Abstract
Traditional correlation coefficients could not accommodate the more complexed dependency between markets. Copula modes are the alternative way to trace the dependence among markets. We use three major stock market indexes ranged from 2000 to 2020 to model the dependence between market indexes. Our sample period covers three major extreme events; therefore, it is quite suitable for copula modelling the dependence across the border. We compare the bivariate copulas to multivariate copulas in modelling the dependency. Our results show that multivariate vine copula model could choose much different pair copulas from bivariate copula. Our finding has a very important implication to portfolio manager and risk manager.
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IJAHSS by IPRPD is licensed under a Creative Commons Attribution 4.0 International License.