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THE EFFECT OF GENERAL ELECTIONS ON STOCK PRICES
FOR FIRMS LISTED IN THE NAIROBI SECURITIES EXCHANGE
KABIRU JAMES
D61/72939/2012
A MANAGEMENT RESEARCH PROJECT SUBMITTED IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
AWARD OF MASTERS OF BUSINESS ADMINISTRATION (MBA),
SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI
NOVEMBER 2014
DECLARATION
I declare that this project is my original work and has not been submitted for an award of
a degree in any other University for examination/ academic purposes.
SIGNATURE …………………………………………DATE ………………………….
KABIRU JAMES
D61/72939/2012
This Research project has been submitted for examination with my approval as the
University Supervisor.
SIGNATURE …………………………………………DATE ………………………….
DR. J.O. ADUDA
ii
DEDICATION
This research project is dedicated to all my family members. Their support for this course
will always remain entrenched in me.
iii
ACKNOWLEDGEMENT
I wish to sincerely appreciate my supervisor Dr J. Aduda for the professional advice and
guidance extended while udertaking this research project. Particularly am grateful for the
timely and well intended instructions provided throughout the study. I also acknowledge
all my lecturers and fellow students for their contributions towards this research. Special
thanks to my colleague Esther for ensuring that the momentum to clear the Project was
sustained.
To my family and friends, kindly accept my appreciation for your great support and for
allowing me time to concentrate on the project.May God bless you mightly.
iv
ABSTRACT
The relationship between information flow and asset prices behaviour is a key topic in
finance. In this project, the ojective was to investigate the effects of political events on
the stock market performance at the Nairobi Securities Exchange (NSE). In particular, the
study examined whether political-related events mainly the national general elections and
their results contain information regarding the changes in prices and volatility at the
NSE.Several theories were applied and used to bring out the issue of information flow
and stock price volatility. The study was based on a political variable (general elections)
event study methodology to establish the behavior of the NSE performance around the
sample period, 1997 to 2013. The population of this study comprised of all the firms
trading at the NSE in the above period. As per the records at the Nairobi Securities
Exchange, there were 61companies listed by March 2013. The period studied cut across
beginning the second election held in Kenya under the multiparty rule in 1997, first
regime change of 2002, the turbulent election period of 2007 and a second regime change
election event of 2013. The study found that the NSE 20 share index exhibited
seasonality over the months from the year 1997 to 2013. The findings concluded that
market reaction to elections is highly negative or positive depending on the election being
analysed. The information content in the general election is therefore useful for valuing
the securities in the markets.These findings have important implications for the optimal
strategies of risk-averse stock market investors.
v
TABLE OF CONTENTS
Contents
Page
DECLARATION ................................................................................................................ ii
DEDICATION ................................................................................................................... iii
ACKNOWLEDGEMENT ................................................................................................. iv
ABSTRACT .........................................................................................................................v
TABLE OF CONTENTS ................................................................................................... vi
LIST OF TABLES ............................................................................................................. ix
LIST OF FIGURES .............................................................................................................x
ABBREVIATIONS ........................................................................................................... xi
CHAPTER ONE ................................................................................................................1
INTRODUCTION..............................................................................................................1
1.1 Background of the Study ...............................................................................................1
1.1.1 General Elections ........................................................................................................2
1.1.2 Stock Returns ..............................................................................................................3
1.1.3 General Elections and Stock Returns ..........................................................................5
1.1.4 Nairobi Securities Exchange .......................................................................................5
1.2 Research Problem ..........................................................................................................7
1.3 Objective of the Study ...................................................................................................8
1.4 Value of the Study .........................................................................................................8
CHAPTER TWO .............................................................................................................10
LITERATURE REVIEW ...............................................................................................10
2.1 Introduction ..................................................................................................................10
2.2 Theoretical Review ......................................................................................................10
2.2.1 Efficient Market Hypothesis .....................................................................................10
vi
2.2.2 Modern Portfolio Theory ..........................................................................................11
2.2.3 The Random Walk Hypothesis .................................................................................11
2.3 Determinants of Stock Returns ....................................................................................12
2.4 Empirical Literature Review ........................................................................................13
2.6 Summary ......................................................................................................................19
CHAPTER THREE .........................................................................................................21
RESEARCH METHODOLOGY ...................................................................................21
3.1
Introduction .........................................................................................................21
3.2
Research Design ..................................................................................................21
3.3
Population and Sampling Design ........................................................................21
3.4
Data Collection ....................................................................................................22
3.5
Data Analysis ......................................................................................................22
CHAPTER FOUR ............................................................................................................26
DATA ANALYSIS AND INTEPRETATION ...............................................................26
4.1
Introduction .........................................................................................................26
4.2
Descriptive Statistics ...........................................................................................26
4.3
Stock Market Performance and 1997 general election ........................................28
4.4
Stock Market Performance and 2002 General Election ......................................31
4.5
Stock Market Performance and 2007 general election ........................................33
4.6
Stock Market Performance and 2013 general election........................................35
4.7
Tests of Significance ...........................................................................................37
4.8
Summary and Interpretation of the Findings .......................................................40
4.8.1 Summary ...................................................................................................................40
4.8.2 Interpretation .............................................................................................................41
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4.8.3 Previous Studies ........................................................................................................41
CHAPTER FIVE .............................................................................................................42
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS .................................42
5.1
Summary .............................................................................................................42
5.2
Conclusions .........................................................................................................43
5.3
Recommendations ...............................................................................................43
5.4
Limitations of the Study ......................................................................................44
5.5
Suggestions for Further Research........................................................................45
REFERENCES .................................................................................................................47
APPENDICES ..................................................................................................................51
APPENDIX 1: LISTED FIRMS AT NAIROBI SECURITIES EXCHANGE .................51
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LIST OF TABLES
Table 4.1: 1997 Abnormal returns and Cumulative abnormal……................................. 29
Table 4.2: Abnormal returns and Cumulative abnormal returns……………………...…32
Table 4.3: Abnormal returns and Cumulative abnormal returns………………………...34
Table 4.4: Abnormal returns and Cumulative abnormal returns………………………...36
Table 4.5: Descriptive Statistics for Abnormal Returns………………………………....38
Table 4.6: T – test on Abnormal Returns…………………………………………..……38
Table 4.7: Descriptive Statistics for Cumulative Abnormal Returns…………………....39
Table 4.8: T – test for Cumulative Abnormal Returns…………………………………..40
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LIST OF FIGURES
Figure 4.1: NSE 20 Share Índex Performance……………...………............................... 27
Figure 4.2: NSE Market Returns………………………………………………………...27
Figure 4.3: NSE 20 share index performance 1997 general elections………………..….28
Figure 4.4: 1997 General elections return, abnormal returns and Cumulative
returns……………………………………………………...………….30
Figure 4.5: NSE 20 share index performance 2002 general elections…………………...31
Figure 4.6: 2002 General elections return, abnormal returns and Cumulative
returns……………………………………………………………...….33
Figure 4.7: NSE 20 share index performance 2007 general elections…………………...33
Figure 4.8: 2007 General elections return, abnormal returns and Cumulative
returns……………………………………………………………...….35
Figure 4.9: NSE 20 share index performance 2013 general elections………………...…35
Figure 4.10: 2013 General elections return, abnormal returns and Cumulative
returns……………………………………………………..…………..37
x
ABBREVIATIONS
ANOVA
-
Analysis of Variances
CAR
-
Cumulative Abnormal Returns
FDI
-
Foreign Direct Investment
ICC
-
International Criminal Court
KRA
-
Kenya Revenue Authority
MBA
-
Masters of Business Administration
MM
-
Market Model
NSE
-
Nairobi Securities Exchange
OECD
-
Organization for Economic Cooperation and Development
PBC
-
Political Business Cycle
SPSS
-
Statistical Package for Social Sciences
UIH
-
Uncertain Information Hypothesis
US
-
United States
USA
-
United States of America
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CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Political risk is one of the crucial factors influencing the operation of a country‟s
financial market. It can come in many forms such as a new piece of legislation, coup, an
election, or a change in the country‟s regime. The performance of a stock market of an
economy is of interest to various parties including investors, capital markets, the stock
exchange and government among others. Stock market performance is influenced by a
number of factors key among them the activities of governments and the general
performance of the economy. Economic activities do affect the performance of the stock
markets. Other factors that affect markets performance include availability of other
investment assets, change in composition of investors, and markets sentiments among
other factors (Mendelson, 1976).
