Topic - The impact of Covid- 19 pandemic on stock market volatility. A case study of the ZSE
listed Companies
1.1 Background of the study
The COVID-19 pandemic is an extreme event that has brought uncertainty to the financial markets,
led to a sudden fall in stock prices, and has given rise to financial volatility (Cobert, 2021). The
novel coronavirus disease (COVID-19) is an infectious disease that spreads rapidly to almost all
countries worldwide and caused a global pandemic. The total cases and mortalities due to COVID19 pandemic have increased sharply between 2020 and in 2021 (Ganesh, 2021). This rapid spread
of cases and deaths due to the COVID-19 pandemic had a significant negative impact on the global
economy and on the financial markets (Baker, 2020). In this research, the researcher shall
empirically investigate the impact of the COVID-19 pandemic on stock market volatility during
and after its initial outbreak mainly focusing on Zimbabwe Stock Exchange (ZSE) listed
companies covering the period from July to October, 2020 and 2021, respectively.
The first half of the year 2020 saw one of the most dramatic stock market crashes in history. The
crash was caused by the virus that originated in Wuhan, China. The first case of COVID-19 was
reported in December 2019 in Wuhan city. Initially, it was not believed that this virus could be
deadly and could spread to every part of the world. The rapid spread of the virus across the globe
and the subsequent fear it created finally led to the halt of various economic activities. Many
countries imposed strict lockdowns including Zimbabwe to contain the further spread of the virus
and halted all major economic operations, which ultimately were received negatively by stock
market exchanges, hence the inevitable stock market crash in March 2020. The Zimbabwean stock
exchange crashed immediately by 5% at that time (Mahata, 2021).
According to Dima (2021), the Government of Zimbabwe gazetted the Public Health (Covid-19
Containment and Treatment) National Lockdown) Order, 2020 through Statutory Instrument 83 of
2020. Section 4 (1) of SI 83 of 2020 Orders a Lockdown for a period of 21 days with effect from
30 March 2020 to 19 April 2020. Before the gazetting of the lockdown Order, Issuers were
struggling to finalize their half-year and full-year financial statements because of the unsettling
effects of Covid-19. The ZSE then issued a blanket dispensation to all issuers whose half-year and
full-year financial statements were due for publication by 31 March 2020 to be published on or
before 30 April 2020. Following the issuance of the lockdown Order some listed entities scaled
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down and some completely halted their operations and the future remains uncertain. In the
unfortunate event that the lockdown was extended, it put operational and financial pressure on
many listed companies. Thampanya (2020) added that, the Zimbabwe Stock Exchange Limited
(‘ZSE’) is a licensed securities exchange in terms of the Securities and Exchange Act (24:25) with
a core mandate of facilitating long term capital raising through listing of securities as well as
offering secondary market securities trading and issuer regulation services. The ZSE currently
provides a listing and trading platform for Equity, Debt, Depository Receipts, Unit Trusts,
Exchange Traded Funds and Real Estate Investment Trusts (Dima, 2021).
The impact of Covid-19 was felt across the globe and the ZSE implemented measures in line with
most industries and this included remotely working from home for most of its employees. Trading
hours were reduced to comply with government health regulations to contain the Covid-19 impact.
The ZSE’s resilience was on the back of increased infrastructure investment on the IT systems and
upgrade of skills in the team. The Zimbabwe Stock Exchange’s (ZSE) main All Share Index
(ALSI) was down by 38.5% during the second quarter of the year 2021 whilst the Top 10 index
firmed 53.98%, driven by gains in Cassava, Simbisa and Econet. The mining index registered a
notably lower return than the All Share index during the quarter. Prices for mining stocks were
relatively sticky. Fama (2021) postulated thatIt should be noted however that foreign investors
were net sellers of ZW$0.7b worth of equities on the ZSE and accounted for 6.84% of the value
traded in Q3 2021 compared to 38.72% traded in Q3 2020 (Zimbabwe Stock Exchange Annual
Report, 2021). Trading in the quarter was marked by a significant decline in the value of foreign
investor activity in blue chip companies (Figure 1.1). Activity in other blue chip companies was
limited and largely on the sell side due to Covid-19 (ZSE Annual Report, 2020).
