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Stokvel is an African traditional credit system with initiatives that are typically situated in the informal economy and are easily accessible to alleviate financial challenges associated with micro and small enterprise financing, networking and product marketing. A wealth of research has provided an understanding of the entrepreneurial imperatives in this regard; however, knowledge of processes of setting up a successful Stokvel model to achieve this overarching benefit of scaling the initiative is still lacking. This study consolidates and examines the application and distribution of the model's four-building constructs established in a previous case study in a broader spectrum, providing requisite knowledge for its adoption in the contemporary entrepreneurial economy. Using a sample of 418 valid responses from the rural and urban areas of Limpopo Province of South Africa, findings reveal that the four building constructs (formation, operation, financial segment and disciplinary measures), are conformant to the study area, with no statistical evidence to support a difference between the ratings of the categories of location. This implies that Stokvel practices across areas of the province are similar, and a proper understanding of the building blocks that sustain its operations can enhance its applicability in other parts of South Africa, as well as other regions. The study, therefore, lays a foundation that can be used to develop a typical rotating Stokvel model for entrepreneurial success in Africa and beyond.

Positive-framed and negative-framed messages were delivered to examine the effect of framing on intertemporal decisions through lab experiments while holding the level of financial literacy constant. The three big questions adopted by Lusardi and Mitchell were utilized to assess the financial literacy of our subjects before they were asked to complete 20 incentivized intertemporal decisions. A small, delayed reward and a slightly bigger one were incorporated into the intertemporal decisions with a delay of 30 days. The ordinary least square (OLS) shows that the negative relationship between financial literacy and discount rates was held when the delayed reward was small. Interestingly, when the delayed reward became slightly bigger, their discount rates were reduced significantly with the negatively framed message. These findings suggest that the negatively framed message can motivate individuals to save for a greater return in the real world. Lastly, subjects with the highest level of financial literacy were not responsive to the magnitude effect, proving that a financial literacy program is essential to strengthen the individual's financial plan and reduce their discount rates in the developing country context.

Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka.

Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis.

Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model.

Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant.

Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.