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

Cuixia Jiang, Xiaoyi Ding, Qifa Xu and Yongbo Tong

The North American Journal of Economics and Finance, 2020, vol. 51, issue C

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.

Keywords: Time-varying multivariate copula; Mixed data sampling; MIDAS-Copula; GARCH; Portfolio; VaR (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.najef.2019.101074

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