Empirical likelihood-based evaluations of value at risk models

Zheng Hong Wei*, Song Qiao Wen, Lixing ZHU

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Value at Risk (VaR) is a basic and very useful tool in measuring market risks. Numerous VaR models have been proposed in literature. Therefore, it is of great interest to evaluate the efficiency of these models, and to select the most appropriate one. In this paper, we shall propose to use the empirical likelihood approach to evaluate these models. Simulation results and real life examples show that the empirical likelihood method is more powerful and more robust than some of the asymptotic method available in literature.

Original languageEnglish
Pages (from-to)1995-2006
Number of pages12
JournalScience in China, Series A: Mathematics, Physics, Astronomy
Volume52
Issue number9
DOIs
Publication statusPublished - Sep 2009

Scopus Subject Areas

  • Mathematics(all)

User-Defined Keywords

  • Empirical likelihood
  • Non-nested test
  • Specification test
  • Value at Risk
  • Volatility

Fingerprint

Dive into the research topics of 'Empirical likelihood-based evaluations of value at risk models'. Together they form a unique fingerprint.

Cite this