Figure 1.1 Value of shares traded from 1 Jan – 31 Dec 2020
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[Source: Zimbabwe Stock Exchange Annual Report 2020]
ZSE recorded a net foreign seller’s position of $9.73 billion in the year 2021 compared to a net
sell position of $5.42 billion in 2020. Foreign investor participation declined to 11.74% in 2021
compared to 22.81% in 2020 because of Covid-19. According to ZSE Annual Report (2020),
Active users on ZSE Direct grew fivefold to 5,000 in 2021 from 1,000 in 2020. The value of trades
also increased to $248.5 million in 2021 from $14.4 million in 2020. A mobile application version
of ZSE Direct was also introduced for both ios and android users in 2021. Mining activities were
largely depressed, during the last quarter of 2020, compared to the same period in 2019, largely
on account of the Covid-19 induced lockdowns, both domestically and globally. The underperformance of coal, gold, chrome and platinum largely weighed down mining. In addition, Total
gold output stood at 4 794 kg in the fourth quarter of 2020, down by 36% from 7 458kg produced
in the comparable period in 2019. This was largely on due to Covid 19.
Global economic activity slowed down in 2020 as most economies imposed stringent lockdown
measures in the first half of 2020 in response to the wave of Covid-19 infections. In its January
2021 update of the World Economic Forum report, the IMF estimated the global growth
contraction for 2020 at -3.5%. The downturn was, however, less severe than what was projected
on the onset of the Covid-19 outbreak. Growing concerns about the magnitude of the spread of
COVID-19 and its economic impact triggered a global sell-off in financial markets in February
and March 2020, which was associated with surging levels of volatility and trading volumes, as
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well as liquidity contractions. A summary of the initial impact of these events on markets and
securities processing follows.
According to IMF (2020). Volatility quickly spread across the globe in the wake of the COVID19 outbreak as the S&P 500 index fell by 20% in just over three weeks (the shortest time ever for
a bear market to materialize) and continued its decline by 30% in a record 30 days. The Euro
STOXX 50 index recorded the quickest fall in its history. From February 20 to March 9, the 10year U.S. Treasury note yield dropped from 1.52% to 0.54%. By March 23, major Asian equity
markets had recorded an aggregate YTD loss of 28.2%, while risk premium in Asian bond markets
had tripled. On March 16, the CBOE Volatility Index, or VIX, closed at an all-time high of 82.69,
breaking the previous record close that was set on November 20, 2008. In Europe, the VSTOXX,
which measures implied volatility of EURO STOXX 50 Index options, reached an intraday high
of 90% on March 18, up from levels of around 15-20% during the first half of February.
In addition, trading volumes surged across several asset classes during the same period. On the
last day of February, 19.3 billion U.S. shares were traded, more than twice the average daily
volume of 7.0 billion shares over 2019. The 10 highest volume days for U.S. shares by notional
volume or trade count of all time occurred in 2020. The European Securities and Markets Authority
(ESMA) reported that transaction volumes on European trading venues had reached all-time highs
in 1Q 2020. Equity trade volumes in the Asia-Pacific region increased significantly as well. Also,
the average number of daily municipal bond transactions reached 75,000 on March 23, more than
twice the volume recorded in mid-February. At the same time, significant volumes of equity
trading moved from venues where prices are not shown pre-trade (dark pools and over-the-counter
markets) to transparent exchange trading, as investors sought certainty of execution during periods
of liquidity stress. This article aims to analyze the impact of COVID-19 on stock market volatility.
1.2 Statement of the problem
The Stock market financial system plays an important role in the global economy as it acts an
intermediary between lenders and borrowers (Maiti, 2021). The COVID-19 outbreak has disturbed
the victims’ economic conditions and posed a significant threat to economies worldwide and their
respective financial markets. The majority of the world stock markets have suffered losses in the
trillions of dollars, and international financial institutions were forced to reduce their forecasted
growth for 2020 and the years to come (Baker, 2020). The price index on ZSE remained pretty
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steady in the early weeks of the crisis but saw a sharp decline in the weeks following the
announcement of a lockdown in Zimbabwean stock market and fell to its lowest point in the week
following the announcement of social distancing in the country. The industries that have been
hardest hit include tourism and leisure (which includes air travel), fossil fuels production and
distribution, insurance, retailers (excluding food and drug retailers) and some large manufacturing
industries (ZSE Annual Report, 2020). This research deals with the impact of the COVID-19
pandemic on the Zimbabwean Stock Exchange.
