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A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection

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  • Jiang, Cuixia
  • Ding, Xiaoyi
  • Xu, Qifa
  • Tong, Yongbo

Abstract

This paper develops a novel time-varying multivariate Copula-MIDAS-GARCH (TVM-Copula-MIDAS-GARCH) model with exogenous explanatory variables to model the joint distribution of returns. The model accounts for mixed frequency factors that affect the time-varying dependence structure of financial assets. Furthermore, we examine the effectiveness of the proposed model in VaR-based portfolio selection. We conduct an empirical analysis on estimating the 90%, 95%, 99% VaRs of the portfolio constituted of the Shanghai Composite Index, Shanghai SE Fund Index, and Shanghai SE Treasury Bond Index. The empirical results show that the proposed TVM-Copula-MIDAS-GARCH model is effective to investigate the nonlinear time-varying dependence among those three indices and performs better in portfolio selection.

Suggested Citation

  • Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:ecofin:v:51:y:2020:i:c:s1062940819300993
    DOI: 10.1016/j.najef.2019.101074
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    4. Lyu, Yongjian & Qin, Fanshu & Ke, Rui & Yang, Mo & Chang, Jianing, 2024. "Forecasting the VaR of the crude oil market: A combination of mixed data sampling and extreme value theory," Energy Economics, Elsevier, vol. 133(C).
    5. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yu, Keming, 2020. "Mixed data sampling expectile regression with applications to measuring financial risk," Economic Modelling, Elsevier, vol. 91(C), pages 469-486.
    6. Dodo Natatou Moutari & Hassane Abba Mallam & Diakarya Barro & Bisso Saley, 2021. "Dependence Modeling and Risk Assessment of a Financial Portfolio with ARMA-APARCH-EVT models based on HACs," Papers 2105.09473, arXiv.org.

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