Lilly Kamoet RAMIFICATIONS OF COVID-19 ON THE JOHANNESBURG STOCK EXCHANGE (JSE) AND THE NAIROBI SECURITIES EXCHANGE (NSE) Vaasa 2022 School of Accounting and Finance Master’s thesis in Finance Masters’ degree program in Finance 2 UNIVERSITY OF VAASA School of : Accounting and Finance Author: Lilly Kamoet Title of the Thesis: RAMIFICATIONS OF COVID-19 ON THE JOHANNESBURG STOCK EXCHANGE (JSE) AND THE NAIROBI SECURITIES EXCHANGE (NSE) Degree: Master’s degree in Finance Programme: Finance Supervisor: John Kihn Year: 2022 Pages: 62 ABSTRACT: The study sought to determine the effect of the Covid-19 pandemic on the Kenyan and South African financial stock markets. The two stock markets analysed in the research were Nairobi Securities Exchange (NSE) and the Johannesburg Stock Exchange (JSE). Events that were studied in this research to determine the impact on the stock markets was: the announcement of the first Covid-19 case in Kenya, announcement of the first Covid-19 case in South Africa and the announcement by WHO declaring Covid-19 to be a pandemic. The rise of the pandemic shook the major sectors that drive economic well-being of the society hence impacting the stock markets. Event study methodology was used in this research.The findings from the research revealed that the stock markets exhibited a significantly high volatility days after the announcement of the first case of Covid-19 in the country.The alarming progression of the pandemic also caused fear and panic among investors.In comparison to the developed economies, the healthcare system in the two countries were insufficiently equipped to contain the spread of the virus therefore causing rapid spread of the virus hence disastrous economic losses. The findings from the re- search contribute to the financial literature on the impact of Covid-19 on the stock market par- ticularly in the African markets. KEYWORDS: Covid-19, stock market, pandemic 3 Contents 1 INTRODUCTION 6 1.1 Background 7 1.2 Motivation 8 1.3 Previous studies 9 1.4 Purpose of the study 10 1.5 Research Questions and Hypothesis 11 1.6 Structure of the study 13 2 LITERATURE REVIEW 14 2.1 Past pandemic and epidemics 14 2.2 Financial and economic impact of covid-19 16 2.3 Impact of covid-19 on the stock market 19 2.4 Theoretical framework 22 2.4.1 Efficient market hypothesis 22 2.4.2 Random walk hypothesis (RWH) 23 2.5 Summary of the literature review 24 3 RESEARCH METHODOLOGY 26 3.1 Significance testing 30 3.2 Estimation window, event window, and event date selection 31 3.3 Nairobi securities exchange (NSE) 32 3.4 Johannesburg securities exchange (JSE) 32 3.5 Limitation of the study 33 4 DISCUSSION OF RESULTS 34 4.1 Overview of results 35 4.2 Impact of the announcement on key sectors 44 5 CONCLUSION 51 5.1 Conclusion for hypothesis findings 53 5.2 Recommendation for future research 54 6 REFERENCES 55 4 Appendices 61 6.1 Appendix 1. List of companies in NSE on 02.02.2022 61 6.2 Appendix 2. List of companies in JSE on 02.02.2022 62 Figures Figure 1.Event timeline for an event study. 12 Figure 2. Covid-19 pandemic and capital market impact flows 17 Figure 3.GDP growth annual percentage Kenya and South Africa 34 Figure 4.Real gross fixed capital trend analysis, South Africa. 35 Figure5.The average abnormal returns, cumulative average abnormal returns percentages, degree of responsiveness and volatility for the Johannesburg stock exchange (JSE) 10 days before and 10 days after the first announcement of Covid-19. 37 Figure6.The average abnormal returns, cumulative average abnormal returns percentages, degree of responsiveness and volatility for the Nairobi securities exchange (NSE) 10 days before and 10 days after the first announcement of Covid-19. 39 Figure7.The average abnormal returns, volatility, and cumulative abnormal returns percentages for both securities,10 days before and 10 days after WHO announced Covid- 19 to be a global pandemic. 42 Figure 8.The cumulative abnormal average returns for event 1 (when the first covid-19 case was announced in South Africa). 45 Figure 9.The cumulative average returns for the second event (WHO declaring Covid-19 to be a pandemic). 47 Figure 10.The cumulative average returns for the event 3 (Announcement of the first Covid-19 case in Kenya). 48 5 Tables Table 1.Early outbreaks and pandemics 15 Table 2.Covid-19 industry impact. 19 Table 3.Government policies to curb the spread of Covid-19 21 Table 4.Early research on Covid-19 impact on stock markets 22 Table 5.Descriptive statistics gathered from the MSCI Indices 36 Abbreviations COVID-19: Coronavirus Disease of 2019 WHO: World Health Organization NSE: Nairobi Securities Exchange JSE: Johannesburg Stock Exchange CMA: Capital Markets Authority SARS: Severe Acute Respiratory Syndrome 6 1 INTRODUCTION On December 31st, 2019, the first case of covid-19 is thought to have occurred in Wuhan, Peoples Republic of China. The covid-19 epidemic in due course progressed from a local- ized epidemic to a global ongoing pandemic and on March 11, 2020.The World Health Organization (WHO) stated covid-19 to be a global pandemic (WHO,2020). According to (Zhang et al,2020) the severity of the pandemic is comparable to the Ebola virus and the Zika outbreak in the Congo. The severity of the pandemic had an impact on the global economies, comparable to the 2008 financial crisis. One of the news that can cause a market crash is the introduction of current information according to market efficiency. Furthermore, when the stock market crashes the stock price declines causing a significant effect on the financial market (Chen 2021; Sornette 2017; Bierman1998). The security exchange markets are a general reflection of the eco- nomic conditions of a country, and it was impacted by the latest information about the pandemic causing destabilization of the socio-economic equilibrium (Zeren and Hi- zarci,2020). The different governments and multi-national organizations introduced im- posed lockdown restrictions and border closures to control the spread of the virus which negatively impacted the performance of firms. Baker et al. (2020) observed that the pan- demic lowers the activity of the security market and therefore the performance as well. The operations in the financial market have not been the same since the first case of Covid-19 reported in both the Kenyan and South African markets in March. The Johan- nesburg stock market plunged by 9.72 percent, Namibia stock the market fell by 8.81 percent, the Casablanca stock exchange recorded a decline of -6.70 percent, while the Nairobi stock exchange declined by 15 percent (Ozili and Arun, 2020). The impact of the ongoing pandemic on the economies have been the topic of study, in the financial mar- kets, however only few have focused on the African countries (Ozili and Arun, 2020). The study is thus of interest because it aims to investigate the impact of the ongoing pan- demic on the Kenyan and South African financial markets. 7 1.1 Background World Health Organization reported multiple cases of pneumonia caused by the novel coronavirus, which is categorized to be in the same group as SARS in December 2019 in Wuhan, China. The virus is spread to persons or animals through close direct contact with infected respiratory secretions of infected individuals. Infected persons’ have a loss of taste and smell but severe symptoms that require medical treatment include chest pains, breathing difficulties and speech difficulty (WHO, 2020). World Health Organiza- tion termed the virus covid-19 on February 11th, 2020. Medical personnel detected that the virus spreading at an alarming pace globally prompting the declaration of covid-19 a pandemic in March 2020. The pandemic caused panic in the global financial markets as it expanded at a relatively frightening rate. The rising number of daily infections, novel variations, and mortality cases the ongoing pandemic is continually fuelling health crisis (Adenomon & Maijamaa, 2020). African countries have been under pressure before the health crisis owing to in- sufficient health infrastructure and medical personnel (Lo, Bassene & Sene 2020). Ac- cording to WHO (2020), the pandemic severely impacted the healthcare system in Africa whereby the ratio of doctor to the patient was 1:985 and nurse to patient 1:3324. The GDP in African markets plummeted from 2.4 percent to between -2.1 percent and -5.1 percent in 2020 which is perhaps indicative of a recession (Bassene;Sene;& Lo, 2020). In the African context (Arun & Ozili, 2020) assessed that majority of the African govern- ment’ lockdown and quarantine policies were causing a significant financial crisis and perhaps leading to a recession. (Morales & Andreosso, 2012) discovered in their research that the stock markets are more interlinked, making it more probable that a crisis in one nation can readily spread across borders. The covid-19 pandemic harmed investors’ emotional well-being, gener- ating dread and terror and thereby impacting their investing decisions. The pandemic made investors to reconsider their investment alternatives. Investor behaviour is one of the most important elements influencing stock market performance. 8 According to research by (Donadelli & Riedel,2016; Zouaoui & Nouyrigat, 2011) stock market investors exhibit similar behaviours and reactions to information which influ- ences the stock market’s performance trend. However, (Takyi & Ennin, 2020) observed that investors in various nations respond differently to the pandemic. The risk-averse investors appeared to engage in panic selling worsening the financial market’s suscepti- bility. 