Shukai Chen, Zenghu Li
Published 2021-04-25Version 1
For general (1+1)-affine Markov processes, we prove the ergodicity and exponential ergodicity in total variation distances. Our methods follow the arguments of ergodic properties for L\'{e}vy-driven OU-processes and a coupling of CBI-processes constructed by stochastic equations driven by time-space noises. Then the strong Feller property is considered.
An inequality for a class of Markov processes
Affine processes on positive semidefinite d x d matrices have jumps of finite variation in dimension d > 1
Affine processes on symmetric cones
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