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    VaR系列(三):DCC模型估计组合VaR

    Engle(2002)年提出了DCC模型,通过DCC模型对相关系数建的整体思路与之前对于单个资产波动率建模的思路基本一致,包括两种方法: 第一种类似RM方法, 通过指数平滑的方法对对相关系数建模,后文统称为...DCC-RM模型,公式来自Engle的paper,需要文献在后台回复"VaR3",公式中的 ?...基于上式,分别讨论两种模型的参数估计过程 DCC-RM 两个资产下,模型可以表示为 ? 带入对数似然函数,求使对数似然函数最大的lambda的值。 初始值: ?...基于DCC-RM模型的VaR ? 基于DCC-Garch模型的时变相关系数 ? 其中,红色线为DCC-RM估计得到的相关系数,绿色线为DCC-Garch估计得到的相关系数,整体趋势一致。...基于DCC-Garch模型的VaR ? 其中,红色线为DCC-RM估计得到的VaR,绿色线为DCC-Garch估计得到的VaR,整体趋势一致。

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    干货 | 最全的文件上传漏洞之WAF拦截绕过总结

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    15.4K56

    R语言改进的DCC-MGARCH:动态条件相关系数模型、BP检验分析股市数据

    在金融领域中,DCC条件(sigma)和收益率之间存在一定的关系。DCC条件(sigma)可以用来估计不同资产之间的相关性,从而帮助投资者更好地理解资产之间的联动性。...plot(fit1 DCC条件均值和收益率 DCC条件均值和收益率是金融领域中的两个重要概念。...DCC 条件协方差 DCC 条件协方差(DCC Conditional Covariance)是一种用于估计金融时间序列中的条件协方差的方法。...DCC 方法通过引入一个动态相关系数矩阵来估计条件协方差。这个矩阵可以随时间变化,反映了变量之间的相关关系的变化。DCC 方法使用了两个步骤来估计条件协方差。...DCC 条件相关系数 DCC 条件相关系数(Dynamic Conditional Correlation)是一种用于衡量时间序列数据中相关性变化的统计指标。

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    R语言多元动态条件相关DCC-MVGARCH、常相关CCC-MVGARCH模型进行多变量波动率预测

    CCC 和DCC 恩格尔(2002)在其开创性的论文中提出了下一个重要的步骤,随后文献中出现了一个高潮。"...对于CCC(恒定条件相关),我们使用样本相关矩阵,而对于DCC(动态),我们使用基于例如3个月的移动窗口估计的相关矩阵。...par()$mar # 边距 plot(ann*cov_ccc[1,1,]~time plot(ann*cov_ccc[1,2,]~time) 点击标题查阅往期内容 GARCH-DCC模型和DCC...在下图中,我们有三个协方差项,一次是假设CCC的估计(实线),一次是假设DCC的估计(虚线)。对于中期和长期债券之间的协方差,如果你假设恒定或动态相关矩阵,并不重要。...本文摘选 《 R语言多元动态条件相关DCC-MVGARCH、常相关CCC-MVGARCH模型进行多变量波动率预测 》

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