Objectives of the study
 The main objective is to investigate the impact of Covid- 19 pandemic on stock market
volatility. Primary objectives of the study are as follows:
1. To determine the influence of Covid-19 daily infections on the stock market returns across
industrial indices on the Zimbabwe Stock Exchange
2. To determine the effect of daily infections on the stock market price
3. To explore the impact of Covid-19 lockdowns on the trading volumes across asset classes
taking place on the ZSE
1.3 Research Questions
The main research question is:
 Investigate the impact of Covid- 19 pandemic on stock market volatility. The primary
research questions of the study are as follows:
1. How do the Covid-19 daily infections influence the stock market returns across industrial
indices on the Zimbabwe Stock Exchange?
2. What is the effect of daily infections on the stock market price?
3. What is the effect of Covid-19 lockdowns on the trading volumes across asset classes
taking place on the ZSE?
1.4 Research Hypothesis
H0: Stock market returns on the ZSE are positively correlated to Covid-19 pandemic
H1: The Covid-19 pandemic and stock market returns on the ZSE are negatively correlated
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1.5 Scope of the Study
The main focus of this research was on the impact of Covid-19 on the stock market volatility. The
Zimbabwe Stock Exchange (ZSE) was the center of a detailed case study. The influence on stock
market prices and the trading volumes attempts to broaden the financial market experiences during
Covid-19 were the subject of the case study. However, because the Zimbabwe Stock Exchange
(ZSE) is Zimbabwe's largest stock market and has the country's top performing companies, all
companies cannot be studied at the same time. As a result, the study was limited to a few of the
top 10 performing companies on the ZSE index. Old Mutual Zimbabwe and Seedco were among
the finalists. Investors, company shareholders were among the study's chosen respondents. The
study will cover period from March 2020 to August 2022.
1.6 Significance of the study
The research study is importance to a number of stakeholders of the community including the
following:
Shareholders/Investors
Stock exchanges form a critical component of the global financial market ecosystem, serving as
gatekeepers linking companies to investors and as a platform for trading the securities of listed
companies. Investors, as providers of capital, are customers of stock exchanges, and constitute a
key stakeholder base. In many areas, investors and stock exchanges are aligned in their views about
promoting the health of financial markets, the protection of investors and the corporate governance
of listed companies.
Brokers
Brokers are major stakeholders in the capital market. They are professionals who facilitate the
trading of stocks for their clients. Most brokers are capable of dealing in all types of securities in
the market. They help clients to buy or sell shares in the market and take a percentage of the trade
value as commission.
Listed companies
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Last but not the least, the companies that list their stocks on the exchange too are one of the
stakeholders. After all, it is their stocks that are being traded. They, thus, are very much concerned
about the activities of the stock market.
Government
Stock markets provide a trading platform for governments too. Sometimes a local, state or national
government may need more money to develop a community housing estate, build a water treatment
plant or initiate any other public projects. Instead of increasing taxes to raise the required revenue,
it can issue bonds through the stock market. When investors buy these bonds, the government is
able to raise the money it needs to launch various projects that can ease the cost of living or even
create jobs for locals. In the long run, this improves the economy.
1.7 Assumptions of the Study
 The researcher anticipated that company shareholders and directors collaborated and
shared important data.
 Key subscribers offered non-biased and factual information about the Zimbabwe Stock
Exchange (ZSE).
 Respondents from the entire population sample were included.
1.8 Literature review
As the COVID-19 pandemic emerged, many studies have covered several aspects of the crisis,
including its economic developments. As new information arrives in the stock markets markets, it
generates skepticism over market efficiency and the interrogation on investors over or under
reaction to the news. Although the existent literature examines a wide variety of theories on the
equity market over COVID-19, this review centers on the stock market responses to lockdowns,
number of cases and media news. In addition, this section also reveals existing literature on the
effect of natural disasters and terrorism, as well as the causes of previous financial recessions.
