Corrected-Hill versus partially reduced-bias value-at-risk estimation

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Gomes, MI (Author) Other; Caeiro, F (Author) Other; Fernanda Figueiredo (Author) FEP; Henriques Rodrigues, L (Author) Other; Pestana, D (Author) Other

Journal

Title: Communications in Statistics Part B: Simulation and Computation

Vol. 49 No. 4

Pages: 867-885

ISSN: 0361-0918

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 2 Citations

Other information

Authenticus ID: P-00Q-5QR

DOI: 10.1080/03610918.2018.1489053

Abstract (EN): The value-at-risk (VaR) at a small level q, 0<q<1, is the size of the loss that occurs with a probability q. Semi-parametric partially reduced-bias (PRB) VaR-estimation procedures based on the mean-of-order-p of a set of k quotients of upper order statistics, with p any real number, are put forward. After the study of their asymptotic behavior, these PRB VaR-estimators are altogether compared with the classical ones for finite samples, through a large-scale Monte-Carlo simulation study. A brief application to financial log-returns is provided, as well as some final remarks. © 2019, © 2019 Taylor & Francis Group, LLC.

Language: English

Type (Professor's evaluation): Scientific