TY - JOUR
T1 - On the asymptotics of tail conditional expectation for portfolio loss under bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails
AU - Xing, Guo dong
AU - Li, Xiaohu
AU - Yang, Shanchao
N1 - Publisher Copyright:
© 2018 Taylor & Francis Group, LLC.
PY - 2020/8/2
Y1 - 2020/8/2
N2 - In the setting of bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails characterized by the power law of tail decay, we present the asymptotics of tail conditional expectation for portfolio loss as the confidence level tends to one. In order to illustrate the obtained result, a numerical example and its relevant simulation are carried out.
AB - In the setting of bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails characterized by the power law of tail decay, we present the asymptotics of tail conditional expectation for portfolio loss as the confidence level tends to one. In order to illustrate the obtained result, a numerical example and its relevant simulation are carried out.
KW - Asymptotics
KW - Bivariate Eyraud-Farlie-Gumbel-Morgenstern copula
KW - Portfolio loss
KW - Power-law
KW - Tail conditional expectation
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U2 - 10.1080/03610918.2018.1510526
DO - 10.1080/03610918.2018.1510526
M3 - Article
AN - SCOPUS:85057227825
SN - 0361-0918
VL - 49
SP - 2049
EP - 2058
JO - Communications in Statistics: Simulation and Computation
JF - Communications in Statistics: Simulation and Computation
IS - 8
ER -