The main objective of this paper was to establish which behavioural finance biases are associated with a certain level of risk tolerance and investor personality. Furthermore, the study aimed to indicate how these behavioural finance biases can influence investment decisions. Since behavioural finance is becoming more essential in the investment industry, further research within a South African context was regarded as necessary. Results indicated that investors with a low-risk tolerance level and a conservative investor personality are subject towards loss aversion and mental accounting biases. Investors with a high-risk tolerance level are mostly subject towards the self-control bias. The significance of this study will enable investment companies to more accurately profile their investors and to offer more refined investment options.

The satisfaction an individual experience with his or her financial position refers to financial well-being. Financial well-being can also be related to financial distress as its subjective indicator. The level of financial well-being may influence the financial decisions of investors and may vary according to their demographics. The aim of this study is to determine the level of financial well-being of investors and whether demographic variables play an influential role in investment decisions. The results from the study indicated that a significant difference exists between the financial well-being of male and female investors. Male investors were more likely to have an average or high financial well-being compared with female investors. A significant difference was also found between the financial well-being among different age categories. Older investors were more likely to have a low financial well-being compared to investors between the ages of 16 to 24.

Financial risk tolerance refers to the amount of risk a person is willing to take when making financial decisions. Previous researchers have found that demographic factors when used as independent variables to have an effect on the risk tolerance behavior of investors. Within this study, emphasis was given to gender and age within a sample of South African investors. Not much research on risk tolerance and demographics has been done in South Africa. Hence, an opportunity for further research within this field emerged. This study aimed to contribute towards the accurate risk profiling of South African investors based on their level of risk tolerance considering their gender and age. This study can be used as a future forecasting tool for investment companies to predict risk tolerance levels based on gender and age levels. Results from this study correspond to previous studies where male investors are more risk tolerant than female investors. A statistical difference was also found between male and female investors within the age categories of 35-49 years and investors older than 50 years. All age categories were found to be more risk tolerant for investors older than 50 years based on the binary regression.

This study examines the dynamics of equity market volatility and economic policy uncertainty (EPU) in South Africa during the COVID-19 pandemic. Using daily return data for sectoral indices and the JSE All Share Index (ALSI) from 1 January 2020 to 31 March 2022, the analysis explores both market-wide and sector-specific volatility responses. Univariate GARCH-family models (GARCH (1,1), E-GARCH, and T-GARCH) are employed to capture volatility clustering, persistence, and asymmetry across sectors. The results show that volatility was highly persistent during the pandemic, with sectoral differences in sensitivity to shocks: Consumer Staples and Financials were particularly reactive to recent news, while Health Care and Basic Materials were more stable. Asymmetric models confirm that market sentiment was predominantly driven by negative news, except in the Energy sector, where positive recovery signals played a stronger role. Correlation analysis further indicates that most sectors were moderately correlated with the ALSI, while Energy and Health Care behaved more independently. In contrast, both the ALSI and sector returns exhibited weak and negative correlations with the South African EPU index, suggesting that uncertainty did not translate directly into equity market declines. Overall, the findings highlight the importance of sectoral heterogeneity in volatility dynamics and suggest that during extreme market events, investors can mitigate downside risk by reallocating portfolios toward more resilient sectors.

The objective of the study is to examine the effects of investor sentiment on the Johannesburg Stock Exchange (JSE) index returns in bull and bear market conditions. Accordingly, this study uses monthly data to construct a new market-wide investor sentiment index and test its effects on the JSE aggregated and disaggregated index returns in alternating market conditions for the period March 2007 to January 2024. The findings of the Markov regime-switching model reveal that when the JSE is in a bull market condition, the JSE oil and gas sector returns and the JSE telecommunication sector returns are affected positively by investor sentiment. Similarly, in a bearish state, the JSE health sector returns and JSE telecommunication sector returns are negatively affected by investor sentiment. Collectively, the findings suggest that the effects of investor sentiment on JSE index returns are regime-specific and time-varying, such that they are dependent on the market conditions (bull or bear) and the type of JSE index (aggregated or disaggregated index). Accordingly, investors must consider this information to ensure resilient investment decisions and risk management strategies in sentiment-induced markets and alternating market conditions.

Operational risk constitutes a large portion of a bank’s risk exposure. Unlike other financial risks, operational risk is classified as a pure risk (only an opportunity of a loss), as it always leads to a financial loss for a bank. The failure to mitigate and manage operational risk effectively during past operational risk events has led to the demise of several banks and other financial institutions. Operational risk has the possibility to lead to other bank risk and to influence the perceptions of the banks’ main stakeholder group i.e. depositors. The rationale behind profiling depositors’ behaviour during operational risk events will contribute toward constructing a revolutionised risk management model. A better indication of how depositors react during operational risk events may lead to better prediction of withdrawal risk within banks. Primary data was collected from 417 depositors in Gauteng, South Africa, using a self-structured questionnaire. Statistical techniques such as correlation and `significance tests were used in the statistical analysis. A positive relationship was found between depositor likelihood to withdraw during operational risk events for two of the three variables; bank perceptive and behavioural finance biases. A negative relationship was found between depositor’s likelihood to withdraw and their risk tolerance level.