The relationship between politics and investor behaviour has been studied in numerous
countries and in various contexts. Though, there is little consensus among previous
studies and many of these have been concentrated on political events in a single country.
Previous research suggests that the political uncertainty around elections creates
economic uncertainty, which increases investors risk aversion. Though, the conclusions
about how stock prices are affected by political events vary a lot depending on type of
event and depending on the country investigated. How stock markets are influenced by
various events and how abnormal returns occur are of great interest to both investors and
researchers (Lehander and Lönnqvist, 2012).
Maning (1989) showed that British Telecom Shares, though not the market as a whole,
reacted to opinion polls surrounding the 1987 General elections in the face of the
impending nationalization. Niederhoffer, Gibbs and Bullock (1970), Peel and Pope
(1993) and Gemmil (1992) examine the stock price behaviours during governmental
and/or congressional elections in various developed countries, and they find some
inefficiency in share prices around the time of elections, implying a profitable trading
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rule. They argue that changes in government administration caused by elections tend to
affect financial policies or legislation, thereby significantly affecting stock prices.
1.1.1 General Elections
The Political Business Cycle (PBC) that was pioneered by Nordhaus (1975) pointed out
that within an incumbent‟s term in office there is a predictable pattern of policy, starting
with relative austerity in early years and ending with the potlatch right before elections.
In the PBC literature, there are two schools of thought that try to explain how the political
process induces cycles in stock market performance. On one hand, the “opportunistic”
PBC theory argues that the incumbent governments use expansionary policy measures to
improve the
economic situation just before an upcoming election. The existence of this
government cycles, also known as presidential cycles in the case of the USA, would
imply that significant and positive returns should be observed in the months preceding an
election. However, those policy moves having only transitory effects could be foreseen
by investors and, if so, no effect on the stock market should be perceived. On the other
hand, the “partisan” PBC theory argues that a “partisan” cycle is detectable in stock
market returns because left-wing governments, unlike right–wing governments, focus
more on expansionary policies, while the right-wing governments are more worried about
the control of the inflation. It implies that differences in the ideological composition of
the governments will be reflected in economic policies and, as a consequence, in the
stock price behavior.
The general election periods are recurring in nature and may affect both the political and
investment environment of a given country. Campello, (2007) observed that upcoming
general elections may create uncertainty which may affect investors‟ decisions and
behavior. Changes in investment behavior are reflected from the activities at the
Securities Exchange. Bear markets tend to occur at the end of the term year of the party
in office while bull markets occur two or three years after elections.
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1.1.2 Stock Returns
Fisher and Jordan, (1995) posit that investors generally attempt to beat the market by
identifying undervalued shares and buying them before their prices rise and look for
overvalued shares in order to sell them before their prices fall. This implies that an
investor„s judgment of the true worth of the shares may be different from the stock
market judgment as seen in the current price of the shares. Theoretical explanations for
the pricing of securities according to Fisher and Jordan (1995) and Fama (1970) are
fundamental analysis, technical analysis, random walk and the Efficient market
Hypothesis ideologies.
Mishkin and Eugene, (2002) observed that the performance of the stock market is
influenced by a number of factors. They include the activities of governments, policies,
political process and the general performance of the economy. Other factors that affect
the stock markets performance include availability of other investments assets, change in
composition of investors, Economic activities and markets sentiments among others.
Semi-strong form efficiency market hypothesis asserts that all publicly available
information is fully reflected in security prices. It is not therefore possible for technical
analysts to beat the market by exploiting public information. The elections are unique
events in that the date of an election is certainly known in advance and only the outcome
is uncertain. The outcomes that are anticipated from the market often cause prices to
move to the implied direction before the date of elections. If the market is semi-strong
efficient, the adjustment of prices to the outcome of elections should occur in a very short
period of time and there are no trading strategies adopted to earn abnormal returns. On
the other hand, if any systematically abnormal returns can be found around elections and
used to beat the market, then this phenomenon of election patterns can be viewed as
challenging market efficiency. A market where prices reflect all past, public and private
information exhibits the strong form efficiency. In this market even if certain investors
have monopolistic access to inside information, they cannot make superior returns (Fama,
1970).
3
Black, (1988) argues that the level of the market is affected by the public's confidence in
the market and the breadth of its participation. The market will be higher when
participation is broad instead of narrow. When more people are willing to share in the
risk of the market, each one bears less risk. This means that the expected return on the
market can be lower and the market level higher. That element can be termed as liquidity.
It often refers to the breadth of interest in a specific stock. When a stock has a liquid
market, investors can buy or sell a relatively large amount in a relatively short time
without affecting the price too much. When there is broad public participation in the
stock market, the level of the market will be high, and a change in one group's desired
holdings won't cause a big change in price; other groups will take up the slack. Such a
market will be less volatile than one with narrow participation.
Ofek and Richardson (2003) showed that investor enthusiasm for stocks could not be
offset by pessimistic investors because of short sale constraints and lock-up periods.
Nevertheless, it was investor optimism that drove the prices up. Their view is that
speculative bubbles are formed because of unusually high optimism of investors. A high
level of social mood influences investor optimism. The peaking of a very high social
mood causes investors to make decisions based more on emotion (optimism) than
rigorous evaluation. The cognitive evaluation analysis illustrates that stock prices have
become too high, yet the emotion of optimism becomes a stronger influence in the
decision-making process. The outcome is that investors keep buying stocks and drive
prices far above fundamental value. One way the social mood may influence investors is
through confirmation by other investors.
Irungu, (2012) observed that the information made by election announcements is useful
for valuing the securities though the market do not value the information contained in a
professional election such as the one in 2002. The average cumulative abnormal returns
exhibited a reducing trend in the periods preceding announcement and a slower increase
after announcement pointing to market absorption of the information in the long run
period after the announcement.
4
1.1.3 General Elections and Stock Returns
Bialkowski, et al., (2008) posit that the implications of general elections for investors in
stocks are tangible and important. Risk-averse agents require an adequate premium
whenever they need to take on additional risks. They observed that typical investors are
not fully diversified internationally, and it may occasionally happen that they find that all
their wealth is invested in a country with upcoming elections. Therefore, the investigation
into whether investors are appropriately compensated for bearing political risk associated
with elections is crucial. It turns out that the premium offered for the election risk is
rather modest and acceptable only for investors with a relatively low degree of risk
aversion.