1.2 Motivation Considering covid-19 is a new occurrence, there is currently minimal research on the impact of the pandemic on the African stock market. The existing research revealed that the security markets were undoubtedly influenced, however the magnitude of impact varied. The US stock index S&P 500 in March 2020 had dropped by 35% compared to February 2020 (Baker, 2020) but this differs from the Kenyan and South African markets. (Fernandes, 2020) explains that less research on the impact of the covid-19 pandemic on the underdeveloped countries are available due to paucity of knowledge on the virus and dependence on information on the SARS virus which is similar in origin. South African financial market was chosen for this study as it is one of the largest stock markets in Africa. The Kenyan stock market was chosen for the research as it was one of the biggest stock markets in the east African region. The African markets, like the world- wide financial markets, have been marked by increasing volatility during the pandemic (Arun & Ozili, 2020). Overall, the stock markets responded to the external shock created by the health crisis; however, the precise stock market response varies by country (Bassene;Sene;& Lo, 2020). It is vital to investigate the influence of the pandemic on these two stock markets since the findings give essential information for stock market participants, academics, and practitioners. 9 The threat of new variants is also prevalent and has an impact on the stock market; thus, it is important to understand how this influences the stock market performance. The study tries to explore how the financial market might be buffered in the face of a pan- demic, as well as how the investors and governments can reduce similar shocks in future. This research is also motivated by the need to comprehend and evaluate stock markets’ reactions and behaviours to new information. 1.3 Previous studies Previous research has focused on the various effects of the covid-19 on the economies of various countries. Baker et al. (2020) investigated covid-19 influence on the American stock market and compared it to prior outbreaks. Baker et al. (2020) discovered that the pandemic had a considerable negative influence on the stock market when compared to the earlier outbreaks. He et al. (2020) used the T-test and Mann-Whitney test to investi- gate the influence of the pandemic on the stock market in nine countries, including China, and discovered that there is a negative impact on the stock market, but only in the short run. Previous studies in industrialized economies reveals that the stock market reacts strongly to fresh knowledge about the virus. In comparison to previous epidemics such as SAR’s and Ebola the covid-19 pushed governments to implement stringent measures to pre- vent infections transmission resulting in stagnated economies (Szlezak;Reeves;& Swartz , 2020). The restrictions and lockdown imposed meant that the African economy would stall, affecting performance of the stock market. According to (He et al., 2020) during moments of economic uncertainty investors are compelled to invest in safe-haven stocks and hence consequently lowering the stock market prices thereby lowering market per- formance. (Ahundjanov;Akhundjanov;& Okhunjanov, 2020) carried out a study to find out how the stock market is impacted based on the financial information available to investors on google about the pandemic. The research findings showed that an increase in the search 10 caused about 0.38% to 0.069% decrease in daily financial indices. (Phan & Narayan, 2020) analyzed the impact of the pandemic on 25 countries and found that there was a pattern of overreaction in the early stages of the pandemic but as the days progressed and de- spite an increased number of cases there was a positive market response signalling cor- rection. Nonetheless, the pandemic has caused a negative stir there has also been an evolution of innovative ideas for the stock markets. 1.4 Purpose of the study The research will use an event study analysis research approach to determine the impact of the pandemic on the stock market, especially the South African and Kenyan stock markets. There is growing body of literature on the impact of the pandemic on the stock market, but there is little to none from the African countries. Stock performance is reli- able predictor of the country’s overall position, particularly from the financial and eco- nomic aspect. The study will contribute to the financial literature, especially those that explore the influence of disasters and crises on the stock market. The research findings will help governments alter their tactics and discover solutions to reduce the risks in the stock markets. Companies’ management is frequently interested in earning factors that may impact share prices since this is important for company valuations. A company investment man- agement must be aware of issues such as the onset of epidemics and pandemics which can have an impact on the performance of their equities in the stock markets. Under- standing the impact of covid-19 benefits the potential as it allows potential investors to make sensible and educated decisions on whether to buy or sell shares rather than act- ing out of fear. Investment managers would also be able to comprehend how to handle pandemic or epidemic without negatively impacting their firms’ stocks. 11 1.5 Research Questions and Hypothesis Any new information, whether favourable or negative, frequently has an impact on the stock market. The following question will lead the investigation of how the pandemic influenced the stock markets: 1. How did the the Nairobi Securities Exchange (NSE) and Johannesburg stock ex- change (JSE) stock markets react to the covid-19 pandemic over different event periods? Baker et al. (2020) discovered that, aside from the Spanish flu of 1918, covid-19 has had the biggest volatility in the stock market. Alfaro et al. (2020) reported that the stock mar- ket value declined in the early period of the pandemic. According to the number of con- firmed cases and death caused by the pandemic in 64 countries (Ashraf, 2020) found that stock returns fell as the number of cases escalated. Researchers (Anh & Gan, 2020) studied the impact of the pandemic in Vietnam before the lock-down and discovered negative impact on the stock market; nonetheless, there was positive impact during lock- down. Based on the outcomes of past study, the foundation for this research hypothesis is: H0: There is no impact of covid-19 on the performance of the Nairobi and Johannesburg stock exchange H1: Covid-19 had an impact on the performance of the JSE or the NSE. H0: Covid-19 had no economic impact on Kenya or South Africa. H1: Covid-19 had an economic impact on Kenya or South Africa. This study employs the event study approach. The event study approach is used to de- termine if the stock prices accurately represent market information available and to 12 explore the impact of certain events on the stock market (Binder, 1998). According to Mackinlay (1997) the phase in the event methodology are as follows: identify event se- lection, pick firms involved, calculate normal returns, calculate abnormal returns, and lastly calculate of statistical significance. The first stage in the event selection includes selecting the event window. (Mackinlay, 1997) suggests that the event window should be much longer than the selected event period of interest to the research for easier evaluation of the time around the occurrence. Additionally, the event window should not Overlap. According to (Benninga 2018) the event window timeline is best depicted in figure 1 below, which shows the estimation window, event window and post-announcement phase. Figure 1.Event timeline for an event study. (Benninga, 2008) The event window covers ten days before the event, event day, and ten days after the event. It is important to select an estimation for when the event occurred hence the reason for choosing to encompass the ten days before and ten days after the event. A 200-day estimation window is considered before the event window when calculating the normal returns before the event window (Vaihekoski, 2016). The first event date chosen for this study is the period for the study is 5th March 2020 when the first case of covid- 19 was reported in South Africa. 13 1.6 Structure of the study The research will be divided into five sections. The first segment is the introduction which will be followed by a review of the literature in the second chapter. The literature review focuses on past literature and gradually develops a theoretical framework for the study. The chapter discusses prior research findings on the influence of covid-19 on the stock market. The data methodology discussion follows later in the third chapter to eval- uate the desired data gathering technique and carry out the study utilizing the chosen research methodology. The third chapter analyses the equations used in event analysis and briefly discusses the methods limitations. In chapter four, the outcomes from the in- depth data collection are presented and interpreted. Finally, in the last chapter there is an analysis of the research findings to highlight opportunities and gaps for future inves- tigations. 14 2 LITERATURE REVIEW Covid-19 has created an unprecedent crisis producing financial markets shocks. This chapter examines at the extant literature on the African stock market and its relevance to the present covid-19 pandemic. Even though, the scale and duration of the pandemic are unknown the impact on the economy and specifically the stock market, is dependent on public health measures and policies imposed by various governments. The measure put in place are not intended to limit corporate operations, but rather to guarantee that business grow while also safeguarding the safety of employees and the society in general. However, there may be certain extremes in the measures that might cripple an economy and therefore it is critical to strike an appropriate balance. 