TY - JOUR
T1 - Directional time-varying partial correlation with the Gaussian copula–DCC–GARCH model
AU - Kim, Jong Min
AU - Jung, Hojin
PY - 2018/9/2
Y1 - 2018/9/2
N2 - This article suggests a directional time-varying partial correlation based on the dynamic conditional correlation (DCC) method. A recent study proposed the copula DCC based on the vine structure. Due to the arbitrary variable selection, their method can produce unnecessary dependence in the multivariate structure, with extra economic and computational burdens. To overcome this limitation, we incorporate directional dependence by copula to track the causal relationship among multiple variables and then extend the copula bivariate DCC method to a directional time varying partial correlation in the multivariate structure. Our proposed method provides a reasonable and efficient conditional dependence structure, without the trial and error process. We offer an application of our method to the U.S. stock market as an illustrated example.
AB - This article suggests a directional time-varying partial correlation based on the dynamic conditional correlation (DCC) method. A recent study proposed the copula DCC based on the vine structure. Due to the arbitrary variable selection, their method can produce unnecessary dependence in the multivariate structure, with extra economic and computational burdens. To overcome this limitation, we incorporate directional dependence by copula to track the causal relationship among multiple variables and then extend the copula bivariate DCC method to a directional time varying partial correlation in the multivariate structure. Our proposed method provides a reasonable and efficient conditional dependence structure, without the trial and error process. We offer an application of our method to the U.S. stock market as an illustrated example.
KW - Directional dependence
KW - dynamic conditional correlation
KW - time-varying partial correlation
UR - http://www.scopus.com/inward/record.url?scp=85044180476&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044180476&partnerID=8YFLogxK
U2 - 10.1080/00036846.2018.1450485
DO - 10.1080/00036846.2018.1450485
M3 - Article
AN - SCOPUS:85044180476
SN - 0003-6846
VL - 50
SP - 4418
EP - 4426
JO - Applied Economics
JF - Applied Economics
IS - 41
ER -