The stationarity of a time series can have a significant influence on its properties and forecasting behaviour, where the inability to render a time series to the correct form of stationarity can lead to spurious results. Although there are several different approaches to render a non-stationary time series stationary, few econometricians look past the first differencing method. This paper employs a novel process to determine whether using the correct form of stationary data will enhance forecasting accuracy. The results from this paper substantiate the hypothesis that the correct form of stationarity will outperform any other form of stationarity.

With more than 600 annual South African festivals to choose from, the ongoing sustainability of established festivals is uncertain. The rationale of sustainability usually rests on what renewable social, economic and cultural benefits the festival offers the community. However, changing visitor characteristics and economic difficulties putting more strain on the disposable income of households compel organizers and marketers to rethink their strategy in order to ensure the sustainability of festivals. This novel and exploratory study utilized a multistage DEA model to identify the presence of tendencies to overspend and budget mismanagement exhibited by visitors at the Innibos National Arts Festival. By identifying the sources of these inefficiencies, this study was able to formulate a framework that can guide organizers and marketers to develop price discounts or package combos that will ensure greater satisfaction which is a vital contributor to sustainability. The results accentuated the need to tailor these package combos to both male and female attendees, with the emphasis on improving satisfaction by limiting the tendencies to overspend that relate to paying for entrance fees, food and drinks.

Background: Based on the static mean-variance portfolio optimisation theory, investors will choose the portfolio with the highest Sharpe ratio to achieve a higher expected utility. However, the traditional Sharpe ratio only accounts for the first two moments of return distributions, which can lead to false portfolio performance diagnostics with the presence of asymmetric, highly skewed returns.Aim: With many criticising the standard deviation’s applicability and with no consensus on the ascendency of which other risk denominator to consult, this study contributes to the literature by validating the importance of consulting value-at-risk as the more commendable risk denominators for the Johannesburg Stock Exchange.Method: These results were derived from a novel index approach that produces a comprehensive risk-adjusted performance evaluation score.Results: Of the 24 Sharpe ratio variations under evaluation, this study identified the value-at-risk Sharpe ratio as the better variation, which led to more profitable share selections for long-only portfolios from a one-year and five-year momentum investment strategy perspective. However, the attributes of adjusting for skewness and kurtosis exhibited more promise from a three-year momentum investment strategy perspective.Conclusion: The results highlighted the ability to outperform the market, which further emphasised the importance of active portfolio management. However, the results also confirmed that active and more passive equity portfolio managers will have to consult different Sharpe ratio variations to enhance the ability to outperform the market and a buy-and-hold strategy.

Background: Using financial ratios is considered to be important when making informed judgments about investment portfolios. However, the ‘ideal’ set of ratios is an elusive notion on which the literature has failed to reach any consensus.Aim: This study attempts to identify to what extent so-called ‘non-financial’ measures can outperform ‘traditional’ financial and risk-adjusted performance ratios to explain future share returns for South African banks in a momentum investment strategy.Method: A multi-stage data envelopment analysis model was used in the study.Results: The results suggest that non-financial measures are able to explain up to 90% of banking shares’ future returns, which is a 30% to 40% improvement on that of traditional financial and risk-adjusted performance ratios. In identifying the ‘ideal’ set of ratios for the South African banking industry, this study also found that pure technical efficiency, the price-to-earnings ratio and the static omega ratio were able to explain up to an average of 83% of future banking share returns.Conclusion: The study contributes to the field of portfolio management in that both risk-adjusted performance ratios and non-financial measures can be used as short-term and long-term investment decision-making tools. Further to this, the ability to explain future returns to some extent implies that the South African banking industry may be time-varying-information efficient.

The traditional Capital Asset Pricing Model (CAPM) suggests that the minimum return required by an investor should be equal to the return of a risk-free asset (Reilly & Brown, 2003), which should be stable (Reilly & Brown, 2006), not influenced by external factors (Harrington, 1987), and certain (Bodie, Kane & Marcus, 2010). Evidence, however, suggests that risk-free asset returns vary (Brunnermeier, 2008), and that “there is really no such thing as a truly riskless asset” (Brigham & Ehrhardt, 2005:312). The pioneering studies of Mehra and Prescott (1985) and Weil (1989) only justified the size of the equity premium and risk-free rate puzzle but failed to provide a consensus on the specifications for the most ideal risk-free rate proxies. The results from this paper accentuated the problem of selecting a risk-free rate proxy, as all proxies under evaluation exhibited a level of risk and volatile returns. No regularities between the pre-, during and post-financial crisis regarding the choice of most ideal risk-free rate proxy were found. Overall findings suggested that the ideal proxies are the 3-month T-Bill rate and the 3-month NCD rate for the pre-, during and post-financial crisis periods, respectively.