Fama (1965) confirmed that stock prices are correlated with future economic activity in
statistical regressions. Confidence in the President may implicitly reflect the underlying
economic conditions, which are important in determining stock prices. Booth and Booth
(2003) found that the difference between the stock returns in the first half and those in the
second half of the Presidential term are economically and statistically significant.
Santa-Clara and Valkanov (2003) observed that the market excess return was higher
under Democrat than Republican presidencies throughout the period from 1927 to 1998
in the United States of America. This anomaly cannot be explained away by variation in
business condition proxies. Additional evidence is provided by Nofsinger (2004), who
contends that the stock market is a barometer of public sentiment and its movements can
indicate whether incumbents will be re-elected.
1.1.4 Nairobi Securities Exchange
The securities exchange has been perceived by many as the backbone for most
contemporary economies, serving a critical need of raising capital funds for companies at
a reasonably low cost as compared to other sources of finance such as borrowing. The
securities exchange serves two critical functions; it provides a critical link between
companies that need funds to set up new businesses or to expand their current operations
and investors that have excess funds to invest in such companies and it provides a
5
regulated market place for buying and selling of shares at prices determined by supply
and demand, not withstanding other macroeconomic fundamentals such as interest and
inflation rates (Sunde and Sanderson, 2009).
In Kenya, dealing in shares and stocks started in the 1920's when the country was still a
British colony. However the market was not formal as there did not exist any rules and
regulations to govern stock broking activities. Trading took place on a „gentleman's
agreement.‟ Standard commissions were charged with clients being obligated to honor
their contractual commitments of making good delivery, and settling relevant costs. At
that time, stock broking was a sideline business conducted by accountants, auctioneers,
estate agents and lawyers who met to exchange prices over a cup of coffee. Because
these firms were engaged in other areas of specialization, the need for association did not
arise (http://www.nse.co.ke).
In 1951, an Estate Agent by the name of Francis Drummond established the first
professional stock broking firm. He also approached the then Finance Minister of Kenya,
Sir Ernest Vasey and impressed upon him the idea of setting up a stock exchange in East
Africa. The two approached London Stock Exchange officials in July of 1953 and the
London officials accepted to recognize the setting up of the Nairobi Stock Exchange as
an overseas stock exchange (Muga, 1974).
In 1954 the Nairobi Stock Exchange was then constituted as a voluntary association of
stockbrokers registered under the Societies Act. Since Africans and Asians were not
permitted to trade in securities until after the attainment of independence in 1963, the
business of dealing in shares was confined to the resident European community. At the
dawn of independence, stock market activity slumped due to uncertainty about the future
of independent Kenya (http://www.nse.co.ke).
The general elections in Kenya are guided by the constitution which provides for general
elections to be held after every five years. For several decades following its
independence, the Republic of Kenya was widely regarded as one of the most stable
6
countries in an otherwise volatile region. But as has been observed this reputation began
to change following the beginning of a transition to multi-party democracy in the early
1990s. Lusinde (2012) has argued that this situation will not change since a key element
in Kenya‟s general elections is the role of personalities in elections.
The elections which gave rise to the first independence were held in May 1963, under the
supervision of the colonial government. The 1969,1974,1979,1983 and 1988 general
elections were held under single party system. The 1992, 1997, 2002, 2007 and 2013
general elections were held under multiparty system after the constitution was amended
in 1991 to multiparty system in Kenya, (Common wealth, 2006).
1.2 Research Problem
The analysis of political cycles in stock market returns has been mostly conducted in the
United States, and therein in the context of presidential elections. Part is generic to the
extent that institutional rigidities in the political cycle-mandated terms in office for
example impose structure upon market returns. Herbst and Slinkman (1984), examined
the period from 1926-1977 and found a 48-month cycle during which returns were higher
than average, peaking in November during presidential elections. Huang (1985) used data
from 1932-1979 and discovered that stock returns were systematically higher in the last
half of a political term than in the first, as did Hensel and Ziemba (1995), though with
small and large caps. On this basis, Hensel and Ziemba (1995) suggested that political reelection campaigns create policies that stimulate the economy and are positive for stock
returns.
The opportunistic Political Business Cycle (PBC) implies that policy-makers
systematically aim for a rise in stock prices preceding elections (Vuchelen 2003), while
the Uncertain Information Hypothesis (UIH) proposed by Brown et al. (1988, 1993)
assumes that investors set prices before an event takes place. In responding to the
increased uncertainty, investors set stock prices below their fundamental values. An
upward corrective trend in security prices will then follow as the election result becomes
7
more certain. As election-induced uncertainty is reduced, the risk-adjusted expected
return should fall and stock prices should rise. However, Mehdian et al. (2008) noted that
the greatest degree of uncertainty resolution and thus the highest observed returns should
be expected in the time period immediately preceding the election date as this is when
media coverage and campaigning are at their peak.
The aim of this research proposal is to study the link between general elections and the
Nairobi Securities Exchange performance. Kenya presents some interesting peculiarities
that deserve special attention. Firstly, the whole issue of pending court cases at the
International Criminal Court (ICC). Secondly, the post-election chaos that resulted from
the 2007-2008 elections affected nearly all the sectors of the economy. In 2007, Foreign
Direct Investment (FDI) was at $729m and dropped by almost 75% to $183m in 2008
after the election violence (KRA, Financial report 2009/2010).
Majority of the local studies reviewed analysed the effects of elections on firm‟s
performance. The studies gave conflicting results, Menge, et al. (2013); Kithinji and
Ngugi (2009) found positive relationship while Irungu (2012) found negative
relationship. Further these studies analysed the entire market without looking at how the
elections affect the different segments of firms listed at the NSE.
This study seeks to answer the following research question.
Do the general elections in Kenya affect the market performance and is the effect the
same in various segments at the NSE?
1.3 Objective of the Study
To investigate whether there is a relationship between the general elections and the
market performance at the Nairobi Securities Exchange.
1.4 Value of the Study
Most of the studies analysing political cycles have been conducted in the United States
(US). The findings of this research will be of importance to academicians, other
8
researchers, investors and the stakeholders at the NSE who include the government as it
will emphasize the need for peace during elections.
To the investors, the study may enlighten them on the behaviour of securities in
anticipation of the related five year cycles following the release of election results in the
country. It will offer investors a springboard against which to plan their strategies. It will
assist them to make decisions whether to buy, hold or sell securities in order to maximize
the returns around the time of this event.
More knowledge will be added to the scholars as other interested researchers may refer to
this study, probably build new ideas around it and some could even test it‟s consistency
in future in order to expand the body of knowledge.
Other stakeholders for example firm managers may use the findings of this study as a
point of reference for evaluating the external environment. This is handy especially when
assessing how anticipated political events might affect the value of their firms. The
investment advisors using these findings will be able to advice their clients make
investment decisions.
The government through the Treasury and Capital Markets Authority could use the
findings of this study to guide the formulation of policies governing the operations of the
securities exchange.
9
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This chapter covers the theoretical literature, empirical literature and a summary of the
previous works undertaken on the relationship between stock prices and the effect of the
general elections with a view to answer the research question.
2.2 Theoretical Review
A number of hypotheses have been advanced in the theoretical literature review to
explain the relationship between information and stock market performance. This section
will therefore review the relationship between information and the stock market
performance based on existing theories and academic arguments.
