目前,各个行业相依性变得越来越高,金融风险传染加剧,投资组合管理的重要性尤为突出。本文选择五家公司股票2019年1月1日~2023年6月1日的每日收盘价为研究对象,对数据进行处理后,选择t-Copula-GARCH模型,利用蒙特卡洛模拟方法对不同置...目前,各个行业相依性变得越来越高,金融风险传染加剧,投资组合管理的重要性尤为突出。本文选择五家公司股票2019年1月1日~2023年6月1日的每日收盘价为研究对象,对数据进行处理后,选择t-Copula-GARCH模型,利用蒙特卡洛模拟方法对不同置信水平下的投资组合风险价值VaR进行测度。结果表明,t-Copula GARCH模型具有刻画真实的金融资产分布的能力,不同资产之间相依关系是非对称的,在不同的置信水平下使用Copula函数构建的投资组合能显著降低投资风险。因此,基于本文的结论,建议考虑各行业间相依性的强弱以及相依结构的特点进行理性的投资,并将自身的风险偏好与预测结果相结合,对投资组合进行适当的调整。Currently, the interdependence between various industries is becoming increasingly high, and the contagion of financial risks is intensifying. The importance of portfolio management is particularly prominent. This article selects the daily closing prices of five companies’ stocks from January 1, 2019 to June 1, 2023 as the research object. After processing the data, the t-Copula GARCH model is selected to measure the VaR of investment portfolios at different confidence levels using Monte Carlo simulation method. The results indicate that the t-Copula GARCH model has the ability to characterize the true distribution of financial assets, and the interdependence between different assets is asymmetric. Investment portfolios constructed using the Copula function at different confidence levels can significantly reduce investment risk. Therefore, based on the conclusions of this article, it is recommended to consider the strength of interdependence between industries and the characteristics of interdependence structures for rational investment, and combine one’s own risk preferences with prediction results to make appropriate adjustments to the investment portfolio.展开更多
This paper considers the upper orthant and extremal tail dependence indices for multivariate t-copula. Where, the multivariate t-copula is defined under a correlation structure. The explicit representations of the tai...This paper considers the upper orthant and extremal tail dependence indices for multivariate t-copula. Where, the multivariate t-copula is defined under a correlation structure. The explicit representations of the tail dependence parameters are deduced since the copula of continuous variables is invariant under strictly increasing transformation about the random variables, which are more simple than those obtained in previous research. Then, the local monotonicity of these indices about the correlation coefficient is discussed, and it is concluded that the upper extremal dependence index increases with the correlation coefficient, but the monotonicity of the upper orthant tail dependence index is complex. Some simulations are performed by the Monte Carlo method to verify the obtained results, which are found to be satisfactory. Meanwhile, it is concluded that the obtained conclusions can be extended to any distribution family in which the generating random variable has a regularly varying distribution.展开更多
It has been argued that fitting a t-copula to financial data is superior to a normal copula. To overcome the shortcoming that a t-copula only has one parameter for the degrees of freedom, the t-copula with multiple pa...It has been argued that fitting a t-copula to financial data is superior to a normal copula. To overcome the shortcoming that a t-copula only has one parameter for the degrees of freedom, the t-copula with multiple parameters of degrees of freedom has been proposed in the literature, which generalizes both the t-copulas and the grouped t-copulas. Like the inference for a t-copula, a computationally efficient inference procedure is to first estimate the correlation matrix via Kendall's τ and then to estimate the parameters of degrees of freedom via pseudo maximum likelihood estimation. This paper proposes a jackknife empirical likelihood test for testing the equality of some parameters of degrees of freedom based on this two-step inference procedure, and shows that the Wilks theorem holds.展开更多
文摘目前,各个行业相依性变得越来越高,金融风险传染加剧,投资组合管理的重要性尤为突出。本文选择五家公司股票2019年1月1日~2023年6月1日的每日收盘价为研究对象,对数据进行处理后,选择t-Copula-GARCH模型,利用蒙特卡洛模拟方法对不同置信水平下的投资组合风险价值VaR进行测度。结果表明,t-Copula GARCH模型具有刻画真实的金融资产分布的能力,不同资产之间相依关系是非对称的,在不同的置信水平下使用Copula函数构建的投资组合能显著降低投资风险。因此,基于本文的结论,建议考虑各行业间相依性的强弱以及相依结构的特点进行理性的投资,并将自身的风险偏好与预测结果相结合,对投资组合进行适当的调整。Currently, the interdependence between various industries is becoming increasingly high, and the contagion of financial risks is intensifying. The importance of portfolio management is particularly prominent. This article selects the daily closing prices of five companies’ stocks from January 1, 2019 to June 1, 2023 as the research object. After processing the data, the t-Copula GARCH model is selected to measure the VaR of investment portfolios at different confidence levels using Monte Carlo simulation method. The results indicate that the t-Copula GARCH model has the ability to characterize the true distribution of financial assets, and the interdependence between different assets is asymmetric. Investment portfolios constructed using the Copula function at different confidence levels can significantly reduce investment risk. Therefore, based on the conclusions of this article, it is recommended to consider the strength of interdependence between industries and the characteristics of interdependence structures for rational investment, and combine one’s own risk preferences with prediction results to make appropriate adjustments to the investment portfolio.
基金The National Natural Science Foundation of China(No.11001052,11171065)the National Science Foundation of Jiangsu Province(No.BK2011058)the Science Foundation of Nanjing University of Posts and Telecommunications(No.JG00710JX57)
文摘This paper considers the upper orthant and extremal tail dependence indices for multivariate t-copula. Where, the multivariate t-copula is defined under a correlation structure. The explicit representations of the tail dependence parameters are deduced since the copula of continuous variables is invariant under strictly increasing transformation about the random variables, which are more simple than those obtained in previous research. Then, the local monotonicity of these indices about the correlation coefficient is discussed, and it is concluded that the upper extremal dependence index increases with the correlation coefficient, but the monotonicity of the upper orthant tail dependence index is complex. Some simulations are performed by the Monte Carlo method to verify the obtained results, which are found to be satisfactory. Meanwhile, it is concluded that the obtained conclusions can be extended to any distribution family in which the generating random variable has a regularly varying distribution.
基金supported by Simons Foundation and National Natural Science Foundation of China(Grant Nos.11571081 and 71531006)。
文摘It has been argued that fitting a t-copula to financial data is superior to a normal copula. To overcome the shortcoming that a t-copula only has one parameter for the degrees of freedom, the t-copula with multiple parameters of degrees of freedom has been proposed in the literature, which generalizes both the t-copulas and the grouped t-copulas. Like the inference for a t-copula, a computationally efficient inference procedure is to first estimate the correlation matrix via Kendall's τ and then to estimate the parameters of degrees of freedom via pseudo maximum likelihood estimation. This paper proposes a jackknife empirical likelihood test for testing the equality of some parameters of degrees of freedom based on this two-step inference procedure, and shows that the Wilks theorem holds.
