35
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
ORIGINAL SCIENTIFIC PAPER
RECEIVED: NOVEMBER 2021
REVISED: FEBRUARY 2022
ACCEPTED: FEBRUARY 2022
DOI: 10.2478/ngoe-2022-0004
UDK: 336.761:005.931.11
JEL: C01, C23, D84, GI4
Citation: Dias, R., Pereira, M. 
J., & Carvalho, C. L. (2022). Are 
African Stock Markets Efficient? 
A Comparative Analysis Between 
Six African Markets, the UK, Japan 
and the USA in the Period of the 
Pandemic. Naše Gospodarstvo/Our 
Economy, 68(1), 35-51.
DOI: 10.2478/ngoe-2022-0004.
This work is licensed under a 
Creative Commons Attribution-Non-
Commercial-NoDerivatives 4.0 
International License.
NAŠE GOSPODARSTVO
OUR ECONOMY
Vol. 68 No. 1 2022
pp. 35–51
Are African Stock Markets Efficient? 
A Comparative Analysis Between Six 
African Markets, the UK, Japan and the 
USA in the Period of the Pandemic
Rui Dias
CEFAGE – Centro de Estudos e Formação Avançada, em Gestão e Economia, 
Universidade de Évora, Portugal
rui.dias@esce.ips.pt
João M. Pereira
Universidade Aberta, Portugal
jmpereira@uab.pt
Luísa Cagica Carvalho
CEFAGE – Centro de Estudos e Formação Avançada, em Gestão e Economia, 
Universidade de Évora, Portugal
luisa.c.carvalho@esce.ips.pt
Abstract
The aim of this study is to test and compare the efficient market hypothesis, 
in its weak form, on the stock markets of Botswana, Egypt, Kenya, Morocco, 
Nigeria, South Africa, Japan, the UK and the USA from 2 September 2019 to 2 
September 2020. This study is based on the following research question: has 
the global pandemic (COVID-19) reduced the efficiency – in its weak form – of 
African financial markets compared to the mature markets of the UK, Japan and 
the USA? The results sustain the evidence that the random walk hypothesis is not 
supported by the financial markets analysed in the period of the global pandemic. 
The variance ratio values are lower than the unit, which implies that the returns 
are self-correlated over time. A reversion to the average is also observed, with 
no differences identified between mature and emerging financial markets. In 
corroboration, the Detrended Fluctuation Analysis (DFA) exponents show that the 
financial markets present signs of (in)efficiency in its weak form, thus showing 
persistence in the yields. This therefore implies the existence of long memories 
validating the results of the variance using the Wright’s Rank and Signs Test 
(2000), which prove the rejection of the random walk hypothesis.
Keywords: African stock markets, efficient market hypothesis, mean reversion, 
random walk
Introduction
The COVID-19 pandemic has negatively affected global trade as well as social 
and cultural life, including tourism, trade in goods, production, and sectors such 
as transport. Therefore, rating agencies such as Moody's and Standard & Poors 