2.2.1 Efficient Market Hypothesis
The Efficient Market Hypothesis (EMH), introduced by Markowitz in 1952 and
subsequently named by Fama in 1970 assumes that financial markets incorporate all
public information and asserts that share prices reflect all relevant information. Correct
information is important in forming expectations and allowing investors to correctly
process all available information, and where the discount rate is consistent with a
normatively acceptable preference specification (Samuelson and Fama, 1965).
The EMH‟s concept of informational efficiency has a Zen-like, counter-intuitive flavour
to it. The more efficient the market, the more random the sequence of price changes
generated by such a market, and the most efficient market of all is one in which price
changes are completely random and unpredictable. This is not an accident of nature, but
is in fact the direct result of many active market participants attempting to profit from
their information. Driven by profit opportunities, an army of investors vigorous pursue
even the smallest informational advantages at their disposal and in doing so they
incorporate their information into market prices and quickly eliminate the profit
opportunities that first motivated their trades (Samuelson, 1965).
10
2.2.2 Modern Portfolio Theory
In stock markets, a stock price goes up or down on a daily basis. The return of a stock is a
ratio of the closing price to the opening price of the stock on daily basis. When investors
buy stocks, they always think about how much the profit they will get in return. In
general, if the expected return is high, the risk is also high. Modern portfolio theory by
Markowitz explains how investors should select a portfolio and make the highest possible
return from a certain level of risk or get the lowest possible risk for a certain level of
return. There is a positive relationship between the risk and the expected return of a
financial asset. When the risk of an asset increases, so does its expected return. What this
means is that if an investor is taking on more risk, he is expected to be compensated for
doing so with a higher return. Similarly, if the investor wants to boost the expected return
of the investment, he needs to be prepared to take on more risk (Markowitz, 1952).
2.2.3 The Random Walk Hypothesis
The importance of the EMH stems primarily from its sharp empirical implications many
of which have been tested over the years. Much of the EMH literature before LeRoy
(1973) and Lucas (1978) revolved around the random walk hypothesis (RWH) and the
martingale model, two statistical descriptions of unforecastable price changes that were
initially taken to be implications of the EMH (Fama and Blume, 1966). One of the first
tests of the RWH was developed by Cowles and Jones (1937), who compared the
frequency of sequences and reversals in historical stock returns, where the former are
pairs of consecutive returns with the same sign, and the latter are pairs of consecutive
returns with opposite signs. French and Roll (1986) document a related phenomenon:
stock return variances over weekends and exchange holidays are considerably lower than
return variances over the same number of days when markets are open. This difference
suggests that the very act of trading creates volatility, which may well be a symptom of
Black‟s (1986) noise traders.
11
2.3 Determinants of Stock Returns
Identifying the factors that influence stock returns is a major concern for practice and
academic research. The topic is a focus of numerous studies in empirical finance
(Korteweg, 2009). Research work which is aimed at determining the factors influencing
stock returns of firms provides, a conceptual backdrop necessary to guide the financial
manager in financial structure planning and decision in order to increase the shareholders
wealth.
Prior to 1981, much of the finance literature viewed the present value of dividends to be
the principal determinant of the level of stock prices. However, Leroy and Porter (1981)
and Shiller (1981) found that, under the assumption of a constant discount factor, stock
prices were too volatile to be consistent with movements in future dividends. This
conclusion, known as the excess volatility hypothesis, argues that stock prices exhibit too
much volatility to be justified by fundamental variables. Literature reviewed, nonetheless,
found that stock price movements could not be explained solely by dividend variability as
suggested by the present value model with constant discounting (Campbell and Shiller,
1989).
Shleifer and Vishny, (2000) studied the stock return policies of over 4000 firms from 33
countries around the world. They found that stock return policies vary across legal
regimes in a way that is consistent with the idea that stock return payment is the outcome
of effective pressure by minority shareholders to limit agency behaviour. Firms in
countries with good legal protection of investors tended to have higher payout ratio
compared with firms in countries with weaker legal protection.
Olowoniyi A. O and Ojenike J.O, (2012) in their study found that expected growth would
significantly improve stock return level of firms in developing countries if appropriate
attention is focused on it. Efforts at increasing assets of firms are also expected to raise
the level of listed firms. Lower net profit after tax is also expected to reduce level of
stock return of listed firm. Similarly leverage of firms is also expected to lower the level
of stock return. The finding suggests that attention needs to be paid to improving growth
12
and size of the firms in order to benefit the advantages that could arise from substantial
stock return.
2.4 Empirical Literature Review
Politics have a significant influence on financial markets. Stock markets respond to new
information regarding political decision that may affect domestic and foreign policy. As
such, market efficiency requires that stock markets absorb news and political uncertainty.
Positive stock returns are expected following the resolution of political uncertainty. In
contrast, if the outcome of the political uncertainty does not allow investors to
immediately measure the negative impact on the stock market, then the political outcome
constitutes an uncertainty inducing surprise (Gemmill, 1992).
Just as it is important that networks of transportation, electricity and telecommunications
function properly, so is it essential that payments can be transacted, capital can be saved
and channelled to the most profitable investment projects and that both households and
firms get help in handling financial uncertainty and risk as well as possibilities of
spreading consumption over time. Financial markets constitute an important part of the
total infrastructure for every society that has passed the stage of largely domestic
economies (Vuchelen, 2003).
According to Jesen et al, (1996) stock market which is part of the financial markets
perform among others the following functions in an economy, (i) raising capital for
businesses: the stock exchange provides companies with the facility to raise capital for
expansion through selling shares to investing public,(ii) Mobilizing savings for
investment: when people draw their savings and invest in shares, it leads to a more
rational allocation of resources i.e. by promoting business activity hence benefiting
several sectors such as agriculture, commerce and industry resulting in a stronger
economic growth and higher productivity levels (iii) Redistribution of wealth: by giving
a wide spectrum of people a chance to buy shares and therefore become part owners of
profitable enterprises, the stock market helps to reduce large income inequalities. Both
13
casual and professional stock investors through stock price rise and dividends get a
chance to share profits of promising businesses.
An efficient stock market sector will have the expertise, the institution and the means to
prioritise access to capital by competing users so that an economy manages to realise
maximum output at least cost. This is what economists refer to as the optimum
production level. If an economy does not have efficient financial markets there are
always the risks that scarce capital could be channelled to non-productive investments as
opposed to productive ones, leading to wastage of economic resources and decline (Lee,
1998).
Reduction of search and information costs of transactions at the stock market is essential
to facilitating growth of the market. Search explicit costs for example money spent to
advertise, the desire to sell or purchase a financial asset, and implicit costs such as the
value of time spent in locating counter party. The presence of an organized stock market
reduces search and information costs (Fabbozi, 1995).
Avenue for flotation of private companies and government owned entities which in turn
allow greater growth in case of the supply of assets available for long term investment are
available at the stock market. This leads to wealth redistribution from state and private
companies to the investing public since they can share in the returns of the privatized
entities. The establishment of an efficient market is therefore indispensable for the
economy that is keen on using scarce capital resources to achieve economic growth
(www.nse.co.ke).
Most of the authors who have examined stock returns in relation to both the presidential
cycle and election effect agree their findings warrant the view that politics and market
returns are correlated. McCallum (1978) studied previous United States administrations
and found evidence that stocks showed consistent return patterns dependent upon which
year of their four terms they are serving, but did not believe this could be manipulated by
the controlling power, contrary to the findings of Nordhaus (1975). Nordhaus (1975)
14
findings suggested governments can affect the state of their economy by influencing the
level of unemployment, and may do so strategically to gain re-election.
