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Empirical likelihood-based evaluations of Value at Risk models

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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.

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Authors and Affiliations

  1. College of Mathematics and Computational Science, Shenzhen University, Shenzhen, 518060, China

    ZhengHong Wei & SongQiao Wen

  2. Department of Mathematics, Hongkong Baptist University, Hong Kong, China

    ZhengHong Wei, SongQiao Wen & LiXing Zhu

Authors
  1. ZhengHong Wei
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  2. SongQiao Wen
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  3. LiXing Zhu
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Corresponding author

Correspondence to ZhengHong Wei.

Additional information

The work was supported by Guangdong Natural Science Foundation (Grant No. 2008276) and a grant from the Research Grants Council of Hong Kong, China

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Wei, Z., Wen, S. & Zhu, L. Empirical likelihood-based evaluations of Value at Risk models. Sci. China Ser. A-Math. 52, 1995–2006 (2009). https://doi.org/10.1007/s11425-009-0050-6

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  • DOI: https://doi.org/10.1007/s11425-009-0050-6

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