Portfolio optimization of stock returns in high-dimensions: A copula-based approach

K. Autchariyapanitkul, S. Chanaim, S. Sriboonchitta

Abstract

We used the multivariate t copula, which can capture the tail de-pendence to modeling the dependence structure of the risk in portfolio analysis.Multivariate t copula based on GARCH model was used to explain portfolio riskstructure for high-dimensional asset allocation issue. With this method we usedthe Monte Carlo simulation and the results of multivariate t copula to estimatethe expected shortfall of the portfolio. Finally, we obtained the optimal weightedfor conditional Value-at-Risk (CVaR) model with the assumption of multivariatedistribution to illustrate the potential model risk among portfolios returns.