Yilmazkuday (2020) examines the impact of COVID-19 daily cases on global economic activities
based on commodities’ daily shipping (transportation). He finds that daily cases adversely affect
the global economic activity and argues that COVID-19 has brought significant disruptions on
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global economic activity through disrupted transportations among the supply chains. Yilmazkuday
(2020) finds that COVID-19 has also increased the U.S.’s unemployment rate, especially in March
2020. Furthermore, He later finds that a one percent increase in the cumulative daily COVID-19
cases in the U.S. resulted in 0.01 percent negative daily return in the S&P 500 index.
Onali (2020) finds that COVID-19 significantly affects the U.S. equity market toward the end of
February 2020. Using daily data from China, India, Japan and Korea, Garg (2020) examine the
relationship between oil price returns and stock returns and find that falling oil prices brings a
negative signal to the stock markets. Recent studies have also examined the impact of COVID-19
on the equity markets’ volatility and trading volume. Baek (2020) find a significant increase in
absolute risk for the US equity market due to the COVID-19 deaths. Salisu and Akanni (2020)
construct a global fear index (GFI) based on the cases and deaths from the COVID-19. They find
that GFI is a good predictor of stock returns in the OECD and the BRICS countries during the
pandemic. Zhang, Hu, and Ji (2020) examine the impact of COVID-19 on stock market volatility
across 11 developed countries and China and find that the volatility has increased substantially
from February to March 2020. COVID-19 studies have also examined the impact on the
commodity markets, specifically crude oil (energy) markets.
Narayan (2020) examines the effect of the threshold of the COVID-19 case on oil prices and finds
that news on oil prices has a limited effect on price when conditioned on COVID-19 cases. Under
the oil price volatility threshold, both COVID-19 cases and negative news on the oil process
significantly affect oil prices. Using hourly data, Devpura (2020) show that COVID-19 cases and
deaths led to a significantly greater daily volatility in the oil process. Salisu and Adediran (2020)
find that the equity market volatility tracker of COVID-19 (Baker, Bloom, Davis, Terry et al.,
2020) is a good predictor for energy market volatility. Qin, Zhang, and Su (2020) find that the
COVID-19 pandemic index negatively affects the oil prices due to lower demand during the
infection period of 2019 and early 2020. Albulescu (2020) examines the impact of COVID-19 on
the stock market volatility in the US and finds that the global new cases and fatality ratio increase
the volatility. Arias (2020) find evidence that COVID-19 has increased herding behavior in returns,
volatility, and trading volumes among five major European equity markets. Chiah and Zhong
(2020) examine the impact of COVID-19 on the trading volumes across 37 international equity
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markets and find a massive increase in trading volume attributable to the national culture and
institutional environment in each country.
Although a number of studies have investigated the impact of different diseases on stock market
performance, emerging literature presents new evidence on the impact of the COVID-19 pandemic
and the reaction of financial markets to its spread worldwide. For example, Liu et al. (2020)
demonstrated in an event study that the COVID 19 outbreak had a negative impact on stock
markets and weakened their performance in many countries, including Korea, Japan, the USA,
Germany, the UK, etc. Ashraf (2020) found that confirmed COVID-19 cases had a quick and
negative impact on stock markets. This study showed that responses from the stock markets varied
over time depending on the stage of outbreak. For example, a negative market reaction was strong
during the early days of confirmed cases. Al-Awadhi et al. (2020) showed in an experimental study
on COVID-19 that the daily growth in total number of confirmed cases and total number of deaths
had a significant negative impact on stock returns of all companies in the Chinese stock market.
Albulescu (2020) highlighted that confirmed cases and deaths due to COVID-19 positively
influenced the market volatility index within and outside China. Baker et al. (2020) demonstrated
that voluntary social distancing and government restrictions on commercial activity were the main
reasons the US stock market reacted more heavily to the COVID-19 than to previous pandemics.
Khan et al. (2020) investigated the stock markets of sixteen countries and came to the conclusion
that once the WHO confirmed the human-to human transmissibility of COVID-19, all stock
markets reacted negatively. While the aforementioned studies demonstrate the negative impact of
the COVID-19 pandemic on stock markets in different countries, Singh et al. (2020) found that
after some time (app. 1.5 months) stock markets recovered from the negative impact of COVID19 in G-20 countries.
