The portfolio construction implications of using various smart beta fundamentals and the fundamental-classification persistence of stocks
Thesis (MBA)--Stellenbosch University, 2018.
ENGLISH SUMMARY : South African investors have been slow to adopt the smart beta investment style as a new investment vehicle compared to their counterparts in the rest of the world. This predisposition towards smart beta is probably because of its lack of a successful track record and transparency (Cox, 2014). This study attempted to provide insight into both the portfolio construction characteristics of local smart beta funds and the classification persistence of stocks using various fundamental factors. Six established fundamental factors, namely value, profitability, momentum, investment, liquidity and high yield, were selected to simulate six single- and two multifactor smart beta portfolios. The ‘winner’ and ‘loser’ portfolios of each factor were analysed both separately and in combination with each other. One multifactor portfolio applied an equal-weighting to factors by using the equally weighted multifactor fund (EWMF), while the other portfolio was constructed to assign a bigger weighting to factors that recently performed well, using the fundamental factor performance history weighted (FFPHW). A ten-year history was used and the 100 largest stocks listed on the Johannesburg Stock Exchange (JSE) on a monthly basis were eligible to be included in the selection of 30 winner and loser stock portfolios. The FFPHW contributes to the existing body of knowledge on constructing smart beta portfolios. The FFPHW methodology was implemented to test the potential of adding value when assigning weights to fundamental factors based on their individual prior performance. The FFPHW strategy was tested against the SWIX and managed to produce an annualised 2.9 per cent market-adjusted abnormal after-cost return over a ten-year period. Against expectation, the equal-weighted strategy significantly outperformed the FFPHW portfolio by achieving an annualised 6.2 per cent market-adjusted abnormal after-cost return. Assigning equal weights to individual fundamental factors in a multifactor portfolio is therefore preferred. The individual fundamental factors that drive returns in the two multifactor portfolios were also tested. Similar to Hou, Xue and Zhang (2016), the profitability factor proved to be a dominating driving force of returns in the multifactor portfolios. The momentum fundamental factor also proved to be a significant driver of returns, which is in contrast with what Van Heerden (2014) reported. The investment and liquidity fundamental factors proved to have limited investment value as they failed to consistently identify the potential outperforming stocks. An analysis of the relationships that may hold between i) net returns, ii) portfolio churn and iii) classification persistence under various portfolio rebalancing strategies was conducted to provide insights into the practical implications of constructing smart beta fund portfolios. A decreasing marginal benefit of return was found for extending the periods between portfolio rebalancing activities. Quarterly rebalancing proved to be the optimal rebalancing strategy as it captures short-lived profits before the stock prices mean-revert. The classification persistence of stocks was also analysed. Classification persistence is defined as the probability of a stock persisting under its existing winner (buy), neutral or loser (sell) classification for the following period given that it already persisted for four, five or six months. The classification persistence of stocks proved to be extremely high once the stock has already persisted for at least four months. No significant difference in the classification persistence of stocks across various sectors could be noted. The winner portfolios, however, proved to display lower classification persistence than the loser portfolios. So-called ‘bad’ stocks are therefore more likely to remain ‘bad’ than ‘good’ stocks are to remain ‘good’. Even though the study found that smart beta offered investors a profitable long-term strategy over a ten year period of 2007 - 2016, smart beta strategies struggled to outperform the SWIX from 2012 onwards. Overall, the study concluded that the costs involved in executing portfolio decisions did not outweigh the benefits, that winner and loser portfolios did not change very often, and that the fundamental factor interaction provided additional investment value.
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