<p>This paper studies the out of sample risk reduction of global minimum variance portfolio. The analysis are drown from the discussions of Jagannathan and Ma (2003) regarding the risk reduction in US stock portfolios using portfolio constraints. We estimate the covariance matrix using the sample covariance matrix approach and derive optimal minimum variance portfolios considering upper/lower bounds and no restrictions. Results are shown under different revision frequency and transaction costs assumed. The data used are monthly indices of stocks, bonds, gold oil and spreads from 1996 until 2013. Unconstrained GMVPs result in the lowest out of sample variance, while unconstrained GMVPs of global bond portfolios performs the best in terms of risk reduction. Diversification through global asset classes result in a better strategy than international stock diversification regarding risk, as suggested by the literature.</p>

The paper studies the differences in risk reduction among global minimum variance portfolios (GMVPs) derived from the optimization of weekly and monthly return. This research follows the analysis of Zibri and Kukeli (2014) regarding differences in performance which is measured for different revision frequencies and transaction costs. The data used are weekly/monthly returns for stock, bond, gold, oil indices for the period 1996-2013. If more frequently rebalancing is applied, most restrictive weekly GMVPs reduce risk more than returns vis--vis monthly GMVPs.