Loh (2006) investigated to what extent the airline companies traded in the financial markets of
Taylan, China, Canada, Hong Kong, and Singapore are affected by SARS. For this purpose, Ftest, Siegel Tukey, Bartlett, Levene, and Brown tests were performed by using the data obtained
from December 1, 2002 to July 5, 2003. As a result of the analysis, it is indicated that the epidemic
harmed airline companies. Giudice and Paltrinieri (2017) examined monthly flows and
performances of 78 equity mutual funds in African countries for the period of 2006-2015. As a
result of the analyzes and examinations, it is concluded that two significant events, which are Ebola
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and the Arab Spring, have significantly affected the funds flows, fund performance, expenses, and
market returns.
Laing (2020) examined the effect of coronavirus on certain precious metals. In order to measure
the price changes, he compared the prices of aluminum, copper, gold, lead, nickel, and zinc for the
period between March 4, 2020 and April 2, 2020. As a result of this comparison, it is found that
the price of aluminum, copper, gold, lead, nickel, and zinc decreased by 15%, 14%, 2%, 10%,
11%, and 6% respectively in the period given. Al-Awadhi et al. (2020) have investigated the effect
of the coronavirus outbreak on financial markets. They included 82 companies operating in The
Hang Seng Index and Shanghai Stock Exchange Composite Index and divided them into ten
sectors according to their fields of activity. Then, they collected daily data of validated cases,
deaths, and stock market values of companies from January 10, 2020 to March 16, 2020. By using
panel data analysis, they concluded that the number of daily confirmed cases and daily death cases
had significant negative effects on the financial markets of the countries included in the study.
1.8.1 Theoretical Framework
Efficient Market Hypothesis theory
The Efficient Market Hypothesis (EMH) is one of the main discussed theories in finance literature,
which defends the impossibility of outperforming the market consistently on a risk adjusted basis.
Introduced by Fama (1970), this theory defines an efficient market as a market in which asset
prices reflect all past and present information. Only new information moves security prices, and
as new information is unknown and occurs at random, upward or downward price movements are
unknown and therefore move randomly. An important point in market efficiency is that prices
should only react to information that is not expected by investors, otherwise the piece of
information should already be considered at the security price. The main conclusion behind the
EMH is that securities always trade at their fair market value, meaning that it is virtually impossible
to sell overvalued stocks at a premium or to buy undervalued ones at a discount. In a highly
effective market, investors prefer passive investment strategy to an active investment strategy due
to lower costs, such as transaction or information-seeking costs.
In his study, Fama (1970) suggested three types of efficiency: a weak form, a semi strong form
and a strong form. The author defined each form according to the availability of information that
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is reflected in prices. Weak form: security prices fully reflect all past market dates. If markets are
weak-form, past trading is already reflected in security prices and investors cannot forecast future
price changes. As a result, it assumes that technical analysis does not offer any consistent excess
return over the market. Under Semi strong form security prices fully reflect all publicly available
information, including financial statement data and market data. Therefore, it improves the weak
form by assuming that neither technical nor fundamental analysis provides an advantage over the
market. Under Strong form security prices fully reflect public and private information. Thus, no
investor can achieve higher returns than others because of inside information. However, this is an
unlikely scenario because of the strict prohibitions against insider trading.
Based on the literature, there are two opposing schools of thought regarding market efficiency.
The first school of thought claims that markets are efficient and that investors cannot forecast
returns. On the other hand, the second school of thought provides empirical evidence that
challenges the theory of efficient markets. Behavioural finance appeared for the first time in Bondt
& Thaler (1985) attempting to explain that emotions and human behaviour play a significant role
in investor decisions. The theory does not assume that investors consider all available information
and act rationally when deciding. The main assumption behind behavioural finance is that
investors are humans and, therefore, not perfect. A key point for explaining this theory are the
behavioural biases of individuals, which explain market inefficiencies.
Market Anomalies
Although there is significant evidence showing that markets are efficient, researchers have
identified several apparent market inefficiencies, called anomalies (Jensen, 1978). If a change in
the price of an asset cannot be attributed to the release of new information, it surges an anomaly
over market efficiency.
