Low volatility alternative equity indices

 

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dc.contributor.advisor Bradfield, David en_ZA
dc.contributor.author Oladele, Oluwatosin Seun en_ZA
dc.date.accessioned 2015-12-08T11:43:15Z
dc.date.available 2015-12-08T11:43:15Z
dc.date.issued 2015 en_ZA
dc.identifier.citation Oladele, O. 2015. Low volatility alternative equity indices. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/15691
dc.description.abstract In recent years, there has been an increasing interest in constructing low volatility portfolios. These portfolios have shown significant outperformance when compared with the market capitalization-weighted portfolios. This study analyses the low volatility portfolios in South Africa using sectors instead of individual stocks as building blocks for portfolio construction. The empirical results from back-testing these portfolios show significant outperformance when compared with their market capitalization weighted equity benchmark counterpart (ALSI). In addition, a further analysis of this study delves into the construction of the low volatility portfolios using the Top 40 and Top 100 stocks. The results also show significant outperformance over the market-capitalization portfolio (ALSI), with the portfolios constructed using the Top 100 stocks having a better performance than portfolio constructed using the Top 40 stocks. Finally, the low volatility portfolios are also blended with typical portfolios (ALSI and the SWIX indices) in order to establish their usefulness as effective portfolio strategies. The results show that the Low volatility Single Index Model (SIM) and the Equally Weight low-beta portfolio (Lowbeta) were the superior performers based on their Sharpe ratios. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Statistics en_ZA
dc.title Low volatility alternative equity indices en_ZA
dc.type Thesis / Dissertation en_ZA
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Statistical Sciences en_ZA
dc.type.qualificationlevel Masters en_ZA
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image


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