36
NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
reduced China's growth forecast for 2020. In line with all 
these adverse effects, it seems inevitable that stock markets, 
economic growth and exchange rates have also been affected 
equally (Liu, Manzoor, Wang, Zhang and Manzoor, 2020). 
Interest in African Stock markets from international inves-
tors has been increasing and attracting significant private 
investment. There are currently over twenty-nine (29) stock 
exchanges in Africa with significant disparities in market 
size, number of companies listed, volume of transactions 
and access to information. These institutional limitations, 
together with the existence of information asymmetry, 
agency problems, regulatory constraints and the presence 
of weak financial institutions, have implications for the ef-
ficient market hypothesis (EMH) in these regional stock ex-
changes (Hawaldar, Rohith, & Pinto, 2020; Lawal, Nwanji, 
Adama, & Otekunrin, 2017; Lawal, Somoye, & Babajide, 
2017; Tweneboah, Owusu, & Oseifuah, 2019). 
Thus, the aim of this study is to test the hypothesis of an 
efficient market, in its weak form, in the stock markets of 
Botswana, Egypt, Japan, Kenya, Morocco, Nigeria, South 
Africa, the UK and the USA from 2 September 2019 to 2 
September 2020, in order to cover the year most affected 
by the global pandemic. This test is conducted based on 
the following research question: Has the global COVID-19 
pandemic reduced the efficiency, in its weak form, of African 
financial markets? The results suggest very pronounced 
structural breaks, the existence of reversion to the mean, and 
the rejection of the informational efficiency hypothesis in 
its weak form.  In corroboration, the DFA exponents show 
that the financial markets present signs of (in)efficiency in 
its weak form, thus showing persistence in the yields. This, 
therefore, implies the existence of long memories validating 
the results of the variance using the Wright’s Rank and Sign 
Test (2000), which prove the rejection of the random walk 
hypothesis. These results also suggest that prices do not 
fully reflect the available information and that price changes 
are not independent and identically distributed (i.i.d.) in all 
markets. The high sensitivity of prices to the arrival of new 
information is said to have been due to the climate of pes-
simism and uncertainty experienced by investors during the 
period of the global pandemic.
This study is justified because there are still some gaps in the 
literature relating to the efficient market hypothesis (HME) 
in African stock exchanges. For instance, hybrid evidence 
is inconclusive in empirical studies on Africa.  The authors 
Smith, Jefferis and Ryoo (2002), Simons and Laryea (2006), 
Obayagbona and Igbinosa (2015), Whisky (2015), Ogbulu 
(2016), Lawal, Somoye and Babajide (2017), Fusthane and 
M (2017), and Ajekwe, Ibiamke and Haruna (2017) demon-
strated that African markets display signs of marked levels of 
(in)efficiency in its weak form, substantiating that returns are 
predictable based on historical prices. In addition, the authors 
Kelikume (2016), Abakah, Alagidede, Mensah and Ohene-
Asare (2018), and Hawaldar, Rohith and Pinto (2020) showed 
that African markets are efficient in their form and verified the 
fact that stock prices fully reflect all the information available 
in the market, and investors cannot obtain anomalous returns 
with the same level of risk. Therefore, this research is justified 
by the need to mitigate existing empirical divergences on the 
African stock market. Moreover, as these stock exchanges 
develop in the presence of imperfect information, investors, 
regulators and other participants demand transparency about 
the efficiency or inefficiency of these stock markets to avoid 
sharp structural breaks, which can cause significant losses to 
domestic and international investors.
In terms of structure, this test is organised into five sections. 
In addition to the current introduction, section 2 is a Lit-
erature Review on the random walk hypothesis in African 
financial markets, section 3 describes the methodology, and 
section 4 contains the data and results. Finally, section 5 
contains the general conclusions of the work.
Literature Review
The subject of the efficient market hypothesis (HME) denotes 
that the current price of assets reflects all the available infor-
mation at a given moment, and the price adjusts quickly as 
new and unexpected information reaches the market. The 
hypothesis of reversion to the average, also called negative 
series correlation, has been interpreted as an efficient cor-
rection mechanism in developed markets and a speculative 
bubble sign in emerging financial markets (Summers, 1986; 
Fama & French, 1988). 
The EMH assumes the absence of asymmetric information 
in trading activities in a traditional stock market. The EHM 
has been tested extensively in developed markets with mixed 
results. The same has happened in relation to African financial 
markets due to the presence of asymmetric information and 
institutional constraints. Validating the African economy's 
assumptions has continued to be of great interest to investors 
and academics, given the prominence of the African economy 
in global economic growth (Kelikume, 2016). 
Smith, Jefferis and Ryoo (2002), and Simons and Laryea 
(2006) analysed market efficiency in its weak form in 
African markets. Smith, Jefferis and Ryoo (2002) tested 
the random walk hypothesis on the stock markets of South 
Africa, Egypt, Kenya, Morocco, Nigeria, Zimbabwe, 
Botswana and Mauritius. The authors show that the random 
walk hypothesis is rejected in seven of these markets due 
to the autocorrelation of the yields. For the South African 
market, the stock index follows the random walk hypothesis. 

