Optimal asset allocation for South African pension funds under the revised Regulation 28

[摘要] ENGLISH ABSTRACT:On 1 July 2011 the revised version of Regulation 28, which governs the South Africanpension fund industry with regard to investments, took effect. The new version allows forpension funds to invest up to 25 percent compared to 20 percent, in the previous version,of its total investment in foreign assets. The aim of this study is to determine whetherit would be optimal for a South African pension fund to invest the full 25 percent of itsportfolio in foreign assets.Seven different optimization models are evaluated in this study to determine the optimalasset mix. The optimization models were selected through an extensive literature studyin order to address key optimization issues, e.g. which risk measure to use, whetherparametric or non parametric optimization should be used and if the Mean Variance modelfor optimization defined by Markowitz, which has been the benchmark with regard to assetallocation, is the best model to determine the long term asset allocation strategies.The results obtained from the different models were used to recommend the optimallong term asset allocation for a South African pension fund and also compared to determinewhich optimization model proved to be the most efficient.The study found that when using only the past ten years of data to construct theportfolios, it would have been optimal to invest in only South African asset classes withstatistical differences with regard to returns in some cases. Using the past 20-years of datato construct the optimal portfolios provided mixed results, while the 30-year period weremore in favour of an international portfolio with the full 25% invested in foreign assetclasses.A comparison of the different models provided a clear winner with regard to a probabilityof out performance. The Historical Resampled Mean Variance optimization provided the highest probability of out performing the benchmark. From the study it also becameevident that a 20-year data period is the optimal period when considering the historicaldata that should be used to construct the optimal portfolio.

[发布机构] Stellenbosch University