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Correlation Analysis of Stock Market and Fund Market Based on M-Copula-EGARCH-M-GED Model

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  • Wang Ruihua
  • Wang Hongjun

    (School of Mathematics and Statistics, Xidian University, Xi’an, 710126, China)

Abstract

In this paper, M-Copula is used to analyze the correlation between Shanghai Composite Index and Shanghai Fund Index. By analyzing the characteristics of the logarithmic yields sequence of two samples, the marginal distribution model is established by using EGARCH-M-GED model. According to the correlation between two logarithmic yields sequence, the M-Copula model is selected to model its correlation structure, and its parameters are estimated by EM algorithm. Because M-Copula combines characteristics of different Copulas, it has more flexible distribution forms and more prominent ability to describe the fat tails and correlation characteristics of data, and more importantly, the effect is better than single Copula.

Suggested Citation

  • Wang Ruihua & Wang Hongjun, 2020. "Correlation Analysis of Stock Market and Fund Market Based on M-Copula-EGARCH-M-GED Model," Journal of Systems Science and Information, De Gruyter, vol. 8(3), pages 240-252, June.
  • Handle: RePEc:bpj:jossai:v:8:y:2020:i:3:p:240-252:n:3
    DOI: 10.21078/JSSI-2020-240-13
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    References listed on IDEAS

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    1. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
    2. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    3. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    4. Daniel Berg, 2009. "Copula goodness-of-fit testing: an overview and power comparison," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 675-701.
    5. Liu, Yan & Luger, Richard, 2009. "Efficient estimation of copula-GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2284-2297, April.
    6. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    7. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    8. Huang, Jen-Jsung & Lee, Kuo-Jung & Liang, Hueimei & Lin, Wei-Fu, 2009. "Estimating value at risk of portfolio by conditional copula-GARCH method," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 315-324, December.
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