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Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR)
Journal of Time Series Econometrics ( IF 0.6 ) Pub Date : 2019-05-06 , DOI: 10.1515/jtse-2017-0016
Paula V. Tófoli 1 , Flávio A. Ziegelmann 2 , Osvaldo Candido 3 , Pedro L. Valls Pereira 4
Affiliation  

Abstract Vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a restricted ARMA(1, m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets. We also investigate the dynamic D-vine copula in a simulation study and the overall results of the Monte Carlo experiments are quite favorable to the dynamic D-vine copula in comparison with a static D-vine copula.

中文翻译:

动态D型藤Copula模型及其在风险价值(VaR)中的应用

摘要藤系动词是从成对系动词(双变量系动词)构造的多元依赖模型。在本文中,我们遵循受限的ARMA(1,m)过程,允许D-vine分解中的对-对数的依赖参数可能随时间变化,从而获得用于应用的非常灵活的依赖模型。多元财务收益数据。我们调查在危机和非危机中来自德国(DAX),法国(CAC 40),英国(FTSE 100),美国(S&P 500)和巴西(IBOVESPA)的广泛股市指数之间的依赖关系时期。我们发现熊市指数之间存在较强的依赖性。不过,令人惊讶的是,动态D型藤蔓copula表明,在2011年初,指数FTSE和CAC之间的依存关系急剧下降,以及2011年中和2008年初之间CAC和DAX之间的关系,这表明这些案例中没有传染性。我们评估相对于风险时期的风险价值(VaR)预测准确性的动态D型葡萄系。就我们的真实数据集的预测准确性而言,动态D-vine优于静态D-vine。我们还在模拟研究中研究了动态D型葡萄藤蔓,与静态D型葡萄藤蔓相比,蒙特卡罗实验的总体结果对动态D型葡萄藤蔓非常有利。就我们的真实数据集的预测准确性而言,动态D-vine优于静态D-vine。我们还在模拟研究中研究了动态D型葡萄藤蔓,与静态D型葡萄藤蔓相比,蒙特卡罗实验的总体结果对动态D型葡萄藤蔓非常有利。就我们的真实数据集的预测准确性而言,动态D-vine优于静态D-vine。我们还在模拟研究中研究了动态D型葡萄藤蔓,与静态D型葡萄藤蔓相比,蒙特卡罗实验的总体结果对动态D型葡萄藤蔓非常有利。
更新日期:2019-05-06
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