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Distortion Risk Measures Under Skew Normal Settings

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Econometrics of Risk

Part of the book series: Studies in Computational Intelligence ((SCI,volume 583))

Abstract

Coherent distortion risk measure is needed in the actuarial and financial fields in order to provide incentive for active risk management. The purpose of this study is to propose extended versions of Wang transform using skew normal distribution functions. The main results show that the extended version of skew normal distortion risk measure is coherent and its transform satisfies the classic capital asset pricing model. Properties of the stock price model under log-skewnormal and its transform are also studied. A simulation based on the skew normal transforms is given for a insurance payoff function.

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Acknowledgments

The authors would like to thank Ying Wang for proofreading of this paper and anonymous referees for their valuable comments which let the improvement of this paper.

Author information

Authors and Affiliations

  1. Department Mathematical Sciences, New Mexico State University, Las Cruces, USA

    Weizhong Tian & Tonghui Wang

  2. Innovation Experimental College, Northwest A and F University, Xianyang, China

    Tonghui Wang

  3. College of Science, Donghua University, Shanghai, China

    Liangjian Hu

  4. Tan Tao University, Long An, Vietnam

    Hien D. Tran

Authors
  1. Weizhong Tian
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  2. Tonghui Wang
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  3. Liangjian Hu
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  4. Hien D. Tran
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Corresponding author

Correspondence to Tonghui Wang .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Van-Nam Huynh

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  3. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  4. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Komsan Suriya

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Tian, W., Wang, T., Hu, L., Tran, H.D. (2015). Distortion Risk Measures Under Skew Normal Settings. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S., Suriya, K. (eds) Econometrics of Risk. Studies in Computational Intelligence, vol 583. Springer, Cham. https://doi.org/10.1007/978-3-319-13449-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-13449-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13448-2

  • Online ISBN: 978-3-319-13449-9

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