This study is aimed at investigating the volatility dynamics and the risk-return relationship in the South African market, analyzing the FTSE/JSE All Share Index returns for an updated sample period of 2009–2019. The study employed several GARCH type models with different probability distributions governing the model’s innovations. Results have revealed strong persistent levels of volatility and a positive risk-return relationship in the South African market. Given the elaborate use of the GARCH approach of risk estimation in the existing finance literature, this study highlighted several weaknesses of the model. A noteworthy property of the GARCH approach was that the innovation distributions did not affect parameter estimation. Analyzing the GARCH type models, this theory was supported by the majority of the GARCH test results with respect to the volatility dynamics. On the contrary, it was strongly unsupported by the risk-return relationship. More specifically, it was found that while the innovations of the EGARCH (1, 1) model could account for the volatile nature of financial data, asymmetry remained uncaptured. As a result, misestimating of risks occurred, which could lead to inaccurate results. This study highlighted the significance of the innovation distribution of choice and recommended the exploration of different nonnormal innovation distributions to aid with capturing the asymmetry.

Questions regarding the specific factors that drive continuous cash allocations by investors into portfolios of actively managed funds, despite consistent underperformance, continue to remain an inexhaustive aspect of the literature that calls for further investigations. This study assesses the dynamic relationship between fund flow and performance of equity mutual funds in South Africa under different market conditions. The study employs a GMM technique to analyze the panel data of 52 South African equity mutual funds from 2006 to 2019. The analysis found that convexity is prevalent in the flow-performance relationship, where fund contributors in subsequent periods allocate recent underperforming and outperforming funds disproportionate cash. This finding is evident in the lack of significance in the past performance effects on subsequent fund flows. The study found that lagged fund flows, fund size, fund risk, and market risk drive subsequent fund flows under changing conditions of the general market and fund markets. Overall, it is posited that fund contributors and asset administrators adapt to prevailing market dynamics relative to trading decisions. As a result, this affirms the normative guidelines of the Adaptive Markets Hypothesis, leading to the conclusion that exogenous factors drive fluctuations in fund flows in South Africa.

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This study assesses the effect of fund-level and systemic factors on the performance of mutual funds in the context of changing market conditions. A Markov regime-switching model is used to analyze the performance of 33 South African equity mutual funds from 2006 to 2019. From the results, fund flow and fund size exert more predictive influences on performance in the bearish state of the market than in the bullish state. Fund age, fund risk, and market risk were found to be the most significant factors driving the performance of active portfolios under time-varying conditions of the market. These variables exert more influence on fund performance under bearish conditions than under bullish conditions, emphasizing the flight-to-liquidity assets phenomenon and risk-aversion behavior of fund contributors during unstable conditions of the market. Consequently, fund managers need to maintain adequate asset bases while implementing policies that minimize dispersions in fund returns to engender persistence in performance. This study provides novel perspectives on how the determinants of fund performance change with market conditions as portrayed by the adaptive market hypothesis (AMH).