AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES

Guangwu Liu; Wen Shi; Kun Zhang

doi:10.1109/WSC40007.2019.9004921

AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES

Guangwu Liu
, Wen Shi
, Kun Zhang

College of Business

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

Coherent risk measures have received increasing attention in recent years among both researchers and practitioners. The problem of estimating a coherent risk measure can be cast as estimating the maximum expected loss taken under a set of probability measures. In this paper, we consider the set of probability measures is finite, and study the estimation of a coherent risk measure via an upper confidence bound (UCB) approach, where samples of the portfolio loss are simulated sequentially from one of the probability measures. We study in depth the so-called Grand Average estimator, and establish statistical guarantees, including its strong consistency, asymptotic normality, and asymptotic mean squared error. We also construct asymptotically valid confidence intervals.

Original language	English
Title of host publication	Proceedings of the 2019 Winter Simulation Conference
Publisher	IEEE
Pages	914-925
ISBN (Electronic)	978-1-7281-3283-9
DOIs	https://doi.org/10.1109/WSC40007.2019.9004921
Publication status	Published - Dec 2019
Event	2019 Winter Simulation Conference, WSC 2019 - National Harbor, United States Duration: 8 Dec 2019 → 11 Dec 2019

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2019-December
ISSN (Print)	0891-7736

Conference

Conference	2019 Winter Simulation Conference, WSC 2019
Place	United States
City	National Harbor
Period	8/12/19 → 11/12/19

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10.1109/WSC40007.2019.9004921

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@inproceedings{cd7374e61cd842a0b45af93ff5a2212f,

title = "AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES",

abstract = "Coherent risk measures have received increasing attention in recent years among both researchers and practitioners. The problem of estimating a coherent risk measure can be cast as estimating the maximum expected loss taken under a set of probability measures. In this paper, we consider the set of probability measures is finite, and study the estimation of a coherent risk measure via an upper confidence bound (UCB) approach, where samples of the portfolio loss are simulated sequentially from one of the probability measures. We study in depth the so-called Grand Average estimator, and establish statistical guarantees, including its strong consistency, asymptotic normality, and asymptotic mean squared error. We also construct asymptotically valid confidence intervals.",

author = "Guangwu Liu and Wen Shi and Kun Zhang",

year = "2019",

month = dec,

doi = "10.1109/WSC40007.2019.9004921",

language = "English",

series = "Proceedings - Winter Simulation Conference",

publisher = "IEEE",

pages = "914--925",

booktitle = "Proceedings of the 2019 Winter Simulation Conference",

address = "United States",

note = "2019 Winter Simulation Conference, WSC 2019 ; Conference date: 08-12-2019 Through 11-12-2019",

}

Liu, G, Shi, W & Zhang, K 2019, AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES. in Proceedings of the 2019 Winter Simulation Conference., 9004921, Proceedings - Winter Simulation Conference, vol. 2019-December, IEEE, pp. 914-925, 2019 Winter Simulation Conference, WSC 2019, National Harbor, United States, 8/12/19. https://doi.org/10.1109/WSC40007.2019.9004921

AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES. / Liu, Guangwu; Shi, Wen; Zhang, Kun.
Proceedings of the 2019 Winter Simulation Conference. IEEE, 2019. p. 914-925 9004921 (Proceedings - Winter Simulation Conference; Vol. 2019-December).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES

AU - Liu, Guangwu

AU - Shi, Wen

AU - Zhang, Kun

PY - 2019/12

Y1 - 2019/12

N2 - Coherent risk measures have received increasing attention in recent years among both researchers and practitioners. The problem of estimating a coherent risk measure can be cast as estimating the maximum expected loss taken under a set of probability measures. In this paper, we consider the set of probability measures is finite, and study the estimation of a coherent risk measure via an upper confidence bound (UCB) approach, where samples of the portfolio loss are simulated sequentially from one of the probability measures. We study in depth the so-called Grand Average estimator, and establish statistical guarantees, including its strong consistency, asymptotic normality, and asymptotic mean squared error. We also construct asymptotically valid confidence intervals.

AB - Coherent risk measures have received increasing attention in recent years among both researchers and practitioners. The problem of estimating a coherent risk measure can be cast as estimating the maximum expected loss taken under a set of probability measures. In this paper, we consider the set of probability measures is finite, and study the estimation of a coherent risk measure via an upper confidence bound (UCB) approach, where samples of the portfolio loss are simulated sequentially from one of the probability measures. We study in depth the so-called Grand Average estimator, and establish statistical guarantees, including its strong consistency, asymptotic normality, and asymptotic mean squared error. We also construct asymptotically valid confidence intervals.

UR - https://www.scopus.com/pages/publications/85081131076

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85081131076&origin=recordpage

U2 - 10.1109/WSC40007.2019.9004921

DO - 10.1109/WSC40007.2019.9004921

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - Proceedings - Winter Simulation Conference

SP - 914

EP - 925

BT - Proceedings of the 2019 Winter Simulation Conference

PB - IEEE

T2 - 2019 Winter Simulation Conference, WSC 2019

Y2 - 8 December 2019 through 11 December 2019

ER -

AN UPPER CONFIDENCE BOUND APPROACH TO ESTIMATING COHERENT RISK MEASURES

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