Publication | Open Access
Coupling for Ornstein–Uhlenbeck processes with jumps
44
Citations
19
References
2011
Year
Markov Transition ProbabilityEngineeringPhysicsNatural SciencesIntegrable ProbabilityStochastic ProcessesStochastic CalculusTransition SemigroupStochastic Dynamical SystemMarkov KernelStochastic AnalysisProbability TheoryLevy ProcessLévy MeasureJump Diffusions
Consider the linear stochastic differential equation (SDE) on $ℝ^n$: $$\mathrm{d}X_t = AX_t \mathrm{d}t + B \mathrm{d}L_t,$$ where $A$ is a real $n × n$ matrix, $B$ is a real $n × d$ real matrix and $L_t$ is a Lévy process with Lévy measure $ν$ on $ℝ^d$. Assume that $ν(\mathrm{d}z) ≥ ρ_0(z)\mathrm{d}z$ for some ${ρ_0} \geq 0$. If $A \leq 0$, Rank$(B) = n$ and $∫_{\{|z−z_0| \leq ε\}}ρ_0(z)^{−1} \mathrm{d}z< \infty$ holds for some $z_0 ∈ ℝ^d$ and some $ε > 0$, then the associated Markov transition probability $P_t(x, \mathrm{d}y)$ satisfies $$‖P_t(x, ⋅) − P_t(y, ⋅)‖_{\mathrm{var}} \le \frac{C(1 + |x − y|)}{√t}, x, y ∈ ℝ^d, t > 0,$$ for some constant $C > 0$, which is sharp for large $t$ and implies that the process has successful couplings. The Harnack inequality, ultracontractivity and the strong Feller property are also investigated for the (conditional) transition semigroup.
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