2.1 Past pandemic and epidemics Covid-19 was officially declared a global pandemic by World Health Organization on March 2020.According to (Doshi, 2011) there is no one precise definition of a pandemic as it has evolved over time. A pandemic is a worldwide disease or an epidemic that spreads across international borders (Doshi, 2011). While exploring pandemic discus- sions, the most popular characteristics used to define them are high attack rates, geo- graphical spread, contagion, and severity. Economist such as (Nippani & Washer, 2004) investigated the impact of SARS on the stock markets in eight countries and discovered that considerable influence was experienced in the earlier days of the pandemic but only in a few stock markets. Recent study carried out by Icev and Marin (2018) on the impact of the 2014-2016 Ebola virus outbreak on the stock prices found that the impact was greatest for stocks of firms in West African countries that experienced volatility and ele- vated risk following the outbreak. Ferguson et al. (2020) observed that pandemics are not a new phenomenon since they have occurred in the past but only a handful have had a global impact. Covid-19 on the other hand is particularly unique in that it is one of the longest pandemic eras. There has been multiple pandemics over the course of the years but the 2000’s exhibited a high 15 rise of outbreaks and catastrophes compared earlier decades. Because of the rising num- ber of viral infections in animals and increased interaction with people the number of pandemics has grown (Madhav et al,2017). As seen in table 1 below, the pandemic out- breaks have persisted for lengthy periods of time while others have been brief, resulting in increasing mortality rates World Economic Forum (2020). Table 1.Early outbreaks and pandemics (World Economic Forum, 2020) Name Period Death toll estimate Antonine plague 165-180 5 million Japanese smallpox 735-737 1 Million Plague of Justinian 541-542 30 -50 million Black death 1347-1351 200 million Smallpox 1520- onwards 56 million Great plague of London 1665 100,000 Italian Plague 1629-1631 1 million Cholera 1817-1923 1 million Third Plague 1885 12 million (China & India) Yellow fever 1800 100,000-150,000 (US) Russian Flu 1889-1890 1 million Spanish flu 1918-1919 40 million Asian flu 1957-1958 1.1 million Hong Kong Flu 1968-1970 1 million HIV/AIDS 1981-present 35 million Swine flu 2009-2010 200,000 SARS 2002-2003 770 Ebola 2014-2016 11,000 MERS 2015-Present 850 16 The rising number of death tolls seen from the table 1 above are thought to have a neg- ative impact on the economy. According to experts, a typical feature of the previous pan- demics on the economy was more layoffs, decreased travel, and higher medical expenses. (Jonas, 2013). Covid-19 in comparison to past pandemics has had a larger influence on the global soci- ety. The pandemic consequences imposed a global lockdown to control the virus’s spread. The lock-down was beneficial to the health sector but detrimental to the finan- cial industry since it altered the supply and demand networks. The disruption led to a heightened financial turbulence and economic shock. The pandemics resulted in in- creased borrowing which resulted in high debt levels (Boissay & Rungcharoenkitkul, 2020). 2.2 Financial and economic impact of covid-19 The pandemic startled the financial markets and the global economy in general. Accord- ing to Barua (2020) the pandemic occurred in different phases as shown in figure 1 below. The economies were more affected in the initial stages than in the later stages. The de- mand and supply of products and services were impacted in the first two waves, and the impact was later seen in the stock markets in the fourth and fifth waves as shown in the figure 2 below. 17 Figure 2.Covid-19 pandemic and capital market impact flows (Barua,2020) According to Carlsson-Szlezak et al. (2020a) the pandemic has three major effects: direct impact, indirect impact, and supply and demand curve disruptions. Due to the lock-down measures put in place by the government to restrict the spread of the virus the direct consequence was lower consumption of goods and services. Due to the uncertainty of the length of the pandemic economies have seen higher savings and less spending and this has an indirect effect on the economy. The demand and supply of products is af- fected due to the travel bans imposed and the increased unemployment rate. Since the stock markets are intertwined, the negative effects of the pandemic might have a cascading effect. Research carried out by Baldwin (2020) revealed that unemployment caused by the pandemic impact’s household savings and consumption levels which sub- sequently affects investment and reduces capital stocks. Gourinchas (2020) argues that whether there were containment measures in place or not the pandemic would have still caused a recession as enterprises would not have completely understood how to manoeuvre in the pandemic. 18 (Carlsson-Szelezak;Swartz;& Reeves, 2020) created the shock geometry to describe the numerous types of economic recoveries following an economic shock such as the pre- sent pandemic. The study classified the recovery into three unique types of shapes V- shape, U-shape, and L-shape. The V-shape indicates that output is shifted but growth is unaffected since there is a speedy return to pre-crisis levels. The U-shape on the other hand signifies that out drops but does not return to its pre-crisis growth path. Finally, the L-shape where there is negative output and decline in the growth rates. Ozili and Arun (2020) investigated the influence of social distancing measures estab- lished during the epidemic on the economic activity and stock market indices in Nigeria. According to their findings, increasing lock down periods and foreign travel restrictions have a detrimental influence on the economic activity as well as closing and opening stock prices. Internal travel restrictions and tighter fiscal policies on the other hand pos- itively boosted the economic activities by encouraging investors to spend their money on local enterprises such as tourism. Al-Qudah and Houscine (2020) discovered a negative correlation between the covid-19 and the daily stock returns in six World Health Organization (WHO) areas. The study dis- covered that an increase in the number of instances each day and had a negative influ- ence on stock returns and caused the stock market to fall. The study’s findings also found that the stock markets had the most negative impact when the pandemic was first re- ported, and this was the attributable to investor’s fear of the pandemic. Kumar and Kumara (2020) conducted research to examine the impact of covid-19 during the pre and post covid-19 period on the stock market and equity market growth in India. The results found that stock in the tourism, entertainment, and oil and gas industries were severely impacted, while IT, healthcare, and telecom companies were positively impacted. The negative impact recorded a decline of about 40% which is a significant dip in the stock market. 19 2.3 Impact of covid-19 on the stock market Although the covid-19 began in China, the influence on the stock market is seen inten- tionally due to China’s development of trading links with major nations. The stock market suffered its largest loss since the 2008-2009 financial crisis, when there was a global re- cession. The first two cases of the covid-19 reported in brought the main African stock exchanges to a halt. The Johannesburg stock market plummeted by 9.72 percent, Namibia stock exchange declined by 8.81 percent, Casablanca stock exchange lost by 6.70 percentage, Nairobi stock exchange sank by 15 and the Nigerian stock market fell by 3.72 percent (Arun & Ozili, 2020). The impact on the first announcement of Covid -19 case according to statis- tics indicate a sharp negative decline in the stock markets on the same day or a day later. Although, the impact of the pandemic on the stock market is severe, the degree of dam- age on various industries in the stock market varies. As a result, some industries excelled in e-commerce while others suffered, as reflected in stock prices. The influence may be classified as given in table 2 below (Mazur et al. 2020). Table 2.Covid-19 industry impact. (Mazur et al. 2020) Major decline in FDI Minimal decline in FDI Growth in FDI Tourism Agri business eCommerce Entertainment Consumer goods Digital technology Retail IT Cybersecurity Luxury goods Automotive Biotechnology Aviation Logistics Healthcare Real estate Pharmaceuticals Renewable energy Coal, oil, gas Financial services Research and Development 20 The rise in confirmed infection and mortality cases caused by covid-19 both within and outside of China demonstrated that the wider the spread the greater the volatility in the stock market Albulescu (2020). Markets typically overreact when investors are bom- barded with new information. Investors are often more sensitive to fresh information, and their perception of the information influences their investment behaviour. When the covid-19 pandemic began, African markets were among the last to be affected. Due to other continents being impacted by the pandemic earlier the trade relationship for Africa with the continents affected export market. Inversely when the infection curve began to lower in the foreign regions and reasonable economic strategy were formulated, for example stimulus package offerings, to counter the effects this was not the case for Africa. The initial attempt to restrict the transmission of the virus was unsuccessful due to a lack of adequate healthcare facilities and resources, resulting in a greater spread of the infection across areas. The rapid transmission on the virus meant that the higher the financial volatility in the stock markets. Financial researchers such as He et al. (2020) analysed the impact of covid-19 on the Vietnam financial market reported that stocks that were negatively impacted were trans- portation, mining, electricity and heating and mining while manufacturing, information technology, healthcare and education were positively impacted. The first reported case of the covid-19 measured using event analysis showed that stock markets in selected 30 countries experienced a downwards trend, increased volatility, and market illiquidity (Bash 2020). To curb the spread of the virus, many governments introduced policies as shown in table 3 below. The measures that had severe impact on the stock markets were travel bans, border closure and lockdowns. 