PARAMETER AND DIMENSION DEPENDENCE OF CONVERGENCE RATES TO STATIONARITY FOR REFLECTING BROWNIAN MOTIONS

We obtain rates of convergence to stationarity in L¹-Wasserstein distance for a d-dimensional reflected Brownian motion (RBM) in the nonnegative orthant that are explicit in the dimension and the system parameters. The results are then applied to a class of RBMs considered in (Blanchet and Xinyun (2...

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Bibliographic Details
Published in:The Annals of applied probability 2020-10, Vol.30 (5), p.2005-2029
Main Authors: Banerjee, Sayan, Budhiraja, Amarjit
Format: Article
Language:English
Subjects:
Brownian motion
Convergence
Mathematical models
Parameter estimation
Parameters
Relaxation time
Stochastic models
Online Access:Get full text
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Summary:We obtain rates of convergence to stationarity in L¹-Wasserstein distance for a d-dimensional reflected Brownian motion (RBM) in the nonnegative orthant that are explicit in the dimension and the system parameters. The results are then applied to a class of RBMs considered in (Blanchet and Xinyun (2016)) and to rank-based diffusions including the Atlas model. In both cases, we obtain explicit rates and bounds on relaxation times. In the first case we improve the relaxation time estimates of O(d⁴(log d)²) obtained in (Blanchet and Xinyun (2016)) to O((log d)²). In the latter case, we give the first results on explicit parameter and dimension dependent rates under the Wasserstein distance. The proofs do not require an explicit form for the stationary measure or reversibility of the process with respect to this measure, and cover settings where these properties are not available. In the special case of the standard Atlas model (In Stochastic Portfolio Theory (2002) 1–24 Springer), we obtain a bound on the relaxation time of O(d⁶(log d)²).
ISSN:1050-5164
2168-8737
DOI:10.1214/19-AAP1550