37
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Simons and Laryea (2006) examined four African stock 
markets – Ghana, Mauritius, Egypt and South Africa. Based 
on the results of the parametric and non-parametric tests, the 
authors show that the South African stock market is efficient 
in its weak form. At the same time, Ghana, Mauritius and 
Egypt are inefficient. 
Additionally, Tiwari and Kyophilavong (2014), Obayag-
bona and Igbinosa (2015), Whisky (2015), Ogbulu (2016), 
and Kelikume (2016) tested whether African markets are 
predictable. Tiwari and Kyophilavong (2014) examined the 
hypothesis of random walk in the BRICS stock indices. The 
authors demonstrated that these markets show inefficiency in 
its weak form, except for the Russian stock index. Obayag-
bona and Igbinosa (2015) show dependence on the series of 
returns and, therefore, non-randomness, demonstrating that 
the Nigerian market shows signs of (in)efficiency in its weak 
form. Whisky (2015) examined the behavior of four sectors 
in Nigeria, suggesting that the series of returns does not 
support randomness, except in the agricultural sector, which 
implies inefficiency in its weak form in this African market. 
Ogbulu (2016) shows that the Nigerian Stock Exchange 
(NSE) is (in)efficient in its weak form for the daily, weekly, 
monthly and quarterly time scales. Kelikume (2016) studied 
the Nigerian stock market from 1985 to 2015, showing that 
it follows a random walk behaviour, thus verifying signs of 
efficiency. In other words, stock prices fully reflect all the 
information available in the market, and investors cannot 
obtain abnormal returns with the same level of risk.
In terms of the risk, Lawal, Somoye and Babajide (2017), 
Fusthane and M (2017), Ajekwe, Ibiamke and Haruna 
(2017), Abakah, Alagidede, Mensah and Ohene-Asare 
(2018), and Hawaldar, Rohith and Pinto (2020) tested the 
hypothesis of arbitration, namely the possibility of investors 
obtaining abnormal returns without incurring additional risk. 
Lawal, Somoye and Babajide (2017) studied the validity of 
the random walk hypothesis in the seven largest African 
markets. The authors argue that the EHM is rejected in its 
weak form, implying that African markets are inefficient 
and that the implementation of adjusted trading strategies 
may provide trading by arbitration. Fusthane and M (2017) 
examined the Johannesburg Stock Exchange, pointing out 
that this market shows signs of inefficiency in its weak form. 
Along the same lines, Ajekwe, Ibiamke and Haruna (2017) 
established that the Nigerian stock market is efficient in its 
weak form. The implication of these results demonstrates 
that investors cannot have anomalous returns with the same 
level of risk. Abakah, Alagidede, Mensah and Ohene-Asare 
(2018) re-examined efficiency in its weak form, in the stock 
markets of South Africa, Nigeria, Egypt, Ghana and Mau-
ritius. The authors point out that South African, Nigerian 
and Egyptian stock market indices follow the random walk 
hypothesis (RWH) and are efficient in their weak form. In 
contrast, the markets of Ghana and Mauritius are inefficient. 
Hawaldar, Rohith and Pinto (2020) examined the predict-
ability of eight African stock markets. The authors deter-
mined that investors cannot obtain anomalous returns based 
on historical prices, proving that these markets are efficient 
in their weak form.
In summary, the aim of this paper is to provide information to 
investors and regulators in African financial markets, where 
individual and institutional investors seek to efficiently di-
versify their portfolios in a period of uncertainty and lack 
of confidence arising from the global COVID-19 pandemic.
Methodology
The stock market index prices of Botswana, Egypt, Kenya, 
Morocco, Nigeria, South Africa, Japan, the UK and the USA 
were analysed from 2 September 2019 to 2 September 2020. 
The quotations are daily and were obtained from the Data-
Stream platform in local currency to mitigate exchange rate 
distortions. 
This sample period was chosen as a result of a study by 
Nsoesie, Rader, Barnoon, Goodwin and Brownstein (2020). 
According to these authors from Harvard Medical School, 
evidence has emerged that the first outbreak of the virus 
occurred in the city of Wuhan, China, in the period before 
December 2019. The study was based on the observation 
of an increase in vehicles in the car parks of main hospitals 
and the high number of searches of Chinese search engines 
(Baidu) related to symptoms of the virus in late summer 2019.
The preference for these African financial markets is ex-
plained by their unstable, rapidly developing economies 
linked by cultural heritage and other similar economic con-
ditions. Additionally, following the 2008 financial crisis in 
international emerging markets and those of Africa, these 
markets became an important investment destination. The 
choice of financial markets in Japan, the UK and the USA 
is due to the relevance of these markets in a global context. 
They are also very relevant indices of the regions in which 
Asia, Europe and America are part.
This research was developed over several stages. In the first 
stage, descriptive statistics and the Jarque and Bera (1980) 
adherence test was used to verify that the data follow a 
normal distribution. Graphs were produced of the markets, 
in levels and yields, to estimate the evolution of the markets 
under analysis. Additionally, the stability of residues was 
examined. To verify the breaks in structure, the Clemente 
et al. test was used (1998). To test the market efficiency in 
its weak form, a non-parametric test developed by Wright 
(2000) was used because this test is more resilient to time 

38
NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
series that do not exhibit normality and are relatively consist-
ent when they show series correlation. The aforementioned 
author's methodology consists of two tests: the position test 
(Ranks) for homoscedastic series, and the Signs test for het-
eroscedastic series.
The position test (Ranks) of the variance is supported in the 
ordering of the yield series.
For clarity, r(r
t
) is considered the profitability position, r
t
, 
between r
1
 , r
2
, …, r
T
:
r
rr
T
TT
t
t
1
1
2
12
2
12
'
()
() ()