21 Table 3.Government policies to curb the spread of Covid-19 (Cheng et al. 2020) Type of policy Total number of policies No. of countries imple- mented the policies Restriction of non-essential busi- ness 1855 135 School closures 1583 169 Quarantine/lockdowns 1102 161 External border restrictions 1064 186 Mass gathering restriction 575 159 Social distancing 518 127 Internal border restrictions 313 111 Curfew 172 91 Health testing 283 98 In research done by Baker (2020) on the impact of the restriction on the stock market found that negative results as the main impacted industries were service oriented and in addition the lockdowns caused deterioration of liquidity and market stability. However, in countries where there were stimulus packages offered boosted the stock market long- term investment but there was little significance for the short-term investments. The earlier reviewed literature on the impact of the pandemic on the stock market have shown negative impacts. However, it is key to note that even though the stock market is highly correlated there can also be differentiating results of the pandemic as the stock markets have different structures. Additionally, actions taken by different companies in the stock market to counter the effects of the pandemic can affect the performance of the stock. The table 4 below highlights the different literature that has been studied so far with regards to the effect of covid-19 on the stock markets and their result findings. 22 Table 4.Early research on covid-19 impact on stock markets (Ashraf,2020) Authors Country Results Al-Awadhi et al. (2020) China Negative impact Shen and Zhang (2020) China Negative Thorbeke (2020) USA Negative, positive- e-entertainment and IT Baek et al. (2020) USA Positive and Negative Alam et al. (2020) India Negative pre-lockdown, positive post lockdown Kumar and Kumara (2020) India Positive and Negative Ozili and Arun (2020) Nigeria Positive and Negative 2.4 Theoretical framework 2.4.1 Efficient market hypothesis Eugene Fama shaped the efficient market hypothesis, which has been accepted and ex- panded by various economist throughout the years. According to the theory, all infor- mation is available to investors and the security markets reflects this. According to Fama (1960) buyers are of the opinion that the security price is generally greater than the pur- chasing price, whereas sellers assume the opposite. The investors psychology is also im- pacted by the belief that an investment judgment made by a prominent investor is de- pendable, resulting in herd-like behaviour in investing decisions. The efficient market theory is classified into three types: strong, semi-strong and weak. The information supplied influences the stock prices, but there is no assurance of beating the market. There are three main requirements that must be satisfied according to Fama (1960): There are no transactional cost, all information is freely available to market par- ticipants at no cost and market participants agree on how current information affects stock prices. 23 In the strong form, it is presumed that the stock prices reflect all the information availa- ble to both the public and private investors and therefore the stock market cannot be defeated. The semi strong form encompasses published historical information that in- vestors can access and analyse the trend to make an investment based on the provided information available. There is no unique information in the weak form that can help investors estimate future prices. In the most basic form, a technical analyst would com- pile all relevant historical data to forecast trend. According to Malkiel (2003) in the early 2000’s economist felt that the future stock price was predicted based on stocks basic qualities and determinants. The school of thought led many individuals to assume that they could outperform the stock market and earn higher profits than the market. However, in subsequent years, behavioural finance econ- omist disputed the assumption that individual investors might make more than the stock market. 2.4.2 Random walk hypothesis (RWH) According to random walk hypothesis, the market adapts new information and any de- viations from the inherent value are random. According to the hypothesis the present market price of a certain stock in unconnected to the prior market-price trends. The idea was to investigate the link between chance and the exchange market. Stock prices were seen to follow a random walk, which was a sign of irrationality and not in accordance with market efficiency. According to random walk theory share prices are erratic and unpredictable, moving in any direction from their existing location (Sandev, Metzler & Chechkin, 2018). Due to unpredictability of stock projections, investors are at a loss as to which investment possibilities to pursue. The theory is considered for this study to understand the changes in the security prices during the covid-19 pandemic in the NSE and JSE. 24 2.5 Summary of the literature review Covid-19 has been has had impact on several different industries both in the JSE and NSE equity markets. Travel, education, hospitality, and entertainment have all been dis- rupted by the previously stated lockdowns and border closures put in place to prevent spread of the virus. The ideas employed in this research serve as a guide in determining the impact of share price variations. Since covid-19 did not originally originate from Kenya or South Africa there should have been better measures in place to counter the effect of the pandemic before it im- pacted the security exchange. However, this was not the case as the pandemic seemed to affect China only and it was not anticipated to spread globally. In China, according to Al-wadhi (2020) the pandemic caused a detrimental impact on the stock market. The reaction in the Chinese stock market was expected as it was the hub where the virus began. As observed by Ozili (2020) the implemented lockdown measure adopted by African countries, with no government subsidy assistance, particularly for the non-formal and small and medium sized business caused a heavy financial strain on the economy. The study had focused on the effect of the pandemic on the general economic performance in the African countries. Adenomon and Maijamaa (2020) observed that the pandemic had negatively impacted the Nigerian economy and the share prices also became vola- tile and this was largely attributed to oil market crush, therefore the results cannot be conclusively replicated in the Kenyan and South African markets. 25 During the 2007 post-election violence and the 2008 financial crisis, the NSE had nearly identical stock price movement to the pandemic (Asongu, 2012 & Rotich 2013). The study established that the unsettling election scenario produced uncertainty in the stock market therefore lowering the performance of the NSE substantially. The 2008 fi- nancial crisis also evidenced the stock market being affected by external factors. Ac- cording to a comparable analysis conducted by (Arguile,2012), the JSE was likewise hit by the 2008 financial crisis, but only defensive stocks were able to survive the obsta- cles. 26 3 RESEARCH METHODOLOGY This section outlines the research design used in the research and the data collection methods used to ensure its reliability. It is critical to select the appropriate study design for the investigation to achieve accurate outcomes. Leavy (2017) research design serves as structure and directs the inquiry targeted at addressing the research questions. The data for this study has been primarily collected from Bloomberg database with addi- tional information obtained from yahoo finance, Johannesburg stock exchange (JSE) and Nairobi Securities Exchange (NSE) websites. The research will adopt event study technique. An event window of 10 days is chosen, and the estimation window of 250 days is chosen to be used for this study. It is important to select an estimation for when the event occurred hence the reason for choosing to encompass the ten days before and ten days after the event. Economist such as Singh (2020) in researching the impact of covid-19 outbreak on the stock markets of G20 coun- tries used event study methodology to evaluate abnormal returns (AR’s) and panel data regression to explain the AR’s. The research will apply similar approach and focus on the South African stock market because it is one of the biggest stock markets in Africa and one of the countries highly affected by the pandemic. Similar strategy is used for analys- ing the Kenyan stock market is likewise one of the main stock exchanges in Africa and was also highly impacted by the pandemic exhibiting a drop of 15% in returns. The event research technique assumes that markets are efficient and