Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns


Autoria(s): Moralles, Herick Fernando; Rebelatto, Daisy Aparecida do Nascimento; Sartoris, Alexandre
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/11/2013

Resumo

Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

Formato

1648-1658

Identificador

http://dx.doi.org/10.1016/j.mcm.2013.07.002

Mathematical and Computer Modelling, v. 58, n. 9-10, p. 1648-1658, 2013.

0895-7177

http://hdl.handle.net/11449/76900

10.1016/j.mcm.2013.07.002

WOS:000325306700007

2-s2.0-84883557862

Idioma(s)

eng

Relação

Mathematical and Computer Modelling

Direitos

closedAccess

Palavras-Chave #Anderson-Darling #Goodness-of-fit tests #Kolmogorov-Smirnov #Parametric Value-at-Risk #Tails #Goodness-of-fit test #Value at Risk #Risk management #Value engineering #Parameter estimation
Tipo

info:eu-repo/semantics/article