 





 (1)
r
rr
T
t
t
2
1
1
'
(
()
) 



(2)
Where Φ
-1
 refers to the cumulative reverse standardised 
normal distribution, r'
2t
 is a standardised linear transfor-
mation of the yield position, and r'
2t
a standardised reverse 
normal transformation.
Rq
Tq
rr r
T
r
tt tq
tq
T
t
tq
T
1
11 11
2
1
1
2
1
1
1
()
()
()
'' '
'

 


 





 









 






22 11
3
1
2
() () qq
qT
(3)
Rq
Tq
rr r
T
r
tt tq
tq
T
t
tq
T
2
22 12
2
1
2
2
1
1
1
()
()
()
'' '
'

 


 





 









 






22 11
3
1
2
() () qq
qT
(4)
The rejection of the RWH of yields is generated by a simu-
lation process, in which the values of the r
t 1
'
and r
t 2
'
statistics 
are replaced by the r
t 1
'*
and r
t 2
'*
simulated value Using boot-
strap estimates, which result in successive random genera-
tion of data, in order to simulate the statistical properties of 
the true sample distribution, the exact distribution of R
1
(q)  
and R
2
(q) can be approximated to a given confidence level.
Wright's methodology (2000) proposes a second test, called 
the signal variance ratio, which considers the signal yield, r
t
, 
to calculate the signal ratio, being the same heteroscedastic. 
Thus, the following test statistic can be used:
Sq
Tq
SS S
T
S
tt tq
tq
T
t
tq
T
1
1
2
1
2
1
1
1
()
()
()

 

















 

 






22 11
3
1
2
() () qq
qT
(5)
where
Sr
tt
 20 (,)
(,)
,
,
xp
se xp
se xp
t
t
t










05
05
(6)
The distribution of S
1
(q) can be approximated by Sq
1
*
()
through bootstrap techniques, as in the case of the ratio of 
variance by rankings. Sq
1
*
() is obtained from the S
t
t
T
*

1
 
sequence, as each of its elements registers a value of 1 or -1, 
with the same probability.
Detrended Fluctuation Analysis (DFA) was used in order to 
validate the results. DFA is an analysis method that examines 
time dependency in non-stationary data series. By assuming 
that time series are non-stationary, this technique avoids 
spurious results when the analysis focuses on long-term data 
series relationships (Bashir, Y u, Hussain and Zebende, 2016; 
Guedes, Ferreira, Dionísio and Zebende, 2019). 
 A DFA is based on the following interpretation:
Table 1. Detrended Fluctuation Analysis (DFA)
Exponent Type of signal

DFA
 05 .
long-range anti-persistent
α
DFA
 05 . uncorrelated, white noise

DFA
 05 . long-range persistent
Source: Authors
Results
In terms of the main results, it is important to highlight the 
results illustrated in Figure 1, which depict the evolution, in 
return, of the nine financial markets. The graphical analysis 
of the indices indicates that they show very similar behav-
iour patterns during the sample period. These patterns were 
strongly marked by the occurrence of the global COVID-19 
pandemic. In contrast, the graphical analysis also verifies the 
existence of a bear market period between February, March 
and April 2020, which is characterised by a sharp drop in the 
index resulting from the evolution of the global COVID-19 
pandemic.
Table 2 shows the main descriptive statistics of the finan-
cial markets under analysis, and allows us to ascertain that 
Botswana, Egypt, Japan, Kenya, Morocco, Nigeria, South 

