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Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model

Received: 30 March 2015     Accepted: 16 April 2015     Published: 27 April 2015
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Abstract

This paper established the ARMA-GJR-AL model of dynamic risk VaR and CVaR measurement. Considering from aspects of the correlation and volatility and residual distribution characteristics, studying the dynamic risk measures of VaR and CVaR based on ARMA-GJR-AL model. Through empirical research, Risk prediction and accuracy of inspection are given of the Shanghai stock market and the New York stock market. And we study the effectiveness of the model. The results show that the dynamic risk measurement model based on AL distribution is more reasonable and applicability, so it can effectively measure risk.

Published in Applied and Computational Mathematics (Volume 4, Issue 3)
DOI 10.11648/j.acm.20150403.13
Page(s) 116-121
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

ARMA-GJR-AL Model, VaR, Financial Market Risk

References
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  • APA Style

    Hong Zhang, Li Zhou, Jian Guo. (2015). Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model. Applied and Computational Mathematics, 4(3), 116-121. https://doi.org/10.11648/j.acm.20150403.13

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    ACS Style

    Hong Zhang; Li Zhou; Jian Guo. Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model. Appl. Comput. Math. 2015, 4(3), 116-121. doi: 10.11648/j.acm.20150403.13

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    AMA Style

    Hong Zhang, Li Zhou, Jian Guo. Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model. Appl Comput Math. 2015;4(3):116-121. doi: 10.11648/j.acm.20150403.13

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  • @article{10.11648/j.acm.20150403.13,
      author = {Hong Zhang and Li Zhou and Jian Guo},
      title = {Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model},
      journal = {Applied and Computational Mathematics},
      volume = {4},
      number = {3},
      pages = {116-121},
      doi = {10.11648/j.acm.20150403.13},
      url = {https://doi.org/10.11648/j.acm.20150403.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20150403.13},
      abstract = {This paper established the ARMA-GJR-AL model of dynamic risk VaR and CVaR measurement. Considering from aspects of the correlation and volatility and residual distribution characteristics, studying the dynamic risk measures of VaR and CVaR based on ARMA-GJR-AL model. Through empirical research, Risk prediction and accuracy of inspection are given of the Shanghai stock market and the New York stock market. And we study the effectiveness of the model. The results show that the dynamic risk measurement model based on AL distribution is more reasonable and applicability, so it can effectively measure risk.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Study on Dynamic Risk Measurement Based on ARMA-GJR-AL Model
    AU  - Hong Zhang
    AU  - Li Zhou
    AU  - Jian Guo
    Y1  - 2015/04/27
    PY  - 2015
    N1  - https://doi.org/10.11648/j.acm.20150403.13
    DO  - 10.11648/j.acm.20150403.13
    T2  - Applied and Computational Mathematics
    JF  - Applied and Computational Mathematics
    JO  - Applied and Computational Mathematics
    SP  - 116
    EP  - 121
    PB  - Science Publishing Group
    SN  - 2328-5613
    UR  - https://doi.org/10.11648/j.acm.20150403.13
    AB  - This paper established the ARMA-GJR-AL model of dynamic risk VaR and CVaR measurement. Considering from aspects of the correlation and volatility and residual distribution characteristics, studying the dynamic risk measures of VaR and CVaR based on ARMA-GJR-AL model. Through empirical research, Risk prediction and accuracy of inspection are given of the Shanghai stock market and the New York stock market. And we study the effectiveness of the model. The results show that the dynamic risk measurement model based on AL distribution is more reasonable and applicability, so it can effectively measure risk.
    VL  - 4
    IS  - 3
    ER  - 

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Author Information
  • School of Information, Beijing Wuzi University, Beijing, China

  • School of Information, Beijing Wuzi University, Beijing, China

  • School of Information, Beijing Wuzi University, Beijing, China

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