Estimating the negative impact of noise on the returns of cap-weighted portfolios in various segments of the JSE

Van der Merwe, Rachelle (2015-04)

Thesis (MBA)--Stellenbosch University, 2015.

Thesis

ENGLISH ABSTRACT:The main aim of this study was to determine the effect of unanticipated information, or noise, on the returns of cap-weighted portfolios in various segments of the JSE for the period 1995 to 2014. Capital Market Theory states that the optimal ex ante portfolio comprises all shares in a market/segment weighted by ex ante market capitalisation. The optimal ex ante portfolio is however rarely the optimal ex post portfolio, because it is underweighted in shares that will unexpectedly become ‘winners’ during the investment period and overweighted in those that will become ‘losers’. According to Fuller, Han and Tung (2012), all investors in a segment would gain maximum alpha from a portfolio weighted by ex post market capitalisation – in other words, a ‘perfect foresight’ (PF) portfolio. The excess return of the PF portfolio over the benchmark portfolio therefore is an estimate of the negative effect of noise on the return of the benchmark portfolio. In this study, the returns of PF portfolios were compared with the All Share, Large Cap, Mid Cap, Small Cap, Financials, Industrials and Resources segments of the JSE. Intuitively, information to guide decisions on portfolio weighting would be more valuable and deliver more profit when the cross-sectional standard deviation of share returns is high. A secondary aim was therefore to investigate the correlation between cross-sectional standard deviation and PF excess return. It was found that a strong positive correlation (more than 88%) existed between cross-sectional standard deviation and PF excess return in all segments. In ascending order of cross-sectional standard deviation and PF excess return, the results for the segments were Financials (25% and 5%), Resources (28% and 6%), Large Cap (29% and 8%), Industrials (30% and 9%), All Share (32% and 9%), Mid Cap (36% and 13%) and Small Cap (43% and 17%).

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/97363
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