39
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Africa and the UK stock market returns present negative 
daily averages, with the exception of the Japanese and 
US markets, which show positive daily averages. The US 
market exhibits the most pronounced standard deviation 
(0.020652). Additionally, the authors of this paper verified 
that all the markets present negative asymmetries, while 
the short ones have values above 3, which contradicts the 
hypothesis that the data follow a normal distribution (asym-
metry = 0, kurtosis = 3). In corroboration, the adherence test 
of Jarque-Bera provides evidence that the data series do not 
follow normal distributions.
Since the time series are estimated, it is necessary to examine 
the stationary nature of the data series of the nine markets. 
The Levin, Lin and Chu (2002) test postulate that the null 
hypothesis has unitary roots, showing the stationary nature 
of the time series. However, the Hadri test (2000) postulates 
the stationarity in the null hypothesis. As can be see, there is 
rejection, which demonstrates that the data series is not sta-
tionary and that the time series may not be stable. As a result 
of this evidence, the Clemente et al. (1998) test is to be con-
ducted to analyse the stationarity with breaks in structure.
Figure 2 shows the stability tests performed on stock market 
residuals, assessing the existence of disturbances in variance. 
Additionally, when examining the graphs and the 95% prob-
ability limits, a violation of the limits of the probability can 
be verified, thus the time series shows unstable behaviour.
Figure 3 illustrates the unit root test results, with structure 
breaks, by Clemente et al. (1998), showing the existence of 
structural breaks in March 2020, except for the Botswana 
Stock Exchange, which was expected given the evolution 
of the global COVID-19 pandemic. These findings are cor-
roborated by the authors Sansa (2020), He, Liu, Wang and 
Yu (2020), who showed structural breaks in the financial 
markets resulting from the global pandemic.
Table 5 shows the results of the non-parametric version 
of Wright's variance test (2000), which includes the Rank 
and Signs variance tests. In both cases, the statistics were 
calculated for lags of 2, 4, 8 and 16 days. Considering the 
results of the Wright's Rank and Signs variance test (2000), 
the RWH is rejected in all stock market indices. Therefore, 
the results sustain the conclusion that the analysed financial 
markets do not support the RWH during this period of the 
global pandemic. The values of the variance ratios are lower 
than the unit, which implies that returns are autocorrelated 
over time, and there is a reversion to the mean. No differenc-
es were identified between mature and emerging financial 
markets. Under these conditions, markets tend to overreact 
to information – whether good or bad news – eventually ad-
justing in the following days. The high sensitivity of prices 
to the arrival of new information was due to the climate of 
pessimism and uncertainty experienced by investors during 
the sample period studied. Additionally, the hypothesis of 
informational efficiency of the financial markets may be 
questioned. These results are corroborated by the studies of 
the authors Aggarwal (2018), and Sadat and Hasan (2019), 
as well as partially by those of Ngene, Tah and Darrat (2017), 
Abakah, Alagidede, Mensah and Ohene-Asare (2018), and 
Malafeyev et al. (2019).
Table 6 shows that the results of the DFA exponents are 
demonstrated, showing that the financial markets display 
signs of (in)efficiency in its weak form. The persistence in 
the yields is then substantiated, i.e. the existence of long 
memories, thus validating the results of the Wright’s Rank 
and Signs variance test (2000), which shows the rejection 
of the RWH. These findings demonstrate that prices do not 
fully reflect the available information and that changes in 
prices are not i.i.d. in all markets. This situation has implica-
tions for investors, since some returns can be expected, thus 
creating opportunities for arbitrage and abnormal returns 
instead of the assumptions of random walk and information 
efficiency.
Table 6. DFA exponent for return. The values of the linear 
adjustments for αDFA always had R
2
 > 0.99
Index DFA exponent (Covid-19)
Botswana 0.61 ≈ 0.0214
Egypt 0.63 ≈ 0.0079
Japan 0.65  ≈ 0.0019
Kenya 0.60  ≈ 0.0073
Morocco 0.62 ≈ 0.0081
Nigeria 0.77 ≈ 0.0190
South Africa 0.64 ≈ 0.0015
UK 0.64  ≈ 0.0029
US 0.59  ≈ 0.0175
Note: The hypotheses are H
0
: α= 0.5 and H
1
: α ≠ 0.5
Source: Authors
Discussion and Conclusions
This study tested the hypothesis of efficiency, in its weak 
form, in the stock markets of Botswana, Egypt, Japan, 
Kenya, Morocco, Nigeria, South Africa, the UK and the 
USA during the period from 2 September 2019 to 2 Septem-
ber 2020. The aim was to determine whether these markets 
have long memories in their returns, i.e. whether past prices 
help to predict future prices. For this purpose, two tests were 
conducted, namely an econometric and an economophysical. 