This behaviour is seen to be negatively associated with stock returns as it is inflationary,
and therefore it is not unreasonable to assume individuals may wish to diversify their
investments among a number of different instruments dependent upon the stage of the
election cycle (Anderson et al., 2008 and Nordhaus, 1975). Anderson et al., (2008) found
stocks and bonds to be more adversely affected than property in periods of higher
inflation, and therefore it may be advantageous for individuals to hedge their investments
dependent upon the level of unemployment.
Booth and Booth (2003) further discovered that returns differed depending upon the
political party which was in power. Their study, as are the majority of studies performed
in this area, focussed on the US, and discovered fixed securities had significantly higher
returns when the ruling party was republican, where small stock excess returns were
higher under democratic administrations.
Higher stock returns under democratic president in the (US) is suggested by Cahan et al.,
(2005) to be a surprising finding, and one that goes against conventional wisdom. As
Nordhaus (1975) explained, one would assume a right wing government would be better
for business, due to their conservative approach to managing economic cycles. Chan et
al., (2005) refer to this apparent contradiction as the presidential puzzle, where real
returns, particularly for small stock business, performed better under democratic
leadership.
Hensel and Ziemba (1995) suggested this may be due to democratic governments
enacting policies aimed at benefiting small business. However the differences they found
between the returns of the two categories of stock were larger than one would expect.
Booth and Booth (2003) found the presidential puzzle to benefit small cap stocks, with no
significant difference between the returns of large cap stocks during the terms of both
democratic and republican presidents.
15
Santa-Clara and Valkanov (2003) noted that large cap stocks do perform better under
democratic presidents, although their performance is not great as that of their smaller
counterparts. They found that large cap stocks tended to perform an average of 7% better,
where small cap stocks produced returns of around 22%. Anderson et al (2008) noted that
the US political system is much more complex than those in other parts of the world, as
the ruling party may not be able to pass major laws or reforms if they do not control the
senate.
Forester and Schmitz (1997) studied the effect US election cycles have on international
returns and found some interesting observations around international stock returns. Their
study showed that stock returns from eighteen Organization for Economic Cooperation
and Development (OECD) countries between the years of 1957 and 1966 appeared to
follow a pattern consistent with the US presidential cycle, thus indicating the effect of the
political cycle may affect more than just the US economy. In their study of eighteen
countries they were able to conclude that US presidential cycles are important when
determining international stock market risk premiums.
Governments have the ability to affect stock returns through the use of both monetary and
fiscal policy (Booth and Booth, 2003; Jensen et al, 1996). However debate still continues
as to whether such moves produce more predictable markets or whether this tends to lead
to inefficiencies within the market. Jacobsen (1999) found that around 50% of traders
tended to act irrationally in 10% of the trades they mad, causing stock prices to exceed
their fundamental values around 10% of the time.
A number of studies examined the long run presidential effect, investors are assumed to
be able to base their investment decisions around the year in which they are in the
presidential cycle (Ferri, 2008). Jensen et al., (1996) and Fama and French (1989) found
that, by examining the term premium, default premium and dividend yield, both stocks
and bonds exhibit a rational in returns, offering no arbitrage opportunities. Furthermore,
McCallum (1978) believes any attempt on behalf of a government to influence an
economy through monetary or fiscal policy will be anticipated by companies and
investors and their effects will therefore be negated.
16
Cahan et al., (2005) contrasts the findings of US studies to their own study of the
Newzealand market and found stock returns to be higher under the right of centre
national party. This is contrary to findings in the US where stock returns did vary under
different governments. Stocks perform better under their left-of-centre democratic party.
This finding is not exclusive to Cahan et al., (2005), but was also discovered by
Worthington (2006), and Anderson et al., (2008). Nordhaus (1975) and Anderson et al.,
(2008) argue that markets perform better under a right wing government. This is true in
the cases of New Zealand and Australia, and is believed to be due to left wing
governments introducing policies that boost employment, of which inflation is a natural
consequence.
Higher levels of employment lead to higher levels of inflation and is reflected in
significantly lower returns (Nordhaus, 1975). Under a national government in New
Zealand, and their equivalent in Australia, the iberal party, returns between 1931 and
2006 were 10.18% and 11.95% per annum respectively, where their labour counterparts
only managed to produce 6.60% and 4.49% per annum (Cahan et al., 2005). This finding
reaffirms those of Anderson et al (2008) and Worthington (2006) that stock performance
differs among political parties, and therefore one may wish to base their investment
decisions accordingly.
Niederhoffer et al. (1970) analyzed the stock market movements in the days and weeks
surrounding US presidential elections, the study of the relationships between politics and
the stock market has generated much research of interest. Thus, a great number of studies
have analyzed several topics such as the influence of economic events on election voting;
the relationship of the expected stock return with economic factors; the link between
stock markets performance and political election dates, and the explanatory power of
political risk in emerging and developed markets.
Recently, some studies have shown new empirical evidence that has boosted the interest
for this type of financial literature. This is the case of the event study by Pantzalis et al.
(2000) that examine stock market behavior around elections on an international scale (33
17
countries) and found that index abnormal returns are generally positive and significant in
the 2 weeks prior to the election week. They noted that this abnormal return is strongest
for elections with the highest degrees of uncertainty, in particular, in countries with low
rankings of political, economic, and press freedom, and elections in which the incumbent
loses. Bialkowski et al. (2008) investigated a sample of 27 OECD countries to test
whether national elections induce higher stock market volatility. Their empirical findings
indicate that investors are still surprised by the ultimate distribution of votes. Stock prices
react strongly in response to this surprise and temporarily elevated levels of volatility are
observed.
Both Santa-Clara and Valkanov (2003), Booth and Booth (2003) have shown that stock
market returns are higher during Democratic than during Republican presidencies at the
USA. They found that this difference is not explained by business-cycle variables and
that it is not concentrated around election dates. Booth & Booth (2003) also noted excess
returns under democratic presidents for a small-cap stock portfolio, while large-cap stock
excess returns are not significantly different from each other during the 1926–1996
periods. Moreover, US stock excess returns are significantly higher in the last two years
than in the first two years of the presidential term.
Vuchelen (2003) focuses on the Belgian market and concludes that when a centre-left
coalition takes office after an election, stock prices slightly increase, whereas a centreright coalition would push stock prices down. Besides, a coalition made up of left-wing
and right-wing parties (without any centre-parties) is said to be perceived as negative by
investors. Leblang and Mukherjee (2005) constructed a model of speculative trading to
show how government partisanship and trader‟s anticipation of electoral victory by the
left-wing or the right-wing party affects the volume of trading and how this, in turn,
affects the mean and volatility of stock prices in both the US and the British equity
markets. Siokis and Kapopoulos (2007) find that different political regimes impact the
conditional variances of the stock market index in Greece, reporting higher volatility
increases in the pre-election period and when the right-wing party is in power.
18
Irungu (2012) investigated the informational content of general election results
announcenment at the Nairobi securities exchange using events study methodology for
the periods 1997 to 2007 and found that the average cumulative abnormal returns
exhibited a reducing trend in the periods preceding announcement and a slower increase
after announcement pointing to market absorption of the information in the long run
period after the announcement.
