基于BEMD-Copula-GARCH模型的股票投资组合VaR风险度量研究
发布时间：2018-10-16 14:47
【摘要】：鉴于股票波动具有显著的多尺度特征,本文引入二元经验模态分解(EMD)与二元CopulaGARCH算法,提出一种新的VaR风险度量模型,即BEMD-Copula-GARCH模型.具体地,新BEMD-Copula-GARCH模型可分为三个主要步骤:数据分析,分风险估计和总风险集成.首先,基于二元EMD模型,将复杂且相互作用的股票对分解为若干组较为简单且相互独立的分量,以降低建模难度.其次,引入二元Copula-GARCH模型,刻画各组分量间的相互关系,以度量股票投资组合在不同尺度上的分VaR值.最后,集成各分VaR值以得出最终VaR风险度量结果.实证研究以恒生指数与上证综指为数据样本构造投资组合,结果表明:本文所构建的新模型能有效度量投资组合风险,其估计精度显著优于DCC-GARCH和Copula-GARCH等现有模型.
[Abstract]:In view of the remarkable multi-scale characteristics of stock volatility, this paper introduces binary empirical mode decomposition (EMD) and binary CopulaGARCH algorithm, and proposes a new VaR risk measurement model, that is, BEMD-Copula-GARCH model. Specifically, the new BEMD-Copula-GARCH model can be divided into three main steps: data analysis, risk estimation and total risk integration. Firstly, based on the binary EMD model, the complex and interacting stock pairs are decomposed into some simple and independent components to reduce the difficulty of modeling. Secondly, a binary Copula-GARCH model is introduced to describe the relationship between each group of components to measure the VaR value of the stock portfolio on different scales. Finally, the VaR values are integrated to get the final VaR risk measurement results. The empirical study takes Hang Seng Index and Shanghai Composite Index as data samples to construct a portfolio. The results show that the new model can effectively measure portfolio risk and its estimation accuracy is significantly better than that of existing models such as DCC-GARCH and Copula-GARCH.
【作者单位】： 北京化工大学经济管理学院;北京航空航天大学经济管理学院;湖南科技大学商学院;
【基金】：国家自然科学基金(71433001,71301006,71201054)~~
【分类号】：F830.91
[Abstract]:In view of the remarkable multi-scale characteristics of stock volatility, this paper introduces binary empirical mode decomposition (EMD) and binary CopulaGARCH algorithm, and proposes a new VaR risk measurement model, that is, BEMD-Copula-GARCH model. Specifically, the new BEMD-Copula-GARCH model can be divided into three main steps: data analysis, risk estimation and total risk integration. Firstly, based on the binary EMD model, the complex and interacting stock pairs are decomposed into some simple and independent components to reduce the difficulty of modeling. Secondly, a binary Copula-GARCH model is introduced to describe the relationship between each group of components to measure the VaR value of the stock portfolio on different scales. Finally, the VaR values are integrated to get the final VaR risk measurement results. The empirical study takes Hang Seng Index and Shanghai Composite Index as data samples to construct a portfolio. The results show that the new model can effectively measure portfolio risk and its estimation accuracy is significantly better than that of existing models such as DCC-GARCH and Copula-GARCH.
【作者单位】： 北京化工大学经济管理学院;北京航空航天大学经济管理学院;湖南科技大学商学院;
【基金】：国家自然科学基金(71433001,71301006,71201054)~~
【分类号】：F830.91
【相似文献】
相关期刊论文 前10条
1 罗俊鹏;;基于Copula的金融市场的相关结构分析[J];统计与决策;2006年16期
2 孙志宾;;混合Copula模型在中国股市的应用[J];数学的实践与认识;2007年20期
3 李娟;戴洪德;刘全辉;;几种Copula函数在沪深股市相关性建模中的应用[J];数学的实践与认识;2007年24期
4 王s，
本文编号：2274691
本文链接：https://www.wllwen.com/jingjilunwen/jinrongzhengquanlunwen/2274691.html
