| 徐刚刚,蔡学鹏,熊尚敏.藤Copula模型在我国股市多资产组合VaR预测中的应用[J].井冈山大学自然版,2020,41(2):8-15 |
| 藤Copula模型在我国股市多资产组合VaR预测中的应用 |
| Application of Vine-Copula Model in VaR Forecasting of Multi-Asset portfolio in China's Stock Market |
| 投稿时间：2019-09-17 修订日期：2019-12-18 |
| DOI：10.3969/j.issn.1674-8085.2020.02.002 |
| 中文关键词: 藤Copula 滚动Monte Carlo模拟 动态VaR MST-PRIM算法 |
| 英文关键词: Vine-Copula rolling Monte Carlo simulation dynamic VaR MST-PRIM algorithm |
| 基金项目:新疆维吾尔族自治区高校科研计划项目(XJEDU2018Y021)；新疆农业大学大学生创新创业训练计划项目(S201910758072) |
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| 摘要点击次数: 1893 |
| 全文下载次数: 3560 |
| 中文摘要: |
| 选取我国六只股指数据为研究对象，基于几类藤Copula模型和VaR理论，运用滚动Monte Carlo技术及MST-PRIM算法确定各类模型的RVM结构，并在此基础上结合滚动时间窗口方法预测投资组合的动态VaR。为了进一步验证模型的拟合效果，采用返回值检验法测试模型的VaR预测结果。事实证明：在等权重与Mean-CVaR约束条件下，C-藤和R-藤对投资组合的VaR预测效果胜于D-藤;另外，R-Vine all Gumbel模型的VaR预测结果比R-Vine all t模型好，充分说明在面对非对称特点的金融数据时，Gumbel-Copula比t-Copula更具说服力。 |
| 英文摘要: |
| Six stock markets indexes data of China are selected as the research object.Based on several types of Vine Copula model and VaR theory, rolling Monte Carlo technology and MST-PRIM algorithm are used to determine the RVM structure of various models. On this basis, combined with rolling time window method, the dynamic VaR of portfolio is predicted. In order to further verify the fitting effect of the model, the Kupiec's test method is used to test the model VaR prediction. As a result, it has been proved that under equal weight and Mean-CVaR constraints, C-Vine and R-Vine have better predictive effect on portfolio VaR than D-Vine. In addition, the predictive result of R-Vine all Gumbel model is better than the predictive results of R-Vine all t model, which illustrates that Gumbel-Copula is more convincing than t-Copula for asymmetric financial data. |
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