Browsing by Author "Evans, Kathleen"

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    The determinants and predictability of South African listed property returns
    (2017) Ramjee, Anil; Evans, Kathleen
    This study investigates the determinants and predictability of listed property returns in South Africa based on the framework developed by Eugene Fama and Kenneth French. The study tests four asset pricing models, including the Capital Asset Pricing Model (CAPM) developed by Sharpe (1964) and Lintner (1965), the Fama and French (1993) 3-Factor model, a model which adds the South African Bond Index to the CAPM and finally a model which includes macroeconomic, market and firm specific factors. The empirical analysis makes use of macro-economic data and returns data of various portfolios of South African listed property stocks created based on a ranking of specific style factors. The style variables are size, momentum, liquidity, dividend yield, price to NAV, earnings yield, dividend growth, average cost of debt, loan to value ratio and the interest coverage ratio. The data was extracted from INET and the Muller and Ward (2015) data base which was subsequently updated by Shapiro (2016). The data sample extends over a 20-year period from January 1996 to December 2015. Ordinary least squares regression is used to determine the appropriateness of each of the four models. Furthermore, because these relationships change over time, a 5-year rolling regression analysis is used to understand the relationships over time. The results suggest that the Capital Asset Pricing Model, the Fama and French (1993) 3-Factor model and the CAPM plus Bond Factor model do not fully explain the patterns of expected return of the South African listed property index. However, the All Factor model is able to fully capture the pattern of expected return of the South African listed property index. Furthermore, the results suggest that the South African listed property sector is less volatile and therefore relatively less risky than the overall stock market. Furthermore, the evidence suggests that that listed property behaves more like bonds than equity over the sample period. The research provides empirical evidence of a positive relationship between South African listed property returns and size, dividend yield and momentum is found. In addition, it is found that South African listed property returns are negatively related to the price to net asset value ratio. This suggests that South African listed property tends to revert to a long term mean net asset value. The analysis of the performance of active trading strategies shows that once transactions costs are included none of the strategies are able to outperform a passive investment strategy. In addition, the study finds that there is no statistically significant difference between active and passive returns. Therefore, it is concluded that the South African listed property sector is efficient and profitable arbitrage opportunities should not exist.
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    Direct operating and portfolio management expenses: a case study of self storage facilities in South Africa within a global context
    (2017) Van Der Linde, Adriaan Nicolaas; Evans, Kathleen
    Self storage has become a globally recognised and specialised property investment. Valuation guidelines and annual Industry surveys are available for mature self storage markets worldwide, but currently there is no published South African guideline for self storage expense ratios in terms of total expenses, direct facility operating expenses and portfolio management expenses. These expenses, which are necessary for valuation, are difficult to obtain in the market compared to rental rates, which are publicly advertised to potential tenants. A case study approach was shown to be the applicable research methodology. It was then explained that the methodology consisted of four stages: The first stage describes the method of data collection from the valuation literature and international annual industry surveys. The second stage describes the method of data collection from the international self storage industry by analysing financial statements of international publicly listed self storage portfolios. The third stage describes the method of data collection from South African self storage portfolio case studies. The fourth stage describes how the data is to be analysed to arrive at an expense ratio guideline for South African self storage portfolios. The methodology was then carried out to answer the four research questions.
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    Effective selection of countries in sub-Saharan Africa for independent wind power producers using a multiple criteria decision analysis
    (2017) Gildenhuys, Enelge; Evans, Kathleen
    Subjective decision making can lead to results that are difficult to justify in cases where the outcome is unfavourable. This is the case in the wind energy industry where wind independent power producers (IPPs) assess new market entry opportunities. Decision analyses methods can assist decision makers when faced with difficult choices such as which market to enter. Multi Criteria Decision Analyses or MCDA is one of the most preferred of many different decision analyses methods. MCDA ranks a set of criteria in order of importance and then, based on the results, ranks alternatives. There are many MCDA methods available and the most often used include the analytical hierarchy process (AHP), multi-attribute utility theory (MAUT), preference ranking organization method for enrichment evaluation (PROMETHEE), elimination and choice translating reality (ELECTRE) and technique for order preference by similarity to ideal solution (TOPSIS). In this study a combination of MCDA methods are used to rank Sub-Saharan African countries based on preference for new market entry for wind IPPs. Nineteen different criteria were identified through a thorough literature review that were included in the analyses. The nineteen criteria were categorised into economic, technical, political and social criteria. The study was divided into two phases. In the first phase an industry expert survey was concluded and resulting from this survey the AHP was used to rank the criteria in order of importance. In the second phase PROMETHEE was used to rank seven Sub-Saharan African countries from most to least favourable for IPP market entry. The expert survey and AHP showed that political and economic criteria are considerably more important than technical and social criteria. Governments have the ability to change both the economic and political landscape and should do so if they want to attract wind IPPs. On the other hand, technical and social criteria are more difficult for governments to change but these do not have as significant impact on market attractiveness. The PROMETHEE model ranked South Africa as the most favourable market for wind IPPs to enter followed by Ethiopia, Namibia, Kenya, Mozambique, Nigeria and lastly Zambia. The top two countries both have very strong natural wind resources and South Africa is the only country with incentives specifically and exclusively for on grid renewable energy. The least favourable two countries, namely Nigeria and Zambia, have almost no wind resource and a weak economic environment. Future research can use MCDA methods, such as AHP and PROMETHEE, to assist in the evaluation of different market entry opportunities. These methods can also be adapted to investigate opportunities at country level i.e. analyse and compare different states/provinces with each other.
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    Reducing the property appraisal bias with decision support systems: an experimental investigation in the South African property market
    (2016) Sui Sang How, Jesse Jefferson; Evans, Kathleen
    Purpose: The valuation tasks for manual valuation are time-demanding and cognitively challenging. Behaviourists have observed that valuation accuracy and variations are mainly caused by human adaptive approaches called cognitive shortcuts. Of particular interest for valuation tasks is the susceptibility of decision makers to anchoring heuristics. The anchoring and adjustment approach is a mental shortcut which involves deliberate and conscious adjustment of values, known to be wrong but close to a right answer. Various studies have shown that valuers are prone to anchoring to asking price, previous estimate and other reference points. The incidence of valuation bias in the property market and the world is of concern. Few studies have used the decision-support tool to reduce property appraisal bias. The research purpose is therefore to determine the efficacy of the decision-support tool in reducing and eliminating property appraisal bias in the South African property market. Design/methodology/approach: Similar to previous behavioural studies, a controlled experimental study design was used. The experimental design is based on a previous German study that uses a self-written valuation software in a MS Excel package, adapted to the South African market. The software comprises two versions, a standard software and a decision-support software, which were administered to separate groups of novices and experts. Descriptive statistics and non-parametric testing were used to interpret the results. Findings: Consistent with other research on valuation accuracy and variations, the findings show that the valuation outcomes do not align with 'margin of errors' concept. Despite the results not being as robust as one would have expected, the study revealed that test subjects were susceptible to the anchoring effects and that use of a decision-support tool can help to reduce valuation variations. Practical implications: This study heightened the need to counter the effect of bias in valuation. The high variance among the experts group is of concern and should be addressed. Other forms of cognitive shortcuts used by valuers should be incorporated into the decision-support tool, and a similar test run for different valuation settings. The behavioural contentions should be discussed and presented to novices and experts.