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

Hong Zhang; Li Zhou; Jian Guo

doi:doi:10.11648/j.acm.20150403.13

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

Hong Zhang, Li Zhou, Jian Guo

Published in Applied and Computational Mathematics (Volume 4, Issue 3)

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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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

Hong Zhang

School of Information, Beijing Wuzi University, Beijing, China
Li Zhou

School of Information, Beijing Wuzi University, Beijing, China
Jian Guo

School of Information, Beijing Wuzi University, Beijing, China

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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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download