tries to find abnor- mal returns produced by specific occurrences. It looks for semi-strong form market effi- ciency, which asserts that all publicly relevant information is already included into a stock’s valuation. Event study according to Mackinlay (1997) indicates that there are nu- merous ways to conduct an events study, but the underlying principle stays the same. The approach is used to examine whether the prices accurately represent the infor- mation available in the market with regards to the pandemic and assess the impact of the event on the stock prices. The format that would be followed in the study is to specify the event, estimate the abnormal returns, group the abnormal returns, and analyse the 27 findings. To study the impact of a certain event on stock prices the abnormal returns need to be calculated by taking the difference of actual returns and expected returns. For company 𝑖 and event 𝑡 the abnormal returns are: 𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸(𝑅𝑖𝑡/𝑋𝑡), (1) Where, 𝐴𝑅𝑖𝑡 is the abnormal returns of the investigated stock index 𝑅𝑖𝑡 is the actual stock returns on the event window day t 𝐸(𝑅𝑖𝑡/𝑋𝑡) is the normal returns for the period t. There are several methods to calculate the normal returns including mean adjusted model, market-adjusted models, and market model (Wells, 2004). The mean adjusted model employs the daily mean return from the estimation window and the average may be compared to the realised market returns. The constant mean return model computes the normal return by averaging the returns. The market model considers the beta which shows the stock risks in comparison to the market risk. As a result, when the beta equals one, it shows the average risk, and beta over one suggests a bigger risk, while beta below one indicates a smaller risk. A risk-adjusted model is the capital asset pricing model (CAPM) (Bowman, 1983). Mackinlay (1997) discovered that normal returns may be determined using CAPM or ar- bitrage pricing model (APT), where CAPM calculates normal stock returns with stock co- variance with the market portfolio and APT models normal returns using a linear combi- nation of risk components. The market model is as follows: 28 𝑅𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖𝑅𝑚𝑡 + 𝜀𝑖𝑡 𝐸(𝜀𝑖𝑡 = 0) 𝑣𝑎𝑟(𝜀𝑖𝑡) = 𝜎𝐸 2, (2) Where, 𝑅𝑖𝑡 is the stock returns on the period t, 𝑅𝑚𝑡 is the market portfolio returns on the period t and 𝜀𝑖𝑡 is an error term which is assumed to be zero disturbance 𝛼𝑖, 𝛽𝑖and 𝜎𝐸 2 are the market model parameters. According to Mackinlay (1997) the market model has the advantage of reducing the variance of abnormal returns and increasing the capacity to observe the influence of events on stock prices. The abnormal return is calculated using the market model as follows: 𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 - 𝛼𝑖 − 𝛽𝑖𝑅𝑚𝑡 (3) Where, 𝐴𝑅𝑖𝑡 is the abnormal return for stock 𝑖 in the event date 𝑡 𝑅𝑖𝑡 is the actual stock return for the stock 𝑖 in the event date 𝑡 The abnormal average returns are calculated as follows 𝐴𝐴𝑅𝑡 = 1 𝑁 ∑ 𝐴𝑅𝑖𝑡 𝑁 𝑖=1 , (4) 29 Where, AARt is the average abnormal returns and N is the number of observations. The companies can be classified and sorted for purposes of analysing the findings. By computing the cumulative abnormal returns the abnormal returns are averaged across the event window. The cumulative average returns are the total of the abnormal re- turns across the time under consideration. As a result, it is computed as follows: 𝐶𝐴𝑅𝑖(𝑡1, 𝑡2) = ∑ 𝐴𝑅𝑖𝑡, 𝑡2 𝑡=𝑡1 (5) Where 𝐶𝐴𝑅𝑖(𝑡1, 𝑡2) is the cumulative abnormal returns in a specific period. The cumulative average abnormal returns can be measured by calculating the cumula- tive abnormal returns for each security and aggregated over time. It is calculated as shown in the below equation 𝐶𝐴𝐴𝑅(𝑡1,𝑡2) = 1 𝑁 ∑ 𝐶𝐴𝑅𝑖 𝑁 𝑡=1 (𝑡1, 𝑡2), (6) Where, 𝐶𝐴𝐴𝑅(𝑡1,𝑡2) is the cumulative average abnormal returns in a specific period. In this study the statistical significance test is also vital. Various set statistics can be used to test the significance. Vaihekoski (2016) the simplest test statistic for average abnormal return is as follows: 𝜃1 = √𝑁 ×𝐴𝐴𝑅𝑡 √𝜎2(𝐴𝑅𝑖𝑡) ~𝑁(0,1), (7) 30 Where, N is the number of observations 𝐴𝐴𝑅𝑡 is the average abnormal returns 𝜎2 is the variance 𝐴𝑅𝑖𝑡 is the abnormal returns. For the cumulative abnormal returns the test static is ∫ 1 = 𝐶𝐴𝑅(𝑡1𝑡2) √𝛿2(𝑡1,𝑡2) ~𝑁(0,1), (8) Where, 𝐶𝐴𝑅(𝑡1𝑡2) is the cummulative abnormal returns in a certain period. The vari- ances in the formula denominators are calculated with 𝜎(𝑡1, 𝑡2) = 1 𝑁2 ∑ (𝑡2 − 𝑡1 + 1)𝜎 2𝑁 𝑖=1 (𝑡1, 𝑡2) (9) 3.1 Significance testing It is important to determine the significance level when determining the significance of the results. The purpose of identifying the significance level is to determine the risk level. The significance level that is generally accepted is 0.05, 0.01 and 0.001 (Heikkilä 2014, 204). 31 3.2 Estimation window, event window, and event date selection The event of interest in this study is the impact of covid-19 on two African stock markets namely the Johannesburg securities exchange and Nairobi securities exchange. Three event dates were chosen for the study as they are significant dates when the Covid-19 first case was reported in each country. I. Event 1 March 5th, 2020: Officials announce the first case of covid-19 in South Africa. II. Event 2 March 11th, 2020: WHO declares covid-19 a pandemic. III. Event 3 March 15th, 2020: Officials announce the first case of covid-19 in Kenya The research estimating window is 250 days before the event window. Overall, the data period covered ranges from 14th March 2019 to 11th March 2021. The 10 days before the event date will be studied with sensitivity analysis due to the unpredictable nature of reporting day. An examination of this period will allow the elimination of any inaccura- cies that would impact the findings discovered. Parameters that are not changed by the event’s returns are designed to ensure that the event window and estimation window do not overlap. The adjusted stock closing price will be used to calculate the stock’s his- torical returns. The trading days chosen for the sample were at least 250 days. However, for trading days that were during holidays, the next day data was considered. The companies that were listed in the securities exchange but did not have any trading days were also eliminated from the study. A sample size of 60 companies was chosen for the study from each of the securities exchange. 32 3.3 Nairobi securities exchange (NSE) Kenya’s only securities market is the Nairobi Securities Exchange (NSE), which was estab- lished under the societies Act of 1954. The creation of the securities market was in- tended to offer an alternative source of money and to distribute available resources. In the later phases, the governments direct interest in the exchange progressively faded subsided and was delegated to the private brokers. As a result, the Capital Markets Au- thority (CMA) was created, and its goal is to bring the government into the market. The security market comprises 62 corporations listed from multiple industries whose shares are traded on the NSE. The NSE is tasked with regulating the issuers, enforcing market policies and surveillance, supervising derivative markets, and reviewing current existing rules being recognized as a self-regulatory association. According to (Odhiambo, 2020) the NSE-20 share index has been declining since March 2020 indicating a poor performance of the underlying firms share prices. The fall in value was caused by inves- tors selling their shares because of the pandemic. Analysts discovered that foreign inves- tors were the biggest net sellers during covid-19, which had an influence on the securi- ties exchange since they accounted for the bulk of the daily business activity. 3.4 Johannesburg securities exchange (JSE) Johannesburg stock exchange founded in 1883 is one of Africa’s oldest stock exchanges. In terms of market value, it is the 19th largest stock market in the world and the largest in Africa (JSE,2020). It has been in business for nearly 125 years, dealing with financial products. A committee of stockbrokers with full voting rights directs the JSE and deter- mines management decisions. The JSE has also developed from a conventional floor- based stock trading market to contemporary stock exchange that provides access to elec- tronic trading, clearing, and settlement of stocks, derivatives, and other associated fi- nancial instruments (JSE,2020). The JSE index covers around 99 percent of the market capitalization and includes over 350 firms listed. The period from 2011 to2013, the trade value fell, which can be ascribed to the 2008 global financial crisis and the Eurozone debt 33 crisis (ASEA yearbook 2012:2013). The JSE has around 32% overseas enterprises and the remainder are indigenous firms. The JSE is made up of a diverse group of investors. 