Analysis of portfolio VaR by pair copula-GARCH

doi:10.7523/j.issn.2095-6134.2010.4.002

Welcome to Journal of University of Chinese Academy of Sciences，Today is

Email Alert RSS 中文

›› 2010, Vol. 27 ›› Issue (4): 440-447.DOI: 10.7523/j.issn.2095-6134.2010.4.002

• Research Articles • Previous Articles Next Articles

Analysis of portfolio VaR by pair copula-GARCH

HUANG En-Xi, CHENG Xi-Jun

Department of Statistic and Finance, University of Science and Technology of China, Hefei 230026, China

Received:2009-11-03 Revised:2010-03-05 Online:2010-07-15

Abstract

Abstract:

We propose a pair copula-GARCH model to analyze the risk of Multi-asset portfolio. Compared to other Copula-GARCH models,our method can capture the tail dependence of different pairs of risk factors in a portfolio so that it can describe the dependence structure of the risk factors better. By using this model combined with Monte Carlo techniques, the numerical analysis of portfolio VaR is fully discussed in this paper. Finally, the empirical portfolio risk analysis is given.

Key words: pair copula, GARCH, Monte Carlo, VaR

CLC Number:

F830.9

HUANG En-Xi, CHENG Xi-Jun. Analysis of portfolio VaR by pair copula-GARCH[J]. , 2010, 27(4): 440-447.

[1]	LIU Tao, YANG Degang, ZHANG Yufang, CAI Tianyi. Spatial-temporal change and influence factors of park green space accessibility in arid area: taking Urumqi as an example [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(3): 350-359.
[2]	RAO Weilong, ZHANG Lan, WANG Qiuyu, TANG He, SUN Wenke. Mass migration of Qinghai-Tibet Plateau studied by using GRACE time-variable gravity [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(1): 9-22.
[3]	LI Fei, YANG Fuzhong. The superpotential and geometric invariants of D-brane system on compact Calabi-Yau manifold [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(1): 41-48.
[4]	LAI Xunfei, LIANG Xuwen, XIE Zhuochen, LI Zongwang. Intrusion detection method based on entity embedding and long short-term memory networks [J]. , 2020, 37(4): 553-561.
[5]	WANG Hongbin. The continuity for commutators of Marcinkiewicz integrals on Herz-type space with variable exponent [J]. , 2020, 37(2): 155-161.
[6]	JIANG Xiaotian, YANG Fuzhong. Parallel/coincident D-brane superpotentials, Ooguri-Vafa invariants, and Type II/F theory duality [J]. , 2019, 36(5): 590-597.
[7]	LI Qi, ZHANG Na, LUO Yingjie, WANG Xin, JING Yongcai. The first flush effect of urban rainfall runoff based on MFF₃₀ method [J]. , 2019, 36(5): 650-662.
[8]	LI Kuangyu, ZHOU Mei, CHEN Jiuying, PAN Miaomiao, LI Chuanrong, TANG Lingli. An approach of improved gradient plus inverse distance squared for spatial interpolation of temperature [J]. , 2019, 36(4): 491-497.
[9]	ZHANG Shenghu, ZHU Jiayan, ZHANG Sanguo. A powerful procedure for multiple outcomes comparison with covariate adjustment and its application to genomic data [J]. , 2019, 36(2): 155-161.
[10]	LI Hongying, LIAO Jiafeng. Existence of positive solutions for a class of Kirchhoff-type equations with critical Hardy-Sobolev exponent [J]. , 2019, 36(1): 11-14.
[11]	ZHI Junhai, CHEN Yufu. Constructing integrating factor to distinguish between the center and the focus [J]. , 2018, 35(5): 577-581.
[12]	CHEN Songsong, CHENG Xijun, MA Lijun. A margin model with liquidity risk [J]. , 2018, 35(5): 589-594.
[13]	ZHANG Shuangshuang, MIAO Bing, SUO Tongchuan. Solvent-dependence of the characteristic scaling exponent for single polymer chain with finite length [J]. , 2018, 35(5): 602-606.
[14]	LIU Jinping, ZHANG Wanchang. Spatial variability in degree-day factors in Yarlung Zangbo River Basin in China [J]. , 2018, 35(5): 704-711.
[15]	LIU Zhifan, WANG Miaomiao, XIE Tianfa, SUN Zhihua. Estimation of error-in-variable varying-coefficient model with auxiliary instrument variables [J]. , 2018, 35(1): 1-9.

Analysis of portfolio VaR by pair copula-GARCH

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments