论文研究-基于BEMD-Copula-GARCH模型的股票投资组合VaR风险度量研究.pdf
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37
2
Vol.37, No.2
2017
2
Systems Engineering — Theory & Practice Feb., 2017
doi: 10.12011/1000-6788(2017)02-0303-08
: F830.91
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VaR measurement for stock portfolio based on
BEMD-Copula-GARCH model
WANG Xuan
1
, CAI Junling
2
, TANG Ling
2
, HE Kaijian
3
(1. School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China; 2. School of
Economics and Management, Beihang University, Beijing 100191, China; 3. School of Business, Hunan University of Science
and Technology, Xiangtan 411201, China)
Abstract Given that stock fluctuation has significant multi-scale features, a novel Value-at-Risk (VaR)
model is proposed by combining the binary empirical mode decomposition (BEMD) and Copula-GARCH
algorithm, i.e., BEMD-Copula-GARCH model. In the proposed model, three main steps are included,
i.e., data decomposition, individual risk measurement, and total risk integration. First, the binary EMD
technique is employed to decomposed the pair of complex and interactive stock series into pairs of relatively
simple and independent components, to reduce the modeling difficulty. Second, Copula-GARCH model
is introduced to individually capture the dynamic dependence between the decomposed components in
pairs, in terms of VaR at different time-scale. Finally, the individual results are integrated into the final
VaR measure. In the empirical study, the portfolio with equal-weighted Hang Seng Index and Shanghai
Composite index is analyzed, and the results indicate that the proposed model outperform the benchmark
DCC-GARCH model and Copula-GARCH model in terms of the risk measurement accuracy.
: 2015-05-26
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(1968–),
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, E-mail: tangling@mail.buct.edu.cn;
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(71433001, 71301006, 71201054)
Foundation item: National Natural Science Foundation of China (71433001, 71301006, 71201054)
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BEMD-Copula-GARCH
VaR
[J].
, 2017, 37(2): 303–310.
b_`a
: Wang X, Cai J L, Tang L, et al. VaR measurement for stock portfolio based on BEMD-Copula-GARCH model[J].
Systems Engineering — Theory & Practice, 2017, 37(2): 303–310.
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