TY - JOUR
T1 - On the asymptotics of value-at-risk for portfolio loss under bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails
AU - Xing, Guo dong
AU - Gan, Xiaoli
AU - Li, Xiaohu
AU - Yang, Shanchao
N1 - Publisher Copyright:
© 2018 Taylor & Francis Group, LLC.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - In the setting of bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails characterized by the power law of tail decay, we give the asymptotics of value-at-risk for portfolio loss as the confidence level tends to one. It can be seen from the obtained asymptotics that diversification decreases the value-at-risk of portfolio loss for the tail index greater than one and increases the value-at-risk of portfolio loss for the tail index less than one. To illustrate the obtained results, a relevant example is shown.
AB - In the setting of bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails characterized by the power law of tail decay, we give the asymptotics of value-at-risk for portfolio loss as the confidence level tends to one. It can be seen from the obtained asymptotics that diversification decreases the value-at-risk of portfolio loss for the tail index greater than one and increases the value-at-risk of portfolio loss for the tail index less than one. To illustrate the obtained results, a relevant example is shown.
KW - Bivariate Eyraud-Farlie-Gumbel-Morgenstern copula
KW - Diversification
KW - Portfolio loss
KW - Power-law
KW - Value-at-risk
UR - http://www.scopus.com/inward/record.url?scp=85055700394&partnerID=8YFLogxK
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U2 - 10.1080/03610918.2018.1520873
DO - 10.1080/03610918.2018.1520873
M3 - Article
AN - SCOPUS:85055700394
SN - 0361-0918
VL - 49
SP - 2462
EP - 2471
JO - Communications in Statistics: Simulation and Computation
JF - Communications in Statistics: Simulation and Computation
IS - 9
ER -