Markowitz Portfolio Selection Using Various Estimators of Expected Returns and Filtering Techniques for Correlation Matrices
András London, Imre Gera, Bánhelyi Balázs · Acta Polytechnica Hungarica · 2018
In this study we examine the performance of the Markowitz portfolio optimization model using stock time series data of various stock exchanges and investment period intervals.Several methods are used to estimate expected returns, then different "noise" filtering techniques are applied on the correlation matrix containing the pairwise correlations of the time series.The performance of the methods is compared using the estimated and realized returns and risks, respectively.The results show that the estimated risk is closer to the realized risk using filtering methods in general.Bootstrap analysis shows that ratio between the realized return and the estimated risk (Sharpe ratio) is also improved by filtering.In terms of the expected return estimation results show that the James-Stein estimator improves the reliability of the portfolio, which means that the realized risk is closer to the estimated risk in this case.