Open Access
2022 Persistence of heavy-tailed sample averages: principle of infinitely many big jumps
Ayan Bhattacharya, Zbigniew Palmowski, Bert Zwart
Author Affiliations +
Electron. J. Probab. 27: 1-25 (2022). DOI: 10.1214/22-EJP774

Abstract

We consider the sample average of a centered random walk in Rd with regularly varying step size distribution. For the first exit time from a compact convex set A not containing the origin, we show that its tail is of lognormal type. Moreover, we show that the typical way for a large exit time to occur is by having a number of jumps growing logarithmically in the scaling parameter.

Funding Statement

The research of AB and BZ is partially supported by Dutch Science foundation NWO VICI grant # 639.033.413. The research of AB and ZP is partially supported by Polish National Science Centre Grant # 2018/29/B/ST1/00756 (2019-2022).

Acknowledgement

The authors are thankful to Guido Janssen for an analytic computation which led to a correct guess of the proper normalization of Pn. The authors are thankful to a referee for valuable suggestions which improved the quality of the exposition.

Citation

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Ayan Bhattacharya. Zbigniew Palmowski. Bert Zwart. "Persistence of heavy-tailed sample averages: principle of infinitely many big jumps." Electron. J. Probab. 27 1 - 25, 2022. https://doi.org/10.1214/22-EJP774

Information

Received: 30 March 2021; Accepted: 3 April 2022; Published: 2022
First available in Project Euclid: 27 April 2022

MathSciNet: MR4416674
zbMATH: 1493.60010
Digital Object Identifier: 10.1214/22-EJP774

Subjects:
Primary: 60F99 , 60G10 , 60G18 , 60G50 , 60G52 , 60K35 , 60K40
Secondary: 60J80

Keywords: heavy-tailed distribution , large deviation , persistency , Random walk , regular variation

Vol.27 • 2022
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