3.5 Limitation of the study The covid-19 being an unexpected pandemic caused multiple uncertainties, especially in the financial markets. The research study aimed at filling the literature gap in the finan- cial markets with regards to the impact of covid-19 on the financial markets there were a handful of literature with regards to the African markets. The study was limited to event study methodology which studies the short-term events and not long-term events. The covid-19 also being an ongoing pandemic the study was limited to the earlier stages of the pandemic and its effects. The effects of the pandemic on the financial markets were significant and may have overshadowed other events that affected the stock mar- ket during the same period. The study is limited to two stock market only and during the first wave of the pandemic. The pandemic is an ongoing phenomenon, and it is con- stantly affecting the stock market, therefore it is difficult to conclude the behaviour of the stock market conclusively. Due to the pandemic being a recent occurrence, there is relatively scarce literature for the subject, allowing for a careful comparison of the findings to developed markets ra- ther than developing and emerging countries. The event study methodology poses a challenge as the event day may be difficult to identify. It is also challenging to distinguish one event from another since they may occur during the same period. Since the event research technique considers only short-term reactions to stock markets movements ra- ther than long-term repercussions, doing a meaningful research study would need shift- ing the emphasis from a single announcement to a huge dataset over the course of the pandemic. 34 4 DISCUSSION OF RESULTS This chapter discusses the findings of the study. The results of the event are presented and an evaluation of the reaction of the share prices to the covid 19 announcement is analysed. GDP GROWTH (ANNUAL PERCENTAGE): SOUTH AFRICA AND KENYA Figure 3.GDP growth annual percentage Kenya and South Africa (World Bank,2020) The above figure 3 shows that the GDP for both Kenya and South Africa had recorded a significant decline from the onset of the pandemic. In 2018 GDP growth for Kenya was 5.63% while South Africa was 1.49%, while in 2019 the growth recorded for Kenya and South Africa was 4.98% and 0.11% respectively. However, in 2020 there was negative GDP growth for both countries with Kenya reporting -0.32% and South Africa at -6.432%. 35 Figure 4.Real gross fixed capital trend analysis, South Africa. (OECD Economic Survey, 2020) The figure 4 above shows the fixed capital trend for South Africa and key factors that influenced the trend. The periods that the South economy experienced a decline almost like the 2020 was during the sanctions-imposed period, election period, the east African crises and global financial crisis period. The reaction is an indicator that markets are in- fluenced by introduction of new information. 4.1 Overview of results The table below shows the descriptive statistics gathered from selected MSCI indices. The indices chosen provides a broad daily overview of the data for the different sized companies and sectors across Emerging Markets and Frontier markets. The MSCI ACWI+Frontier IMI indices, MSCI ACWI mid cap, MSCI ACWI+Frontier small cap indices were used to analyze the broad impact of covid-19 on the African markets. Eight indus- try-level indices were also used to gather for the data findings. The emerging markets indices are considered in this study as South Africa is part of the emerging markets while Kenya is part of the Frontier markets therefore frontier market indices were also consid- ered. 36 Table 5.Descriptive statistics gathered from the MSCI Indices The analysis of the results reveals that indeed the news of the pandemic caused different reactions from the different industries. From the table above results indicate that indus- tries such as finance and technology were the most volatile, while small and mid-cap companies were also more volatile as compared to the large cap companies. It could be argued that the small and mid-sized companies are expected to react impulsively to bad news as compared to large sized companies. Small and mid-size companies were notably deemed to be high risk and illiquid and therefore financial institutions would avoid issu- ing out credit to these institutions as compared to large cap companies. The figure 5 below shows the analysis for event 1: announcement of first covid-19 case in South Africa. The figure reports the average abnormal returns, cumulative average abnormal returns percentages, degree of responsiveness and volatility for the Johannes- burg stock exchange (JSE) 10 days before and 10 days after the first announcement of covid-19. 37 Figure 5.The average abnormal returns, cumulative average abnormal returns percent- ages, degree of responsiveness and volatility for the Johannesburg stock ex- change (JSE) 10 days before and 10 days after the first announcement of covid- 19. 38 From the results above day -1 had the highest average returns of 1,789% followed by day -9 which had a relatively high positve average return of 1,328%. Event day 1 had the lowest average returns of -3,651%.The average return for the day 0 announcement day was – 2,914%. The days -5 to -1 prior to the announcement period had rather positive average returns compared to the days after the announcement that had mostly negative average returns.This is an indication that the announcement of the covid-19 had a negative impact on the returns. The results indicate that on prior days before the announcement of covid-19 the market had positive average returns as compared to after the announcement where there were negative returns. The semi-strong form of efficient market hypothesis can therefore be rejected since the results indicate that prior market history trend cannot be used to pre- dict future trend of the market. The trend of the average returns from the results under efficient market theory can be deemed to be a weak efficient market since there is no predictability of the trend, as the market behaves in a rather independent manner. The cumulative average returns in the event window were -6,191%. The investors who had invested within the window period made significant loss. However, a closer look at the period between day -10 to -1 the cumulative average return was positive 6,015%. Therefore, an investor would have made a profit prior to the event day 0. The cumulative average returns seemed to have seemed to have had a stable trend from the beginning of the event window but quickly started dropping after the announcement day. The volatility level on event day 0 announcement day was the highest at 5,687%. The behaviour can be expected since the trading volume and return volatility are indication of information stream to the market increases during major announcement in this case Covid-19 announcement. The figure 5 above show a high fluctuation in the volatility trend. The behaviour is consistent with finding carried out by Bodie (2009) which argues that volatility greatly varies depending on new information, moreso, since new infor- mation influences investors intrinsic behaviour as well. 39 The figure 6 below shows the analysis for event 3: announcement of first covid-19 case in Kenya. The figure reports the average abnormal returns, cumulative average abnormal returns percentages, degree of responsiveness and volatility for the Nairobi securities exchange (NSE) 10 days before and 10 days after the first announcement of covid-19. Figure 6.The average abnormal returns, cumulative average abnormal returns percent- ages, degree of responsiveness and volatility for the Nairobi securities ex- change (NSE) 10 days before and 10 days after the first announcement of covid-19. 40 The results reveal that day-6 had the highest abnormal average returns 1,120% while day -3 had the lowest abnormal returns of -2.110%. The days that had relative positive average abnormal returns were on days -10, -5, -2, -1 before announcement day 0 and after announcement day 7,8,9 and 10 reflected positive average abnormal returns. Ob- serving the results closely around the event announcement period there is a slightly pos- itive average abnormal return of 0,073% on day -1 and on day 0 there is a negative ab- normal average return of -0,357% and day 1 follows the negative trend of returns with - 0,042%. The observation is consistent with the finding from Dey and Radhakrishna (2008) which indicated that investors who rely on earning announcement earn weaker positive or neg- ative abnormal returns a day before, day-1 and on the day after day 1 of the announce- ment day, day 0. Overall, observation of the abnormal average returns of the announce- ment day 0 and considering the trend reaction before and after announcement of covid- 19 strongly indicate that the Nairobi securities exchange indeed reacts to new infor- mation. The stock price change and change in average returns are a key confirming indi- cator. The cumulative abnormal average returns at day 10 was -2.457%. An investor who had investor during this 21-day period would have made significant negative returns on their investments. The announcement had increased the negative performance of the NSE evidenced by the increased negative cumulative average returns. The cumulative aver- age returns from day 0 to day 6 was -4,50% and day 6 had the highest negative CAAR in the event window. The trend indicates that the NSE was behaving bearish. Research done by Durnev (2011) on the impact of political elections on the stock market found similar results that announcements impact stock performance and caused the NSE dur- ing the 2008 post-election violence to experience bear market tendencies. 