40
NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
The first tested market efficiency, in its weak form, through 
a non-parametric test, the position test (Ranks) for the ho-
moscedasticity series, and the Signs test for the heteroskedas-
ticity series. The second test examined the time dependency 
in non-stationary data series through the DFA methodology. 
In the first test, the Wright’s Rank and Signs variance ratios 
test was estimated. In both cases, the statistics were calculat-
ed for lags of 2, 4, 8 and 16 days. Considering the results of 
the Rank and Signs variance test, the RWH is rejected in all 
the stock indexes. The results thus support the conclusion that 
Figure 1. Evolution, in return, of the nine financial markets in the period between 02/09/2019 and 02/09/2020
Source: Authors
Table 2. Descriptive statistics, return, of the nine financial markets analysed, in the period from 02/09/2019 to 02/09/2020
Botswana Egypt Japan Kenya Morocco Nigeria South Africa UK US
Mean
-0.001470 -0.001006 0.000298 -0.000407 -0.000504 -0.000946 -6.77E-05 -0.000714 0.000719
Std. Dev.
0.014387 0.013725 0.012811 0.016262 0.011857 0.014550 0.019396 0.017086 0.020652
Skewness
-1.572172 -1.493110 -0.133368 -0.760551 -2.349464 -0.867744 -1.184155 -1.185227 -1.100900
Kurtosis
18.81400 9.589017 8.185755 6.067979 22.43120 8.963956 9.911942 12.71763 14.05248
Jarque-Bera
2848.831*** 73.4786*** 95.4717*** 128.5001*** 379.512*** 422.7801*** 584.9979*** 096.397*** 1391.766***
Observations
263 263 263 263 263 263 263 263 263
Note: *** represent significance at 1%.
Source: Authors
the RWH is not backed up by the financial markets analysed 
during this period of the global pandemic. The values of the 
variance ratios are lower than the unit, implying that returns 
are autocorrelated over time. There is a reversion to the mean 
and no differences between mature and emerging financial 
markets. Under these conditions, markets tend to overreact 
to information – irrespective of whether the news is good or 
bad – eventually correcting in the following days.
The second DFA test shows signs of (in)efficiency in its 
weak form. Indicating persistence in profitability, or the 
existence of long memories, thus validates the results of the 
Wright’s Rank and Signs variance test, which also shows 
the rejection of the RWH. These findings reveal that prices 
do not fully reflect the available information and that price 
changes are not i.i.d., in all markets.

41
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Table 3. Levin, Lin and Chu (2002) stationary test, applied to the nine financial markets for the period from 09/02/2019 to 
09/02/2020
Method Statistic Prob.***
Levin, Lin & Chut*
-46.9363 0.0000
Intermediate results on UNTITLED
Series
2nd Stage
Coefficient
Variance of Reg HAC of Dep. Lag Max Lag Bandwidth Obs
Botswana -0.96947 0.0002 1.E-05 0 15 40.0 262
Egypt -0.71834 0.0002 3.E-06 0 15 122.0 262
Japan -0.87115 0.0002 3.E-06 0 15 96.0 262
Kenya -0.81164 0.0002 4.E-06 1 15 131.0 261
Morocco -0.80662 0.0001 6.E-06 0 15 45.0 262
Nigeria -0.70982 0.0002 1.E-05 0 15 34.0 262
South Africa -1.05047 0.0004 1.E-05 0 15 66.0 262
UK -1.00337 0.0003 1.E-05 0 15 58.0 262
US -0.85068 0.0003 3.E-05 6 15 30.0 256
Coefficient t-Stat SE Reg mu* sig* Obs
Pooled -0.86535 -39.695 1.007 -0.508 0.740 2351
Note: *** represent significance at 1%.
Source: Authors
Table 4. Hadri (2000) stationary test, applied to the nine financial markets for the period from 09/02/2019 to 09/02/2020
Method Statistic Prob.***
Hadri Z-stat
2.45648 0.0070
Heteroscedastic Consistent Z-stat
2.79639 0.0026
Intermediate results on UNTITLED
Series LM Variance HAC Bandwidth Obs
Botswana 0.1333 0.000211 1.0 263
Egypt 0.0927 0.000239 1.0 263
Japan 0.1225 0.000215 3.0 263
Kenya 0.0855 0.000363 3.0 263
Morocco 0.1393 0.000167 1.0 263
Nigeria 0.1265 0.000351 4.0 263
South Africa 0.0754 0.000416 6.0 263
UK 0.0843 0.000339 5.0 263
US 0.0911 0.000322 5.0 263
Note: *** represent significance at 1%.
Source: Authors

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
Figure 2. Stability tests performed on the residuals of the nine financial markets in the period from 02/09/2019 to 
02/09/2020

43
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Figure 3. Stationary tests with breaks in the structure of Clemente et al. (1998), in return, related to the nine financial 
markets in the period from 09/02/2019 to 09/02/2020

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020
Null Hypothesis: Botswana is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 7.769864 262 0.0000
Wald (Chi-Square) 60.68542 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.519976 0.061780 -7.769864 0.0000
4 0.285238 0.115580 -6.184123 0.0000
8 0.133499 0.182748 -4.741497 0.0000
16 0.094114 0.271938 -3.331219 0.0010
Null Hypothesis: Botswana is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 6.054460 262 0.0000
Wald (Chi-Square) 38.17342 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.625954 0.061780 -6.054460 0.0000
4 0.488550 0.115580 -4.425070 0.0000
8 0.351145 0.182748 -3.550539 0.0000
16 0.315840 0.271938 -2.515867 0.0040
Null Hypothesis: Egypt is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 6.083644 262 0.0000
Wald (Chi-Square) 40.47185 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.624151 0.061780 -6.083644 0.0000
4 0.313415 0.115580 -5.940335 0.0000
8 0.179850 0.182748 -4.487867 0.0000
16 0.106560 0.271938 -3.285454 0.0020