A study by Menge, et al. (2014) on the effect of elections on stock market returns at the
Nairobi securities exchange adopting events study methodology covering periods
between 2002 and 2013 found that actual stock returns were significantly higher before
elections than after election periods. The results led to the conclusion that the expected
returns as well as the market returns were significantly higher before elections than after
the elections. Their findings concur with the conclusions arrived at by Kithinji and Ngugi
(2009).
The prices of stocks around the world do not move together in an exact manner. This is
because the economic systems in which stock markets are located have dissimilar
environments in terms of taxation, industrial growth, political stability, monetary policies
and other factors. Stock markets may experience a general increase in level referred to as
a bull market or general decrease in price level referred to as bear market. Stagnant prices
or sudden big price movement downward is referred to as stock market crash (Kithinji
and Ngugi, 2009).
2.6 Summary
Though rational partisan theory is persuasive in its focus on electoral uncertainty, it is
silent on the issue of policy uncertainty. Alesina (1987) assumes future policies of
election winners are fixed and known, but it is much more likely that there is some degree
of uncertainty surrounding them. This uncertainty may result from not knowing exactly
what economic policies a given party prefers and the inflation that would result if they
were implemented. Even though it may be easy to rank-order the impact of Left and
Right policies, it may be difficult to know if the victorious parties will implement the
moderate or extreme version of its proposals. Uncertainty may also arise because the
19
effectiveness of a government in implementing policy varies, in part due to changing
logistical competence and in part due to idiosyncrasies of the current institutional context.
A study by Irungu (2012) to investigate the informational content of general election
results announcement at the Nairobi Securities Exchange found that the average
cumulative abnormal returns exhibited a reducing trend in the periods preceding
announcement and a slower increase after announcement pointing to market absorption of
the information in the long run period after the announcement. However Kithinji and
Ngugi (2009) and Menge, et al. (2014) studying the relationship of elections on stock
market returns at the Nairobi Securities Exchange found that actual stock returns were
significantly higher before elections than after election periods. Empirical literature
reviewed has concluded conflicting results as to the affect of elections on stock prices.
This study will investigate whether there is a relationship between the general elections
and the market performance and to further analyse if the effect is the same in various
segments at the NSE.
20
CHAPTER THREE
RESEARCH METHODOLOGY
3.1
Introduction
This chapter outlines the research methodology that was used to enable the researcher
achieve the research objectives. It outlines the research design, the target population and
sampling design, the data collection and the data analysis techniques adopted.
3.2
Research Design
Research design is the blue print used to guide a research study to ensure that it addresses
the research problem. Research design refers to both structure of the research problem,
the framework, organization or configuration of the relationships among variables of a
study and the plan of investigation used to obtain the empirical evidence on those
relationships (Cooper and Schindler, 2010). The study adopted an event study
methodology. The basic concept is to find the abnormal return attributable to the event
being studied by adjusting for the return that stems from the price fluctuation of the
market as a whole (Gilson and Black, 1995). The study was based on a political variable
(general elections) event study methodology to establish the behavior of the NSE
performance around the sample period, 1997 to 2013.
3.3
Population and Sampling Design
Population refers to the total collection of elements about which one wishes to make
inferences (Cooper and Schindler, 2010). The population of this study comprised all the
firms trading at the NSE in the period between 1997 and 2013. As per the records at the
Nairobi Securities Exchange, there were 61 (Appendix 1) companies listed by March
2013. However, the sample size of the study was the 20 firms in the NSE share index.
The index is a representative of the securities exchange performance.
21
3.4
Data Collection
Mugenda and Mugenda (2003) acknowledges there are two types of data; primary and
secondary data. The study used secondary data from the Nairobi Securities Exchange and
the financial statements of the concerned companies. Data obtained covered the period
between 31st December 1997, through 29th December 2002, through 30th December 2007,
and 4th March, 2013.
3.5
Data Analysis
Data analysis is defined as a process of bringing order, structure and meaning to the data
collected so that it can be interpreted and communicated in a research report (Marshall
and Rossman, 2006). The collected secondary data was coded and entered into Statistical
Package for Social Sciences (SPSS, Version 20.0) for analysis. The study used the
following Market Model (MM) steps as outlined by (MacKinlay, 1997);
Step 1: Identification of the event of interest
The event of interest is the effect of general elections on the return of stocks quoted at the
NSE. The dates of elections include 31st December 1997, 29th December, 2002, 30th
December 2007 and 4th March 2013.
Step 2: Definition of the event window
The event window is taken to be 15 days before the election date and 15 days after the
election day. The estimation window is 120 days before the event window and the post
event window is 60 days after the event window.
22
Estimation
Window
-120 days
Post Event
Window
Event Window
-15 days
+15days
+45 Days
Step 3: Selection of the sample set of firms included in the analysis
A sample of 20 firms in the NSE share index was used. Only those companies existing
120 days before election and 60 days after election dates were included. This implies that
the figure of 20 has different companies at some points in time.
Step 4: Prediction of a “normal” return during the event window in the absence of the
event
The study first computed the changes recorded in share prices to determine the actual
return.
𝐴𝑐𝑡𝑢𝑎𝑙 𝑆ℎ𝑎𝑟𝑒 𝑟𝑒𝑡𝑢𝑟𝑛 𝑖𝑛 𝑑𝑎𝑦 𝑡, =
(𝑝 𝑡 −𝑝 𝑡−1 )
𝑝 𝑡−1
*100
Where;
Pt = Price of the security i at time t
Pt-1= Price of the security at time t-1
The changes in the NSE index for the same period were also computed. This was denoted
as the market return.
𝑁𝑆𝐸 20 𝑠ℎ𝑎𝑟𝑒 𝐼𝑛𝑑𝑒𝑥 𝑅𝑒𝑡𝑢𝑟𝑛 𝑖𝑛 𝑡𝑖𝑚𝑒 𝑡(𝑀𝑎𝑟𝑘𝑒𝑡 𝑅𝑒𝑡𝑢𝑟𝑛) =
The following market model was applied;
(𝑁𝑆𝐸𝑡 −𝑁𝑆𝐸𝑡−1 )
𝑁𝑆𝐸𝑡−1
*100
𝐴𝑅 = 𝛼 + 𝛽𝑋 + 𝑒
Where;
AR= actual returns
X = market return
𝛽 = market risk/partial correlation coefficient for market return and actual returns
23
𝛼 = constant
e = error term,
The normal or expected returns were generated from the following;
𝑌 = 𝛼 + 𝛽𝑋
Where;
𝑌 = Expected Return
Step 5: Estimation of the “abnormal” return within the event window, where the
abnormal return is defined as the difference between the actual and predicted returns,
without the event occurring
The research applied the following model to get abnormal returns.
Abnormal Return = Actual Returns -Expected Returns
Step 6: Testing whether the abnormal return is statistically different from zero.
Test statistics was used to measure the statistical significance of the:
a) Cumulative Abnormal Returns (CAR) for each firm
b) Cumulative Abnormal Returns (CAR) for all firms
c) Cumulative Abnormal Returns (CAR) for all firms - across segments in the NSE.
Analysis of variances (ANOVA) was applied for scenario (a) where Cumulative
Abnormal Returns (CAR) mean was compared across 4 electioneering periods to check
whether some electioneering periods had more informational content compared to others.
This approach differs significantly from Menge, et al. (2014) who analysed the CAR for
all firms only. A t-test will be applied for Scenario (b) where mean
Cumulative
Abnormal Returns (CAR) for all firms were aggregated and means of the two periods,
that is, before and after election date checked for significant differences.