41 The volatility of the market also increased around the announcement period. The vola- tility on day-2 was 1,563 %, day -1 was 1,777%, day 0 was 2,889% day 1 was 3,875% and day 2 was 3,987%. The increased volatility could be attributed to the sensitivity of inves- tors to the announcement of covid-19 case. These finding is in comparable to findings from research study done by Lusinde (2012) on the impact of general elections on vola- tility of stock markets that revealed that volatility increases around the announcement period. The figure 7 below shows the comparison of event 1 and event 3 to the announcement of event 2. The results show analysis of the average abnormal returns, volatility, and cumulative abnormal returns percentages for both securities 10 days before and 10 days after WHO announced covid-19 to be a global pandemic 42 Figure 7.The average abnormal returns, volatility, and cumulative abnormal returns per- centages for both securities,10 days before and 10 days after WHO announced covid-19 to be a global pandemic. The results show that the average abnormal returns to be negative during the announce- ment period to be negative for both stock markets. The average abnormal returns on day 1 and day 2 continue to reflect a downward trend behaviour however on day 3 the 43 JSE seems to have a positive return compared to the NSE. The behaviour perhaps could be attributed to first case of covid-19 being already announced in South Africa before Kenya. The announcement of first case of covid-19 in Kenya was announced a few days after WHO had declared covid-19 a pandemic. Similarly, the announcement had an im- pact on both the stock markets as the day before the JSE reported positive average ab- normal return of 0,064%, on day 0 it reported -0,951% then day 1 it reported -0,521%. The NSE reported positive average annual return of 0,050% on day-1, day 0 it reported - 1,5435% while on day 1 it reported -0,140%. From the results there is a strong indication that the announcement indeed caused negative returns after announcement day. The investors who had invested in either of the stock markets with the 21-day window period made losses on the returns as both markets had negative abnormal average returns. The cumulative average abnormal return volatility on day 0 was 5,268% and 1,335% for NSE and JSE respectively. The NSE and JSE reported volatility of 11,031% and 12,506% respectively 21-day event window. This implies that an investor in NSE would incur a risk of 11,030% for earning a cumulative average abnormal return of 4,950% while an inves- tor would incur a risk of 12,506% to earn a cumulative average abnormal return of 1,430%. An investor in the NSE would have received a higher positive cumulative abnor- mal average return of 4,950% between day 1 and day 10 compared to the cumulative abnormal average returns for day -10 to -1 of 2,233%. An investor in the JSE in the event window period between day -10 and -1 would have earned a cumulative abnormal av- erage return of 3,500%, while between period day 1 to day 10 an investor would have had a lower cumulative abnormal average return of 1,430%. The average abnormal returns of both security markets indicate that they are efficient as the behaviour before and after the announcement day 0 are reflective of the infor- mation. The two stock markets can be speculated to be weak efficient market as the trends of the abnormal average returns shows stock market independence. 44 Therefore, overall based on analysis of all the three events and results obtained it can be noted that the announcement of the covid -19 in the markets had a negative impact on the stock market based on the average abnormal returns and cumulative average returns patterns on the day before announcement, the announcement day, and the day after announcements. 4.2 Impact of the announcement on key sectors In this section, there is a look at the results from the data and analyse how the different major sectors in the stock market were impacted by the announcement of covid-19. There are some sectors that had positive, negative, or neutral reactions to the announce- ment of the news. The sectors analyzed in the study were technology, energy, healthcare, financials, telecommunications, consumer staples, consumer discretionary and industri- als. The figure 8 below shows the cumulative abnormal average returns for event 1 (when the first covid-19 case was announced in South Africa) 45 Figure 8.The cumulative abnormal average returns for event 1 (when the first covid-19 case was announced in South Africa). The reaction for the specific sectors indicates that the announcement had a significant impact on the sectors given the abnormal negative returns. Even though the news was relatively new there was still a noticeable reaction in the sectors. The results indicate that the abnormal return with certainty of 95% are negative. It can therefore be assumed that the reaction is not a surprise as there was high level of uncertainty and panic as to how the virus would affect the country. The healthcare sector was impacted highest with the highest abnormal average return of -19,32%. The healthcare industry based on the literature review was already crippling in the African countries and therefore the introduction of covid-19 made the situation move from bad to worse. This high negative abnormal return was during the initial stages when the pandemic was announced giving an indication that the situation might get worse as the number of death cases were also on the rise. -11,35 -8,75 -19,32 -7,28 -7,50 -4,55 -11,84 -10,00 -25 -20 -15 -10 -5 0 5 10 15 EVENT 1: JSE CAR% FOR EACH SECTOR 46 Consumer discretionary also reflected a high negative abnormal return of -11.84%. The consumer discretionary sector consists of travel and leisure. The high negative return can be anticipated due to the enforced restrictions such as border closures, stay at home initiative and social distancing that were used in an attempt and limit the spread of the virus. The impact of the imposed restrictions is reflected in the abnormal returns. Industrials also reflected a negative return of -10%. The negative returns can be ex- plained by the decreased supply of components from China. Construction companies were also impacted by the quarantine and self-isolation government policy measure and therefore this meant lack of employees and travel bans also meant lack of access to crit- ical manufacturing items needed. The technology industry also recorded a high negative return of -11.35%. The negative returns could be pinned on the fact that the pandemic was initially a surprise and there was no plan to fully integrate and operate largely on e-commerce platforms. For instance, projects that were underway and relied on access to optical fibre were delayed as China is one of the largest producers of optical fibre. The fibre is a critical component to facili- tate e- business. Event 2: Impact on major sectors The table below shows the cumulative average returns for the second event (WHO de- claring covid-19 to be a pandemic) 47 Figure 9.The cumulative average returns for the second event (WHO declaring Covid-19 to be a pandemic). In comparison to event one, the news of declaring covid-19 to be a global pandemic had a substantial impact on the key sectors. The results reveal that the healthcare had the highest negative return of -25,42% while industrial had the lowest negative return of -11,89%. The heightened negative returns are speculated to be owed to inadequacy to handle the virus due to shortage of medical staff, high medical cost, lack of testing equipment’s and poor infrastructure. The consumer discretionary also reflected a high negative return of -20.02%. The results are reflective of the imposed restrictions put in place by the governments to limit the spread of the virus. -17,03 -18,57 -25,42 -16,65 -15,45 -13,62 -20,02 -11,89 -30 -25 -20 -15 -10 -5 0 5 10 15 EVENT 2: CAR% FOR EACH SECTOR JSE AND NSE 48 Event 3: Results on the effect on major sectors The figure 10 below shows the cumulative average returns for the event 3 (Announce- ment of the first covid-19 case in Kenya) Figure 10.The cumulative average returns for the event 3 (Announcement of the first covid-19 case in Kenya). The results in event three disclose that the impact on the various sectors can be deemed to be less severe as compared to event 1 and event 2. The results can be owed to the fact that the announcement of the first covid-19 case was reported a few days after the WHO had reported the virus to be pandemic. Therefore, it can be assumed that the re- sults are reflective of the early stages surprise as the market had just received the news. -4,79 -1,61 -9,24 -2,85 -4,23 -0,92 -5,38 -3,05 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 Technology Energy Healthcare Financials Telecommunications Consumer staples Consumer discretionary Industrials EVENT 3:CAR % FOR EACH SECTOR IN NSE 49 The results reveal that the highest impacted sector was healthcare which had a -9,24% returns while the least impacted sector was the consumer staples. Healthcare compared to event 1 and event 2 had indicated patterns of negative returns. The results of the negative returns are also reflective of the hospitals incapability to man- age the reported cases already. The health facilities may have been not prepared to cater to the virus cases and hospitals were slowly beginning to be overcrowded. The impact on the healthcare sector could be owed to the fact that the pandemic was already de- clared a pandemic, and this could have increased the panic as the number of infected cases were also beginning to rise. The consumer staples exhibited positive returns of 0,92%. Despite the announcement of the pandemic the consumer purchasing behaviour had not been drastically impacted. The results show that the consumers continued to purchase their daily basic needs with- out any hesitance yet and without any panic buying. Telecommunications and technology reflect negative returns as well. The results could be attributed to the fact that there needed to be a shift in how companies operate. The companies had to shift from a rather traditional face- to face business to a more e-com- merce business platform. Since other countries had been impacted by the pandemic earlier on and therefore transitioned to a more online approach there were no stable and reliable transitions done by many of the Kenyan companies. Due to the lack of sup- plies from China meant that there would be delays and this trickled down to negative return in the telecommunication and technology industries. Consumer discretionary also reported negative returns of -5,38%. Due to the imposed government measure that restricted movement meant that travel and leisure industries are impacted. Tourism and leisure being a key foreign earner for Kenya’s economy was impacted by the various travel bans and border closures. 