Browsing by Author "Krige, J. D."

Now showing 1 - 6 of 6
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    Analysis of sources of return in South African private equity
    (AOSIS, 2009) Van Niekerk, J. R.; Krige, J. D.
    Private Equity is rapidly growing as an asset class for investors in South Africa. Local and international literature presents overwhelming evidence to suggest that Private Equity offers superior risk-adjusted returns and portfolio diversification benefits. This study addresses the question of how exactly Private Equity managers are able to achieve superior returns. A sample of 46 individual completed investments representing large buy-outs in South Africa in the period 1992 to 2007 was selected and analysed to quantitatively investigate the relationship between some of the identified sources of return and the realised internal rates of return in the case of each investment. These relationships were not found to be as strong as expected and in many cases were not supportive of the findings in the literature. Only earnings growth and an increase in the earnings multiple had a significant impact on the internal rates of return achieved according to the sample analysed. The authors conclude that investing in Private Equity is too interdisciplinary to distil the sources of return into a few concise elements. Proprietary knowledge, expertise, superior management skills, relationships and experience all seem to play a role in providing Private Equity managers with a competitive edge over their public market participants.
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    Evaluating the economic impact of national sporting performance : evidence from the Johannesburg Stock Exchange
    (AOSIS, 2010) Smith, B. K.; Krige, J. D.
    This study examines the impact of South Africa's national soccer, rugby and cricket teams' performances in international matches on returns on the Johannesburg Stock Exchange (JSE). Match results constitute a mood proxy variable hypothesised to affect stock returns through its influence on investor mood. The unconditional mean return on the JSE All Share index for a 131/2 year period from September 1995 to February 2009 was compared to the mean return after wins, draws and losses by the national sport teams. An event study approach was followed and four different statistical tests were conducted in order to test for a relationship. The results of the tests indicate the existence of a moderate win effect, with mean returns after wins being statistically significantly higher for the categories all sports combined, cricket and soccer.
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    Paying the high price of active management : a new look at unit trust fees
    (Bureau for Economic Research, 2018) Janse van Rensburg, C.; Krige, J. D.
    This study attempts to allocate the fund management expenses of actively managed South African general equity unit trusts between active and passive management portions, thereby calculating the implicit cost of active management. The active expense ratio of a unit trust can be calculated by using the published total expense ratio (TER) of the unit trust, its correlation relative to its benchmark and the expense ratio of a comparable exchange traded fund (ETF) tracking the benchmark of the unit trust. This study focuses on actively managed South African equity unit trusts available to the retail investor for the period March 2007 to February 2015. The active expense ratios of these unit trusts were calculated on the basis of a three-, five- and eight-year analysis period. It was found that the mean active expense ratios of the South African unit trust sample amounted to 4,14%, 4,29% and 4,25% respectively in the case of the three-, five- and eight-year periods. The comparable mean reported TERs amounted to 1,60%, 1,61% and 1,61% respectively. Thus the mean active expense ratio is more than 150% higher than the comparable mean reported TER in each period. A similar study was conducted by Miller (2010), investigating the active expense ratios of actively managed large cap American unit trusts. He found that the mean active expense ratio was 6.44%, compared with a mean TER of 1.20%. However, due to a higher degree of active management being employed by South African managers, the active expense ratios are lower than those of the American counterparts.
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    Perfect foresight portfolios on the Johannesburg stock exchange
    (AOSIS, 2017) Van der Merwe, R.; Krige, J. D.
    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. 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 PF portfolio is a buy-and-hold portfolio of all shares in a particular segment with weights at the beginning of the return period set to be proportional to the market capitalisation of the shares at the end of the return period. The excess return of the PF portfolio over the benchmark portfolio therefore is an estimate of the effect of unanticipated information on the return of the benchmark portfolio. It provides an estimate of the maximum annual amount of available alpha to all investors involved in that segment in a given year. In this study, the returns of PF portfolios were compared with the All Share, Large Cap, Mid Cap and Small Cap 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. Therefore a secondary aim was to investigate the correlation between cross-sectional standard deviation and PF excess return. It was found that a strong positive correlation (more than 90%) existed between cross-sectional standard deviation and PF excess return in all segments. In ascending order of annual PF excess return and average cross-sectional standard deviation the results for the segments were: Large Cap (8% and 29%), All Share (9% and 32%), Mid Cap (13% and 36%) and Small Cap (17% and 43%).
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    The price-to-book effect on the JSE : valuation disparities and subsequent performance
    (AOSIS, 2014) Du Toit, S. G.; Krige, J. D.
    The purpose of this study was to determine whether the relative out- or underperformance of a value portfolio versus a growth portfolio can be anticipated in advance by comparing a valuation difference multiple with the subsequent fiveyear relative performance of the value and growth portfolios. The valuation difference multiple was calculated as the median price-to-book value (P/B) ratio of the growth portfolio divided by the median P/B ratio of the value portfolio. Using monthly data for the period 1991 to 2011, this study found that in most instances the higher the valuation difference multiple, the higher the outperformance of the value portfolio over the subsequent five-year period, as compared to the growth portfolio.
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    Some perspectives on planning for retirement
    (Stellenbosch : Stellenbosch University, 2013-04) Krige, J. D.
    This paper explores two themes related to the financial aspects of retirement – real-age adjusted life expectancy and the financial survival probability of living annuitants. The first theme focuses on the development of a model to determine an individual’s adjusted life expectancy based on his or her real age as opposed to his or her calendar age. The model incorporates aspects such as gender, residing province, income, HIV status, ethnic background, weight, exercise, family illness history, stress, substance abuse and diet. The finding was that the real-age adjusted life expectancy of individuals retiring at age 65 may be as much as twice the life expectancy based on the latest South African actuarial mortality tables. This has significant implications for retirement planning. The second theme focuses on the financial survival probability of pensioners who have selected living annuities as their preferred retirement investment option. It addresses the question of how long a given amount of capital will be able to fund a living annuitant if the following parameters are known: expected retirement duration (i.e. years between retirement date and expected date of death), investment returns, inflation, annual withdrawal amount and initial capital amount. A model was developed that shows how retirement duration and different withdrawal rates change the probability of having sufficient capital in retirement for different investment scenarios.