Analysis of Variance was applied for scenario (c) where mean Cumulative Abnormal
Returns (CAR) was compared across the various segments. This approach differed
significantly from Menge, Mirie and Kimani (2014) who concentrated on scenario (b)
only.
24
The level of significance for the ANOVA and t-test was 5% (95 % confidence level). If
the significance number found is less than the critical value (
) set at 0.05, then the
conclusion is that the information content of general elections is significant. In other
words, there exists significant difference in abnormal returns before and after the general
elections. Otherwise the events study concludes that general elections do not influence
stock returns.
25
CHAPTER FOUR
DATA ANALYSIS AND INTEPRETATION
4.1
Introduction
This chapter presents the results of the analysis and findings of the study with reference
to the study objectives. The first section gives a summary of the data analysis method
used. The second part gives the findings of the study and it includes relevant tables and
figures that help to explain the results of the data analysis. The last part gives a summary
of findings and interpretation of the results.
4.2
Descriptive Statistics
The objective of the study was to establish the effect of a political event specifically the
general election on the returns at the Nairobi Securities Exchange (NSE). To achieve this
objective, event study methodology was used for four general elections held in Kenya on
31st December 1997, 29th December, 2002, 30th December 2007 and 4th March 2013. The
study analyzed the performance of the securities market before and after the general
elections.
Secondary data obtained from the NSE was compiled and analyzed in Excel format and
then transferred to Statistical Package for Social Sciences (SPSS) for further statistical
data analysis. The study looked at how the Nairobi security exchange has been
performing since the 1997 general election year. The NSE-20 share return was studied for
a period of one year before the 1997 general election to one year after the 2013 elections.
Figure 4.1 and 4.2 below presents the end of month NSE 20 share index movements and
the monthly market returns respectively. As observed from the trendline in figure 4.1, the
NSE share index declined steadily from 1997 to 2002 after which it increased
substantially in the period between 2002 and 2007. Between 2005 and 2006, the market
was volatile ostensibly because of the 2005 referendum. The period after 2007 has been
characterised by seasonality in declines and increases in the share index. There is a
26
decline phase between 2011 and 2012 attributed to the post 2010 constitutional
referendum. There is observed a steady rise in year 2012.
NSE 20 Share Index
6,000
5,000
4,000
3,000
2,000
1,000
1998
2000
2002
2004
2006
2008
2010
2012
Figure 4.1: NSE 20 Share Índex Performance
Figure 4.2 shows the volatility and seasonality of monthly NSE market returns as the
market returns oscillates between positive and negative values over the months.
NSE Percentage Return
20
10
0
-10
-20
-30
1998
2000
2002
2004
2006
2008
Figure 4.2: NSE Market Returns
27
2010
2012
4.3
Stock Market Performance and 1997 general election
The study analysed the stock market performance during the 1997 general election.
NSE 20 Share Index
3,600
3,500
3,400
3,300
3,200
3,100
3,000
2,900
M6
M7
M8
M9
M10 M11 M12
M1
1997
M2
M3
M4
M5
M6
1998
Figure 4.3: NSE 20 share index performance 1997 general elections
Figure 4.3 above, presenting the NSE-20 share index performance trend between mid
1997 and 1998, shows that stock market performance generally declined to November of
the same year before rising till beginning of January. The stock performance since then
declined sharply till mid 1998. This scenario could depict that bad information content
was read from the 1997 election as most investors shied from trading while some sold
their portfolio owing to ucertainty of the outcome of the election.
4.3.1
Abnormal Returns (AR) and Cumulative Abnormal Returns (CAR) for 1997
general elections
Abnormal returns on the indices were computed using a mean-adjusted return approach
as described by Brown and Warner (1985). Daily excess returns were measured by the
mean-adjusted returns approach, that is, for each day and following the event, the
abnormal or excess return from the stock index were calculated by the following
equation.
28
ARt = Rt – R
Where:
ARt:
Is the excess of the expected return for index at time t
Rt:
Is the return on index at the time of event t
R:
Is the average return on the index taken over the interval of 31 days in the
estimation window.
Cumulative abnormal returns (CARs) were also analyzed over the interval of 31 days in
the post-event window. The CAR corresponding to an event that was happening at time t
(j=0) was computed as:
CARt =Σ ARt
Where:
CARt: Is the cumulative abnormal return at time t
ARt:
Is the abnormal return at time t
In contrast to event-day abnormal returns, which show the immediate investors' reaction
on the political event (general election), the 30-day CARs provide an indication of the
market response to the event 30 days following the general election.
Table 4.1: 1997 Abnormal returns and Cumulative abnormal returns
Days
Share
Return
Abnormal return
Index
-15
-14
-13
-12
-11
-10
-9
-8
-7
-6
-5
3049.11
3045.50
3068.72
3077.50
3078.97
3077.97
3063.05
3073.97
3066.67
3069.46
3078.42
Cumulative
Abnormal return
0.25152
-0.1184
0.76244
0.28611
0.04777
-0.0325
-0.4847
0.35651
-0.2375
0.09098
0.29191
-0.0608
-0.4308
0.45008
-0.0262
-0.2646
-0.3448
-0.7971
0.04415
-0.5498
-0.2214
-0.0205
29
-0.0608
-0.4916
-0.0415
-0.0678
-0.3323
-0.6772
-1.4743
-1.4301
-1.98
-2.2013
-2.2218
-4
3088.69
-3
3110.85
-2
3113.12
-1
3117.47
1
3118.78
2
3128.01
3
3148.45
4
3188.54
5
3221.56
6
3273.16
7
3301.67
8
3307.07
9
3353.26
10
3344.21
11
3335.18
12
3341.56
13
3338.09
14
3338.49
15
3338.49
Average return
0.33361
0.71746
0.07297
0.13973
0.0419
0.29613
0.65341
1.27335
1.03539
1.60198
0.8709
0.16356
1.39684
-0.27
-0.27
0.19114
-0.1036
0.01189
0
0.31236
0.02125
0.4051
-0.2394
-0.1726
-0.2705
-0.0162
0.34105
0.96099
0.72303
1.28962
0.55854
-0.1488
1.08448
-0.5823
-0.5824
-0.1212
-0.416
-0.3005
-0.3124
-2.2005
-1.7954
-2.0348
-2.2075
-2.4779
-2.4941
-2.1531
-1.1921
-0.4691
0.82055
1.37909
1.23029
2.31477
1.73243
1.15003
1.02881
0.61283
0.31236
0
3
2
Return
1
Abnormal Return
0
-20
-10
0
10
20
-1
Cumulative Abnormal
Return
-2
-3
Figure 4.4:
1997 General elections return, abnormal returns and Cumulative
returns
30
As presented in figure 4.4 above, the normal and the abnormal returns on average move
in synchronicity during the event period. The Cumulative abnormal returns decline in the
negative before the general election and steadily rises after the event.
4.4
Stock Market Performance and 2002 General Election
The study analysed the stock market performance during the 2002 general election.
NSE 20 share index
2,200
2,000
1,800
1,600
1,400
1,200
1,000
M6
M7
M8
M9
M10 M11 M12
2002
M1
M2
M3
M4
M5
M6
2003
Figure 4.5: NSE 20 share index performance 2002 general elections
Figure 4.5 above shows that the NSE-20 Share Index rose gently but steadily from mid-2002
to 2003. This points to the investors confidence in the then election that led to a regime
change in governance in Kenya.
