An Empirical Evaluation of Alternative Asset Allocation Policies for Emerging and Frontier Market Investors in Africa ()
ABSTRACT
Despite forming an integral part of literature and
practitioner knowledge, Markowitz-based optimization has been
shown to suffer severe drawbacks of estimation errors and sensitivity to input
parameters when implemented in practice. The best diversification methods from
the perspective of a private investor in real-life situations still remain
largely unsolved. Most of the potential diversification benefits so far have
primarily been analyzed for internationally diversified stock portfolios, with a focus on the special viewpoint of U.S investors.
Studies have suggested that the Mean-Variance optimization can be robustified
by the use of robust covariance estimators other than the sample covariance
that relies on the classical Maximum Likelihood Estimator. Using a portfolio
formed from 2 Emerging Market and 5 Frontier Market indices in Africa, this
study sought to compare the performance of the traditional Mean-Variance model
against the performance of the Mean-Variance optimization model robustified
with the Orthogonalized Gnanadesikan-Kettenring, Minimum Covariance
Determinant, Minimum Volume Ellipsoid and shrink estimators, with an aim of
recommending the best model applicable to the African emerging and frontier
markets investors. The robustified models were found to indeed have better
characteristics in terms of gross returns, annualized returns and net portfolio
returns over time compared to the traditional Mean-Variance optimization model.
Share and Cite:
Job, O. (2022) An Empirical Evaluation of Alternative Asset Allocation Policies for Emerging and Frontier Market Investors in Africa.
Journal of Financial Risk Management,
11, 481-521. doi:
10.4236/jfrm.2022.113024.