45
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Egypt is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 3.368337 262 0.0060
Wald (Chi-Square) 11.75573 4 0.0230
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.839695 0.061780 -2.594769 0.0060
4 0.610687 0.115580 -3.368337 0.0010
8 0.515267 0.182748 -2.652461 0.0070
16 0.448473 0.271938 -2.028133 0.0290
Null Hypothesis: Japan is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 8.090627 262 0.0000
Wald (Chi-Square) 66.69285 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.500159 0.061780 -8.090627 0.0000
4 0.307603 0.115580 -5.990621 0.0000
8 0.162038 0.182748 -4.585334 0.0000
16 0.105081 0.271938 -3.290890 0.0010
Null Hypothesis: Japan is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 7.413625 262 0.0000
Wald (Chi-Square) 55.36321 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.541985 0.061780 -7.413625 0.0000
4 0.354962 0.115580 -5.580872 0.0000
8 0.255725 0.182748 -4.072677 0.0000
16 0.211832 0.271938 -2.898335 0.0050
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020 (continued)

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
Null Hypothesis: Kenya is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 5.354766 262 0.0000
Wald (Chi-Square) 29.69610 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.757748 0.061780 -3.921185 0.0000
4 0.381095 0.115580 -5.354766 0.0000
8 0.209973 0.182748 -4.323031 0.0000
16 0.119039 0.271938 -3.239563 0.0010
Null Hypothesis: Kenya is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 3.953933 262 0.0000
Wald (Chi-Square) 15.92664 4 0.0020
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.755725 0.061780 -3.953933 0.0000
4 0.618321 0.115580 -3.302291 0.0000
8 0.507634 0.182748 -2.694232 0.0040
16 0.468511 0.271938 -1.954446 0.0350
Null Hypothesis: Morocco is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 6.847880 262 0.0000
Wald (Chi-Square) 47.24316 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.576937 0.061780 -6.847880 0.0000
4 0.378446 0.115580 -5.377687 0.0000
8 0.232358 0.182748 -4.200545 0.0000
16 0.153260 0.271938 -3.113724 0.0010
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020 (continued)

47
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Null Hypothesis: Morocco is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 4.695296 262 0.0000
Wald (Chi-Square) 22.93522 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.709924 0.061780 -4.695296 0.0000
4 0.603053 0.115580 -3.434383 0.0010
8 0.530534 0.182748 -2.568919 0.0130
16 0.400763 0.271938 -2.203577 0.0150
Null Hypothesis: Nigeria is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 6.476426 262 0.0000
Wald (Chi-Square) 42.91433 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.599885 0.061780 -6.476426 0.0000
4 0.391809 0.115580 -5.262071 0.0000
8 0.204557 0.182748 -4.352669 0.0000
16 0.127734 0.271938 -3.207590 0.0010
Null Hypothesis: Nigeria is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 4.571735 262 0.0000
Wald (Chi-Square) 22.14425 4 0.0010
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.717557 0.061780 -4.571735 0.0000
4 0.515267 0.115580 -4.193909 0.0000
8 0.381679 0.182748 -3.383455 0.0010
16 0.230916 0.271938 -2.828157 0.0030
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020 (continued)

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
Null Hypothesis: South Africa is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 7.221207 262 0.0000
Wald (Chi-Square) 52.90245 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.553872 0.061780 -7.221207 0.0000
4 0.283339 0.115580 -6.200557 0.0000
8 0.181556 0.182748 -4.478529 0.0000
16 0.116130 0.271938 -3.250261 0.0010
Null Hypothesis: South Africa is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 4.818856 262 0.0000
Wald (Chi-Square) 25.50291 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.702290 0.061780 -4.818856 0.0000
4 0.473282 0.115580 -4.557161 0.0000
8 0.410305 0.182748 -3.226813 0.0000
16 0.326336 0.271938 -2.477269 0.0080
Null Hypothesis: The UK is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 8.044168 262 0.0000
Wald (Chi-Square) 64.89393 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.503030 0.061780 -8.044168 0.0000
4 0.282822 0.115580 -6.205027 0.0000
8 0.177048 0.182748 -4.503196 0.0000
16 0.107695 0.271938 -3.281279 0.0000
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020 (continued)

