Skip to main content

Research on the Relevance and VaR of GEM Market Based on Vine Copula

  • Conference paper
  • First Online:
Emerging Trends in Intelligent and Interactive Systems and Applications (IISA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1304))

  • 1089 Accesses

Abstract

This article selects the Standard & Poor’s GEM index (SPHKGEM), GEM Strategic Emerging Industries Index (SZSCSEII), the Growth Enterprise Market 50 Index (SZEXT50), the Growth Enterprise Market Fundamental Market Index (SZSCPMI) as the research objects from January 2, 2018 to December 2, 2019. Establish the C-Vine structure for 2018 and 2019 for the four indexes, and then establish the C-Vine structure for the overall yield, and measure the VaR of the asset portfolio that conforms to the C-Vine structure in 2018 and 2019. The results show that the GEM Strategic Emerging Industries Index is in a key node position among the four GEM indices, and it shows a high correlation with other indexes under the C-Vine structure. The GEM Strategic Emerging Industries Index.The VaR in 2019 combined with the SPHKGEM, the SZEXT50, and the SZSCPMI decreased compared with 2018. This is related to China’s continued implementation of a stable monetary policy, continuous promotion of the opening of the financial industry, the government’s encouragement of technology companies, and the development of high-tech industries.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Huang, J.J., et al.: Estimating value at risk of portfolio by conditional Copula-GARCH method. Insur. Math. Econ. 45(3), 315–324 (2009)

    Article  MathSciNet  Google Scholar 

  2. Zhou, Q., Chen, Z., Ming, R.: Copula-based grouped risk aggregation under mixed operation. Appl. Math. 61(1), 103–120 (2016). https://doi.org/10.1007/s10492-016-0124-z

    Article  MathSciNet  MATH  Google Scholar 

  3. Bo, L.: Application of VaR method based on GARCH model in Shanghai Stock Market. Times Finance (27), 250–251+253 (2013)

    Google Scholar 

  4. Lin, L., Qinglong, Z.: A comparative study of liquidity risk of different types of commercial banks–an empirical analysis based on the GARCH-VaR model. China Price 03, 50–53 (2020)

    Google Scholar 

  5. Zhao, Z., Li, B.: Comparison of Risk Measurement of my country’s Growth Enterprise Market Based on GARCH Models. Econ. Manage (3), 58–64 (2016)

    Google Scholar 

  6. Jilin, W., Erhua, Z.: Subprime mortgage crisis, market risk and the dependence of the stock market. World Econ. 33(03), 95–108 (2010)

    Google Scholar 

  7. Zhenya, L.: The impact of the New York stock market on China’s A-share market. Nankai Econ. Res. (03), 13–26 + 53 (2006)

    Google Scholar 

  8. Taihua, Y., Mingyu, C.: Time series analysis of shanghai stock index weekly return rate based on markov switching model. China Manage. Sci. 17(06), 33–38 (2009)

    Google Scholar 

  9. Bedford, T., Cooke, R.M.: Probability density decomposition for conditionally dependent random variables modeled by vines. Ann. Math. Artif. Intell. 32, 245–268 (2001)

    Article  MathSciNet  Google Scholar 

  10. Bedford, T., Vines, C.R.M.: A new graphical model for dependent random variable. Ann. Stat. 30(3), 1031–1068 (2002)

    MathSciNet  MATH  Google Scholar 

  11. Joe, H.: Families of m-Variate distributions with given margins and m(m−1)/2 BIvariate dependence parameters. Lect. Notes-Monogr. Ser. 28, 120–141 (1996)

    Article  MathSciNet  Google Scholar 

  12. Bangzheng, Z., Yu, W.: Research on the correlation of Shanghai Stock Exchange Index based on R_Vine Copula method. J. Beijing Inst. Technol. (Soc. Sci. Edn.) 17(03), 100–108 (2015)

    Google Scholar 

  13. Chao, H., Taihua, Y.: Risk analysis of exchange rate portfolio based on high-dimensional dynamic vine Copula. China Manage. Sci. 25(02), 10–20 (2017)

    Google Scholar 

  14. Zhiqiang, H., Meijuan, Z.: Research on the IPO underpricing system and IPO underpricing under the multi-partial t-Copula model: an empirical analysis based on the main board, small and medium-sized board and the GEM. Econ. Rev. 199(03), 150–162 (2016)

    Google Scholar 

  15. Zhengwu, B., Shuzhen, Z., Xuerui, Z.: Research on the correlation of my country’s capital market based on dynamic t-Copula model. Manage. Modernization 39(06), 5–7 (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhang Xin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Xin, Z., Yumei, Z. (2021). Research on the Relevance and VaR of GEM Market Based on Vine Copula. In: Tavana, M., Nedjah, N., Alhajj, R. (eds) Emerging Trends in Intelligent and Interactive Systems and Applications. IISA 2020. Advances in Intelligent Systems and Computing, vol 1304. Springer, Cham. https://doi.org/10.1007/978-3-030-63784-2_9

Download citation

Publish with us

Policies and ethics