| 基于MCMC算法的时变Copula-GARCH-t模型参数估计及应用 |
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| 引用本文： | 傅强,彭选华.基于MCMC算法的时变Copula-GARCH-t模型参数估计及应用[J].数量经济技术经济研究,2011(7). |
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| 作者姓名： | 傅强 彭选华 |
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| 作者单位： | 重庆大学经济与工商管理学院; |
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| 基金项目： | 国家自然科学基金(70501015); 教育部博士点基金(20100191110033); 重庆大学研究生科技创新基金(200811A1B0080297)项目的资助 |
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| 摘 要： | 本文假设单变量时序的新息服从标准的学生t分布,提出多元时变Copula-GARCH-t模型,利用蒙特卡洛马尔科夫链(MCMC)算法对模型参数进行贝叶斯统计推断,给出了多个资产组合风险VaR和CVaR的度量方法,并基于风险最小化原则确立了最佳的资产配置模型。实证分析表明,MCMC方法优于经典的IFM方法,能够充分捕捉到中美股市的时变相依结构及相关系数和尾部指数的动态特征。
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| 关 键 词： | MCMC算法 Copula-GARCH 时变相依结构 |
Time-varying Copula-GARCH-t Model Based on the MCMC Algorithm and its Application in Portfolio Risk Measurement |
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| Fu Qiang et al..Time-varying Copula-GARCH-t Model Based on the MCMC Algorithm and its Application in Portfolio Risk Measurement[J].The Journal of Quantitative & Technical Economics,2011(7). |
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| Authors: | Fu Qiang |
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| Institution: | Fu Qiang et al. |
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| Abstract: | The article proposes a time-varying Copula-GARCH-t model,which assumes that the innovation comes from the standard students' t-distribution.By using the MCMC algorithm to a Bayesian statistical inference,we obtain one-step CVaR and VaR prediction method,and further establish an optimal weight of asset allocation based on risk minimization principle.For the analysis of Shanghai composite index,Hang Sang Index,TWII and America's S&P 500,the results show that,MCMC method is superior to the classical IFM method... |
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| Keywords: | MCMC Algorithm Copula-GARCH Time-varying Dependency Structure |
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