Open Access
October 2020 Parameter and dimension dependence of convergence rates to stationarity for reflecting Brownian motions
Sayan Banerjee, Amarjit Budhiraja
Ann. Appl. Probab. 30(5): 2005-2029 (October 2020). DOI: 10.1214/19-AAP1550

Abstract

We obtain rates of convergence to stationarity in $L^{1}$-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 $O(d^{4}(\log d)^{2})$ 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 $O(d^{6}(\log d)^{2})$.

Citation

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Sayan Banerjee. Amarjit Budhiraja. "Parameter and dimension dependence of convergence rates to stationarity for reflecting Brownian motions." Ann. Appl. Probab. 30 (5) 2005 - 2029, October 2020. https://doi.org/10.1214/19-AAP1550

Information

Received: 1 March 2019; Revised: 1 August 2019; Published: October 2020
First available in Project Euclid: 15 September 2020

MathSciNet: MR4149521
Digital Object Identifier: 10.1214/19-AAP1550

Subjects:
Primary: 60H10 , 60J60
Secondary: 60J55 , 60K25

Keywords: atlas model , coupling , heavy traffic , Local time , reflected Brownian motion , relaxation time , Wasserstein distance

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.30 • No. 5 • October 2020
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