Portfolio Resampling in Malaysian Equity Market

Abstract

Since the work of Markowitz (1959) and Sharpe (1964), Mean-Variance (MV) analysis has been a central focus of financial economics. Problems involving quadratic objective functions generally incorporate a MV analysis. However, estimation error is known to have huge impact on MV optimized portfolios, which is one of the primary reasons to make standard Markowitz optimization unfeasible in practice. In these studies we focus on a relatively new approach introduced by Michaud (1998), resampled efficiency. Michaud argues that the limitations of MV efficiency in practice generally derive from a lack of statistical understanding of MV optimization. He advocates a statistical view of MV optimization that leads to new procedures that can reduce estimation error. Optimal portfolio based on MV efficiency and resampled efficiency is compared in an empirical out-of sample study in term of their performances using Malaysian stock market. We divided the data to three groups, daily, weekly and monthly. We found that, resampled efficiency performed well and group of daily and weekly data have the least estimation error.