Based on the analysis method that identified the anomaly, there are two types of categories: timeseries anomalies, which use time series of data; and cross-sectional anomalies, which use a sample
of companies. Time-series anomalies can be sub-categorized in calendar anomalies, which are
situations linked to a particular point in time; and momentum and overreaction anomalies, which
relate to short-term price patterns. Calendar anomalies include the January effect the weekend
effect or the turn of-the-month effect (Ariel, 1987). Momentum and overreaction anomalies were
introduced in by affirming that most people tend to overreact to unexpected and dramatic event
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news. In addition, Folkinshteyn et al. (2015) document a recurring trend of investor overreacting
through five of the most important stock market crashes of the last three decades. As for crosssectional anomalies, two of the most researched situations are the size effect and the value effect.
The size effect, first observed by (Banz, 1981), results from the observation that small-cap
companies stock tends to outperform large-cap companies’ stock. The value effect results from the
observation that value stocks have consistently outperformed growth stocks through long periods
of time (Basu, 1977).
1.9.2 Conceptual framework
Figure 1.2: Conceptual Framework
• Covid-19
pandemic
Independent
variable
Dependent
variable
• Stock
market
volatility
[Source: Arash (2021) Covid 19 and Stock market performance]
The objective of this study is to examine the impact of the global Covid-19 pandemic in the
Zimbabwean stock market. Hence, Covid 19 is the independent variable as it is independent of the
stock market. Stock market volatility is depending or react based on the confirmed cases or daily
infections of Covid-19, hence it is the dependent variable.
1.9 Research Methodology
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Research design
The research strategy serves as a guide for achieving goals and finding answers. It emphasizes the
significance of a time- and activity-based approach in study design. It creates a framework for
describing the connection between the research variables. Two of the most well-known
personalities in the world are Cooper and Schindler (Saunders, 2015). The investigation was
carried out using a descriptive research methodology. The method was chosen because it would
make it easier to spot trends in attitudes and behavior and enable generalization of the study's
findings. The reason descriptive research was chosen was so that a more accurate profile of a
circumstance, person, or event could be created. Robson (Robson, 2016).
This research approach was chosen because it saves time, money, and allows for the legitimate
collection of quality data while minimizing interviewer bias because participants complete selfreport questionnaires with similar wording (Faberge, 2015). Due to time constraints, a crosssectional approach was not used in this work. To examine a specific event at a specific time,
researchers can employ cross-sectional research. The survey tactic is typically used in this research
methodology (Robson, 2016).
Sampling method
The method of judgmental sampling was used. It permits researchers to use their judgment in
selecting the sample that will allow them to answer the research questions and meet the study
objectives. It is also known as intentional sampling (Saunders et al, 2007). The researcher attempts
to draw a representative sample using their own judgment. Wegner (2013) cautions that if this
method is used, the researcher must ensure that the sample chosen is representative of the entire
community. This sort of sampling is commonly employed when working with small samples, such
as in case study research, or when the researcher wants to select cases that are particularly
instructive. When a large number of groups have to be chosen, the advantage is that group size
balance is ensured. The Shareholders or investors, brokerage firms and company executives who
took part in the study were chosen by a judgmental sampling procedure.
Sample size
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According to Bougie and Sekaran (2016), for most scientific empirical social science research, a
sample size of larger than 30 and equivalent to 500 is appropriate since it achieves the statistical
power required in social science research. To lower standard error, a large sample size is required.
Saunders et al. (1996) added to this by adding that the larger the sample size, the less likely it is to
generalize incorrectly to the population, and the margin of error should be within acceptable limits.
The study's sample size was thirty (30), with 22 shareholders and 8 executives chosen at random.
The sample size was substantial and representative enough for the researcher to draw reasonable
findings. Choosing exceptionally large samples, according to Saunders et al. (1996), does not pay
off.
Data collection techniques
In this study, a semi-structured electronic questionnaire based on the interview guide was utilized
to collect data, and it was sent via email and on the ZSE official website. The opinions of the
students were then obtained by introducing the questionnaire link. Top 10 performing industries
on the ZSE around the country provided a total of 30 open-ended questionnaires. Shareholders
were requested to provide their ZSE IDs so that the survey could be managed to ensure that only
those listed on ZSE completed it. Within a month, all of the data had been collected. The
participants were not asked for any personally identifiable information.
