Markov Chains to Non-Equilibrium Particle Systems, 2nd ed., World Scientific, Singapore, 2004. · Zbl 1078.60003
[10] M.-F. Chen and S. Li, Coupling methods for multidimensional diffusion processes, Ann. Probab., 17 (1989), pp. 151–177. · Zbl 0686.60083
[11] Z.Q. Chen and Z. Zhao, Potential theory for elliptic systems, Ann. Probab., 24 (1996), pp. 293–319. · Zbl 0854.60062
[12] B. Cloez and M. Hairer, Exponential ergodicity for Markov processes with random switching, Bernoulli, 21 (2015), pp. 505–536. · Zbl 1330.60094
[13] B. de Saporta and J.-F. Yao, Tail of linear diffusion with Markov switching, Ann. Appl. Probab., 15 (2005), pp. 992–1018. · Zbl 1064.60174
[14] N.H. Du, H.N. Dang, and G. Yin, Conditions for permanence and ergodicity of certain stochastic predator-prey models, J. Appl. Probab., 53 (2015), pp. 187–202. · Zbl 1338.34091
[15] M.D. Fragoso and O.L.V. Costa, A unified approach for stochastic and mean square stability of continuous-time linear systems with Markovian jumping parameters and additive disturbances, SIAM J. Control Optim., 44 (2005), pp. 1165–1191. · Zbl 1139.93037
[16] T. Hoang, G. Yin, and F. Xi, Numerical solutions of regime-switching jump diffusions, Appl. Math. Comput., 244 (2014), pp. 822–835. · Zbl 1335.60130
[17] T. Hou and J. Shao, Heavy Tail and Light Tail of Cox-Ingersoll-Ross Processes with Regime-Switching, preprint, arXiv:1709.01691, 2017.
[18] R.Z. Khasminskii, C. Zhu, and G. Yin, Stability of regime-switching diffusions, Stochastic Process. Appl. 117 (2007), pp. 1037–1051. · Zbl 1119.60065
[19] T. Lindvall and L.C.G. Rogers, Coupling of multidimensional diffusion processes, Ann. Probab., 14 (1986), pp. 860–872. · Zbl 0593.60076
[20] A.J. Majda and X. Tong, Geometric ergodicity for piecewise contracting processes with applications for tropical stochastic lattice models, Comm. Pure Appl. Math., 69 (2016), pp. 1110–1153. · Zbl 1346.86005
[21] X. Mao, Stabilization of continuous-time hybrid stochastic differential equations by discrete time feedback control, Automatica J. IFAC, 49 (2013), pp. 3677–3681. · Zbl 1315.93083
[22] X. Mao and C. Yuan, Stochastic Differential Equations with Markovian Switching, Imperial College Press, London, 2006. · Zbl 1126.60002
[23] X. Mao, C. Yuan, and G. Yin, Approximations of Euler-Maruyama type for stochastic differential equations with Markovian switching, under non-Lipschitz conditions, J. Comput. Appl. Math., 205 (2007), pp. 936–948. · Zbl 1121.65011
[24] D.H. Nguyen and G. Yin, Modeling and analysis of switching diffusion systems: Past-dependent switching with a countable state space, SIAM J. Control Optim., 54 (2016), pp. 2450–2477. · Zbl 1391.93199
[25] N. Ikeda and S. Watanabe, Stochastic Differential Equations and Diffusion Processes, North-Holland Math. Lib. 24, North-Holland, Amsterdam, 1981. · Zbl 0495.60005
[26] M. Pinsky and R. Pinsky, Transience recurrence and central limit theorem behavior for diffusions in random temporal environments, Ann. Probab., 21 (1993), pp. 433–452. · Zbl 0773.60076
[27] R. Pinsky and M. Scheutzow, Some remarks and examples concerning the transience and recurrence of random diffusions, Ann. Inst. Henri. Poincaré, 28 (1992), pp. 519–536. · Zbl 0766.60098
[28] J. Shao and F. Xi, Stability and recurrence of regime-switching diffusion processes, SIAM J. Control Optim., 52 (2014), pp. 3496–3516. · Zbl 1312.60094
[29] J. Shao, Criteria for transience and recurrence of regime-switching diffusion processes, Electron. J. Probab., 20 (2015), pp. 1–15. · Zbl 1327.60017
[30] J. Shao, Ergodicity of regime-switching diffusions in Wasserstein distances, Stochastic Process. Appl., 125 (2015), pp. 739–758. · Zbl 1322.60165
[31] J. Shao, Strong solutions and strong Feller properties for regime-switching diffusion processes in an infinite state space, SIAM J. Control Optim., 53 (2015), pp. 2462–2479. · Zbl 1321.60155
[32] J. Shao, Stabilization of regime-switching process by feedback control based on discrete time observations, SIAM J. Control Optim., 55 (2017), pp. 724–740. · Zbl 1360.60115
[33] A. Skorokhod, Asymptotic Methods in the Theory of Stochastic Differential Equations, AMS, Providence, RI, 1989. · Zbl 0695.60055
[34] F. Xi, Asymptotic properties of jump-diffusion processes with state-dependent switching, Stochastic Process. Appl., 119 (2009), pp. 2198–2221. · Zbl 1191.60091
[35] F. Xi and J. Shao, Successful couplings for diffusion processes with state-dependent switching, Sci. China Math., 56 (2013), pp. 2135–2144. · Zbl 1291.60163
[36] F. Xi and C. Zhu, On Feller and strong Feller properties and exponential ergodicity of regime-switching jump diffusion processes with countable regimes, SIAM J. Control Optim., 55 (2017), pp. 1789–1818. · Zbl 1366.60101
[37] G. Yin, X. Mao, C. Yuan, and D. Cao, Approximation methods for hybrid diffusion systems with state-dependent switching processes: Numerical algorithms and existence and uniqueness of solutions, SIAM J. Math. Anal., 41 (2010), pp. 2335–2352. · Zbl 1208.65019
[38] C. Yuan and X. Mao, Convergence of the Euler-Maruyama method for stochastic differential equations with Markovian switching, Math. Comput. Simulation, 64 (2004), pp. 223–235. · Zbl 1044.65007
[39] C. Yuan, X. Mao, and J. Lygeros, Stochastic hybrid delay population dynamics: Well-posed models and extinction, J. Biol. Dyn., 3 (2009), pp. 1–21. · Zbl 1155.92044
[40] G. Yin and F. Xi, Stability of regime-switching jump diffusions, SIAM J. Control Optim., 48 (2010), pp. 4525–4549. · Zbl 1210.60089
[41] G. Yin and C. Zhu, Hybrid Switching Diffusions: Properties and Applications, Stoch. Model. Appl. Probab. 63, Springer, New York, 2010. · Zbl 1279.60007
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.