Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach-Reference-Cited by-同舟云学术

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Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach

Published:2019-04-11 Issue:8 Volume:19 Page:1255-1266
ISSN:1469-7688
Container-title:Quantitative Finance
language:en
Short-container-title:Quantitative Finance

Author:

Bee M.¹^ORCID,Hambuckers J.²³,Trapin L.⁴

Affiliation:

1. Department of Economics and Management, University of Trento, Trento, Italy

2. Department of Finance, HEC Liège, University of Liège, Liège, Belgium

3. Chair of Statistics, Faculty of Economics, University of Goettingen, Goettingen, Germany

4. Department of Economic Policy, Università Cattolica del Sacro Cuore, Milano, Italy

Funder

German Research Foundation

Publisher

Informa UK Limited

Subject

General Economics, Econometrics and Finance,Finance

Link

https://www.tandfonline.com/doi/pdf/10.1080/14697688.2019.1580762

Reference20 articles.

1. A simple approach to the estimation of Tukey's gh distribution

2. Revisiting the Edge, Ten Years On

3. Fundamental Aspects of Operational Risk and Insurance Analytics

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1. Some analytical results on bivariate stable distributions with an application in operational risk;Quantitative Finance;2022-03-24

2. The truncated g-and-h distribution: estimation and application to loss modeling;Computational Statistics;2022-01-04

3. Modeling multivariate operational losses via copula-based distributions with g-and-h marginals;The Journal of Operational Risk;2022

4. Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach;Computational Statistics;2021-02-08

5. Estimating large losses in insurance analytics and operational risk using the g-and-h distribution;Quantitative Finance;2021-02-04

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