The instruments utilized in this investigation were questionnaires. The items were created by the
researcher because no appropriate item could be identified in the present literature. The
questionnaires were created with the study's goal in mind. Closed-ended Likert scale statements
were used on the questionnaire forms (quantitative data). The questionnaire was graded on a fivepoint Likert scale (Strongly Agree= 1 Agree= 2, Not sure/Neutral= 3, Disagree= 4, and Strongly
Disagree= 5). The demographic data of respondents was collected using a nominal scale as shown
in Table 3.1 Below:
Strongly Agree
Agree
Uncertain
Disagree
Strongly
Disagree
1
2
3
4
5
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Table 1.1: Likert scale
The entire questionnaire was split into two groups: A and B. The respondents' backgrounds are
explored in Section A, which includes their age, gender, education, and length of time they have
been learning at the universities. Section B discusses the main study objectives.
Data Analysis and Presentation
A quantitative technique will be used to analyze the data. Microsoft Office Excel will be used in
the banking industry to examine the relationship between Covid-19 and Stock market volatility.
SPSS and Excel will be the primary analytical tools for analyzing the study's findings. The raw
data would be summarized and presented in the form of tables and percentages. Based on the
study's findings and conclusions, appropriate recommendations for strengthening the online
learning experience of students will be made. In addition, Statistical Package for the Social
Sciences (SPSS) Statistics version 20.0 was used to analyze the questionnaires. Hence, Descriptive
statistics (discreet variables and respondents' demographics were analyzed using frequencies and
charts) Regression/Correlation analyses were calculated using (IBM SPSS 20).
Reliability, Validity and Ethical Considerations
Research involves not just talent and diligence, but it also necessitates honesty and integrity. This
is done to preserve the rights of the study participants. This research was carried out in such a way
that the participants felt safe and their privacy and confidentiality were protected. The rights of
self-determination, anonymity, secrecy, and informed consent were observed to make the study
ethical, as argued by Burn and Groves (1993). To begin, the researcher obtained permission from
universities to conduct the study.
The respondents' agreement was sought prior to completing the questionnaires. Burns and Grove
(1993) define informed consent as a prospective respondent's voluntary assent to participate in a
study after being informed about the study's purpose. The participants were advised of their rights
to freely consent, decline to participate, or withdraw their participation at any time with a penalty.
The participants were told about the study's goals, what it hoped to accomplish, how the data would
be collected, and how the data would be used.
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The researcher maintained anonymity and secrecy during the investigation. Burns and Grove
(1993) define anonymity as the inability to link the specific opinions of responders. The
respondents' privacy was preserved in this study by the researcher not revealing their identity on
the questionnaires or research reports. While reporting on the findings, the researcher preserved
confidentiality for the purposes of this study by not releasing the gathered data or the identity of
the respondents. Finally, the researcher's contact information was provided in case there were any
questions.
1.10
Definition of key terms
Stock market – Is a market which consists of exchanges in which stock shares and other financial
securities of publicly held companies are bought and sold
Covid-19 - The novel coronavirus disease (COVID-19) is an infectious disease that spreads rapidly
to almost all countries worldwide and caused a global pandemic. The total cases and mortalities
due to COVID-19 pandemic have increased sharply in the last months of 2020 and in 2021. This
rapid spread of cases and deaths due to the COVID-19 pandemic had a significant negative impact
on the global economy and on the financial markets.
Stock volatility – It is the standard deviation of a stock’s annualized returns over a given period
and shows the range in which its price may increase or decrease. If the price of a stock fluctuates
rapidly in short period, hitting new highs and lows, it is said to have high volatility
Lockdown – It is a restriction policy for people or community to stay where they are, usually due
to specific risks to themselves or to others if they can move and interact freely.
Market Index – Is a hypothetical portfolio of investment holdings that represent a segment of the
financial market.
1.11
Work Plan
Table 1.2 Proposed Dissertation Working Schedule
Milestone
First submission date
To be done by
Chapter 1
Literature review
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Methodology and Research
Instruments
Data collection
Corrected Methodology
Chapter 4
Chapter 5
Final draft
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References
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