49
Rui Dias, João M. Pereira, Luísa Cagica Carvalho: Are African Stock Markets Efficient? 
A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic
Null Hypothesis: The UK is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2)* 3.970425 262 0.0003
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.466014 0.134491 -3.970425 0.0001
4 0.239752 0.239710 -3.171532 0.0015
8 0.148832 0.367746 -2.314553 0.0206
16 0.071438 0.524701 -1.769699 0.0768
Null Hypothesis: The US is a random walk (rank score variance ratio)
Joint Tests
Value df Probability
Max |z| (at period 2) 10.25450 262 0.0000
Wald (Chi-Square) 113.7720 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.366475 0.061780 -10.25450 0.0000
4 0.244683 0.115580 -6.535007 0.0000
8 0.151129 0.182748 -4.645026 0.0000
16 0.078112 0.271938 -3.390064 0.0010
Null Hypothesis: The US is a martingale (sign variance ratio test)
Joint Tests
Value df Probability
Max |z| (at period 2) 7.413625 262 0.0000
Wald (Chi-Square) 55.36321 4 0.0000
Individual T ests
Period Var. Ratio Std. Error z-Statistic Probability
2 0.541985 0.061780 -7.413625 0.0000
4 0.354962 0.115580 -5.580872 0.0000
8 0.255725 0.182748 -4.072677 0.0000
16 0.211832 0.271938 -2.898335 0.0050
Source: Authors
Table 5. Tests of the Wright’s Rank and Signs Ratios (2000), in return, referring to the nine financial markets in the period 
from 09/02/2019 to 09/02/2020 (continued)

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 68 No. 1 / March 2022
In reply to the research question, evidence was found in the 
results of both tests which confirm that mature and emerging 
financial markets show signs of (in)efficiency in their weak 
form. These findings have implications for investors, as 
some returns can be expected, thus creating opportunities 
for arbitrage and abnormal returns. 
The overall conclusion that is to be highlighted, as support-
ed by the results obtained through the tests performed using 
econometric and mathematical models, is that the global 
pandemic has had a significant impact on the memory prop-
erties of the markets analysed. The results show that the 
markets have persistence and long memories in their returns, 
implying in return that investors will be able to obtain 
abnormal returns without incurring additional risk. This 
study suggests that, in order to mitigate risk and improve 
portfolio efficiency, investors should diversify their portfoli-
os and invest in less risky markets. 
As for future research suggestions, this study used general 
indexes of a daily frequency to analyse efficiency in its weak 
form. In the continuation of this study, it would also be inter-
esting to use higher frequency data, intraday-based, quotes 
per minute, to perform a more refined analysis of the data 
and highlight more robust results.
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Ali so afriški borzni trgi učinkoviti? Primerjalna analiza 
med šestimi afriškimi trgi, Združenim kraljestvom, 
Japonsko in ZDA v obdobju pandemije
Izvleček
Namen te študije je preizkusiti in primerjati hipotezo učinkovitega trga v njeni šibki obliki na borznih trgih Bocvane, Egipta, 
Kenije, Maroka, Nigerije, Južne Afrike, Japonske, Združenega kraljestva in ZDA od 2. septembra 2019 do 2. septembra 2020. 
Študija temelji na naslednjem raziskovalnem vprašanju: Ali je globalna pandemija (covida-19) v svoji šibki obliki zmanjšala 
učinkovitost afriških finančnih trgov v primerjavi z razvitimi trgi Združenega kraljestva, Japonske in ZDA? Rezultati potrju-
jejo dokaze, da finančni trgi, analizirani v obdobju te globalne pandemije, ne podpirajo hipoteze naključnega sprehoda. Vred-
nosti variančnih razmerij so nižje od ena, kar pomeni, da se donosi sčasoma samokorelirajo. Ugotovljen je bil tudi povratek 
k povprečju, pri čemer razlike med razvitimi finančnimi trgi in tistimi, ki so v vzponu, niso bile prepoznane. To potrjujejo 
eksponenti detrendne analize fluktuacije (DFA), ki prikazujejo, da finančni trgi kažejo znake (ne)učinkovitosti v svoji šibki 
obliki, kar kaže na obstojnost donosa. S tem implicirajo obstoj dolgih spominov in potrjujejo rezultate Wrightovega (2000) 
testa variance, kar dokazuje zavrnitev hipoteze slučajnega hoda.
Ključne besede: afriški borzni trgi, hipoteza učinkovitega trga, povprečna reverzija, naključni sprehod