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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2020

Autores

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

Revista

Título: Communications in Statistics Part B: Simulation and Computation

Vol. 49 Nº 4

Páginas: 867-885

ISSN: 0361-0918

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 2 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica