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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/76900
Title: 
Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns
Author(s): 
Institution: 
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
ISSN: 
0895-7177
Abstract: 
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.
Issue Date: 
1-Nov-2013
Citation: 
Mathematical and Computer Modelling, v. 58, n. 9-10, p. 1648-1658, 2013.
Time Duration: 
1648-1658
Keywords: 
  • 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
Source: 
http://dx.doi.org/10.1016/j.mcm.2013.07.002
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/76900
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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