50 Energy industry was also slightly impacted revealing a return of -1,61%. The impact was not so great as compared to other hit sectors as the economy was shifting slowly to work from home plans, quarantine, and border closure with travel bans. The demand for en- ergy by local consumers was slowly fading away. The industrial sector was also shifting to a close due to the imposed restrictions and lack of essential supplies from foreign suppliers such as China, to proceed with manufacturing slowly made the demand for energy to gradually dwindle. All the results point out that indeed the covid-19 had impacted the stock market heavily on the negative but the degree of impact on each of the different sectors vary from sec- tor to sector. The economy of both Kenya and South Africa has been negatively impacted as seen from the performance of the financial markets and disruption of the global sup- ply chain. 51 5 CONCLUSION In this chapter, there is an in-depth discussion of the major findings of the research, and its implications and analyse whether the set question for the research was answered and objectives met. There is also analysis of the hypothesis and determine whether to reject or accept the hypothesis. The main objective of the research was to find out what was the reaction of the stock market to announcement of covid-19. Similar research study was carried out in the developed countries but there was limited to none done in the developing countries in particular African countries. The analysis of the findings in the research question is as follows: 1. How did the the Nairobi Securities Exchange (NSE) and Johannesburg stock ex- change (JSE) stock markets react to the covid-19 pandemic over different event periods? To answer the question, the research looked at the reaction of the stock market under three events. The events considered for this study are when the first covid-19 case was announced in each of the respective countries and when World Health Organization de- clared covid-19 to be a global pandemic. To conclusively answer this question there is a look at the results average abnormal returns, cumulative average abnormal returns, and the volatility of the markets around the announcement periods. In addition, there is also a comparison to the theoretical framework set out in the literature review to determine whether the finding conform or not. The research observed 60 companies from the NSE and 60 companies from the JSE over a 21-day event period. The results observed show that indeed the announcement of covid-19 caused both markets to react to the ´´surprise news’’ in a negative manner. The announcement of the news also impacted investors decision making. The news of the pandemic caused fear in investors causing them to intrinsically react irrationally making decision out of fear and panic.The herd-like behaviour of the investors caused negative reactions in the stock markets. 52 The results of the abnormal average returns indicate a downward trend after the announcements.The declining trend in the abnormal returns earnings indicate that the market is experiencing a bear trend.The downward trend is additionally heightened by the imposed governmetn policies aimed to curb the spread of the virus. The study also considered the volatility behaviour of both markets.The results indicate that the volatility in the stock market was also higher particularly around the announce- ment day. The trading volume and the volatility returns patterns are indicative of infor- mation flow in the stock market during the announcement consistent with the findings from research by Baker (2020). The volatility pattern in the markets is consistently fluc- tuating in the event window implying that the abnormal average return determines in- vestors risk. The volatility behaviour is consistent with Bodie (2009) research that found out new information in the stock market influences investors to intrinsically assess their investments, hence causing fluctuating volatilities. The stock market negative reaction reveal that the two markets are both efficient mar- kets since they exhibit reaction to the announcement of covid-19. The average abnormal returns around the announcement day are statistically significant therefore indicative of a weak form of efficient market hypothesis. The results have evidenced that covid-19 had an impact on the stock markets therefore the H0 hypothesis that there is no impact of covid-19 on the performance of the Nairobi and Johannesburg stock market is re- jected. 53 5.1 Conclusion for hypothesis findings This section discusses the hypothesis findings that were set in the introduction chapter of the thesis. The hypothesis were as follows: H0: Covid-19 had no economic impact on Kenya or South Africa. H1: Covid-19 had an economic impact on Kenya or South Africa. The hypothesis H0 :there is no economic impact on Kenya and South Africa is also re- jected as the sectoral analysis in the results section indicates that the economies were impacted based on the results shown in figure 8,9 and 10. The healthcare industry had been impacted by the pandemic. The results show that the average returns in Kenya was -9,24% while South Africa had -19,32% returns. This was the most impacted sector in both countries. The virus had begun to spread at an alarm- ing rate that created fear and panic. The high infection rates meant that the economic performance of the countries is impacted as the employment sector relied on the labour force heavily. The industry was heavily impacted as the medical infrastructure, resources and personnel were at a disadvantage as the virus was a new phenomenon. The healthcare sector was incapable to handle virus as there was shortage of staffs and some hospitals already overcrowded. The pharmaceutical sector may have performed better due to increased demand for ‘preventive drugs’ but the other healthcare sub sectors were gradually subsiding. Consumer discretionary is also among the industries that reflected negative impact on the economy. There was a negative average return of -5.38% and -11.84% in the Kenyan and South African markets respectively. The news of covid-19 caused the travel and lei- sure industries to be impacted negatively. The high infection rates locally and abroad caused shut down of borders, cancellation of major events and hotel closures. The travel bans caused significant delays in delivery of essential supplies and goods impeding pro- ject deliverables. The number of tourist and tourism activities were also impacted 54 causing loss of revenues. There was a decrease in air traffic due to closed borders and high infection rates. The energy sector was also affected by the news of the pandemic. Both markets exhibited negative returns as shown in the results section.The results could be attributed to the less need for commute.Due to imposed travel ban, work from home policies implimented there was less demand for fuel.Lack of access to manufacturing material meant also low need for energy as production level were low. Technology and telecommunications showed negative returns as well. Covid-19 im- pacted the industry that largely relied on traditional way of working. Companies had to shift to e-working. The lack of access to materials such as optical fibre due to border closure meant delays in shipment especially since both countries relied of delivery from China. There was already poor existing technological infrastructure which meant more industries are impacted as the pandemic was a surprise. 5.2 Recommendation for future research The research studies the impact of the pandemic on two stock markets in Africa. Similar research could be conducted on other African stock markets for comparison of behav- ioural patterns. Due to rising number of variants of the virus potential research could be conducted to compare whether there were any changes to the stock market behaviour compared to the first wave of the pandemic. Potential research study could also be done to find out whether introduction of vaccines had an impact of the stock market as well. The research was carried put during ongoing pandemic period, similar research can be done during post pandemic period to find out if there was significant reaction in the stock markets.Due to the limited literature that is available on the impact of the pandemic on stock market in the African markets other researchers can look at other African stock markets and analyse if the similar or different trends were experienced.Similar reserach can also be carried out with extended event window. 55 6 REFERENCES (ASEA), A. S. (11. November 2012). Noudettu osoitteesta http//www.african- exchanges.org (ASEA), A. S. (11. Novemebr 2013 ). Noudettu osoitteesta http//www.african- exchanges.org Adenomon, M.;& Maijamaa, B. (2020). Effects of the covid-19 outbreak on the Nigerian stock exchange Performance:Evidence from Garch Models. Journal of Economics. doi:https://doi.org/10.20944/preprints202004.0444.v1 Ahundjanov, B.;Akhundjanov, S.;& Okhunjanov, B. (2020). 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How does investor Sentiment Affect Stock Markets Crises? Financial Review , 46, 723-747. doi:https://doi.org/10.1111/j.1540-6288.2011.00318.x 61 Appendices 6.1 Appendix 1. List of companies in NSE on 02.02.2022 62 6.2 Appendix 2. List of companies in JSE on 02.02.2022