31
4.4.1
Abnormal Returns (AR) and Cumulative Abnormal Returns (CAR) for 2002
general elections
Table 4.2: Abnormal returns and Cumulative abnormal returns
Days
Share
Return
Abnormal return
Index
-15
1156.59
-14
1159.71
-13
1162.93
-12
1167.18
-11
1165.92
-10
1178.7
-9
1199.87
-8
1225.95
-7
1242.98
-6
1256.53
-5
1270.95
-4
1270.67
-3
1279.09
-2
1298.5
-1
1298.86
1
1317.45
2
1362.85
3
1384.98
4
1446.75
5
1504.2
6
1538.12
7
1565.84
8
1572.12
9
1578.21
10
1551.06
11
1550.88
12
1509.43
13
1488.59
14
1507.11
15
1518.92
Average return
Cumulative
Abnormal return
-0.39014
0.269759
0.277656
0.365456
-0.10795
1.09613
1.796046
2.173569
1.389127
1.090122
1.147605
-0.02203
0.662643
1.517485
0.027724
1.431255
3.446051
1.623803
4.459992
3.970969
2.255019
1.8022
0.401063
0.387375
-1.7203
-0.0116
-2.67268
-1.38065
1.24413
0.783619
0.910448
-1.30059
-0.64069
-0.63279
-0.54499
-1.0184
0.185682
0.885599
1.263121
0.478679
0.179674
0.237157
-0.93248
-0.24781
0.607037
-0.88272
0.520807
2.535603
0.713355
3.549544
3.060522
1.344571
0.891752
-0.50939
-0.52307
-2.63075
-0.92205
-3.58312
-2.2911
0.333682
-0.12683
32
-1.30059
-1.94128
-2.57407
-3.11906
-4.13746
-3.95178
-3.06618
-1.80306
-1.32438
-1.14471
-0.90755
-1.84003
-2.08783
-1.4808
-2.36352
-1.84271
0.69289
1.406245
4.955789
8.016311
9.360882
10.25263
9.743249
9.220176
6.589425
5.667372
2.084248
-0.20685
0.126829
0.0000000000000018
12
10
8
6
Return
4
Abnormal Return
2
Cumulative Abnormal
Return
0
-20
-10
-2
0
10
20
-4
-6
Figure 4.6:
2002 General elections return, abnormal returns and Cumulative
returns
From figure 4.6 above, it is presented that the cumulative abnormal returns remain
negative throughout the pre- event (general election) period and rises after the event. The
normal and abnormal returns on average move in tandem in the event period.
4.5
Stock Market Performance and 2007 general election
The study analysed the stock market performance during the 2007 general election.
NSE 20 Share Index
5,500
5,400
5,300
5,200
5,100
5,000
4,900
4,800
4,700
M6
M7
M8
M9
M10
M11
M12
2007
M1
M2
M3
M4
M5
M6
2008
Figure 4.7: NSE 20 share index performance 2007 general elections
33
Figure 4.7 illustrates that the NSE-20 share performance was erratic, though, receding on
average. The decline was more pronounced between the months of December and January
2008. This may be attributed to the events of the post election violence that scared investors
at the market.
4.5.1
Abnormal Returns (AR) and Cumulative Abnormal Returns (CAR) for 2007
general elections
Table 4.3: Abnormal returns and Cumulative abnormal returns
Days
Share
Return
Abnormal return
Index
-15
5234.54
-14
5205.06
-13
5221.96
-12
5246.16
-11
5266.78
-10
5265.15
-9
5269.08
-8
5332.03
-7
5342.96
-6
5339.80
-5
5278.73
-4
5291.69
-3
5287.93
-2
5339.75
-1
5444.83
1
5167.18
2
5133.48
3
5015.50
4
5180.14
5
5419.93
6
5338.77
7
5341.82
8
5335.23
9
5207.16
10
5124.45
11
5206.15
12
5111.74
13
5098.48
14
5063.44
15
4942.30
Average return
Cumulative
Abnormal return
0.36777
-0.5633
0.32484
0.46326
0.39307
-0.0308
0.07447
1.19475
0.20511
-0.0592
-1.1437
0.2456
-0.0712
0.98007
1.96784
-5.0994
-0.6522
-2.2983
3.28261
4.6291
-1.4974
0.05712
-0.1234
-2.4004
-1.5885
1.59443
-1.8134
-0.2594
-0.6873
-2.3925
-0.1633
0.531113248
-0.399952826
0.48818222
0.626607461
0.556408142
0.132542642
0.237816966
1.358096393
0.368450019
0.104130726
-0.980356613
0.408939954
0.09216333
1.143411466
2.131186888
-4.936017445
-0.488827413
-2.134936102
3.445947787
4.792444112
-1.334084263
0.22046134
0.03992139
-2.237072917
-1.425121921
1.757773151
-1.650062169
-0.096075893
-0.523915928
-2.229173747
34
0.531113248
0.131160422
0.619342642
1.245950103
1.802358245
1.934900887
2.172717853
3.530814246
3.899264265
4.003394991
3.023038378
3.431978333
3.524141663
4.667553129
6.798740017
1.862722572
1.373895159
-0.761040943
2.684906844
7.477350956
6.143266694
6.363728033
6.403649424
4.166576507
2.741454586
4.499227737
2.849165568
2.753089675
2.229173747
0.000000000
10
6
8
4
6
4
2
0
-20
-10
-2
0
10
20
Return
0
Cumulative Abnormal
Return
Abnormal Return
-2
-4
-4
-6
Figure 4.8:
2
-6
2007 General elections return, abnormal returns and Cumulative
returns
For the 2007 general elections, the cumulative abnormal return remained positive during
the pre – event phase and dipped to the negative on the post event and reverted
immediately to the positive and declined thereafter. The normal and abnormal returns
moved in uniformity throughout the event period.
4.6
Stock Market Performance and 2013 general election
The study analysed the stock market performance during the 2013 general election.
NSE 20 Share Index
5,200
5,000
4,800
4,600
4,400
4,200
4,000
3,800
M9
M10
M11
M12
M1
M2
2012
M3
M4
M5
M6
M7
M8
M9
2013
Figure 4.9: NSE 20 share index performance 2013 general elections
35
Figure 4.6 illustrates that the NSE-20 share performance was on an upward trend until after
the 2013 general election. There was however a decline in the month after the election and
swings in performance in the months thereafter. There was however not a substantial decline
indicating that the elections did not affect investor confidence irrespective of the regime
change in governamce in Kenya resulting from this election. This was also the first election
after enanctment of the new Kenyan constitution.
4.6.1
Abnormal Returns (AR) and Cumulative Abnormal Returns (CAR) for 2013
general elections
Table 4.4: Abnormal returns and Cumulative abnormal returns
Days
Share
Return
Abnormal return
Index
-15
-14
-13
-12
-11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
1
2
3
4
5
6
7
8
9
10
11
12
4611.03
4633.48
4648.09
4637.54
4614.75
4573.88
4551.06
4502.75
4505.59
4477.89
4463.65
4469.19
4513.55
4518.59
4510.47
4533.82
4546.83
4585.07
4658.64
4796.33
4985.91
4911.45
4831.85
4774.12
4727.04
4721.23
4719.05
Cumulative
Abnormal return
0.49276
0.48688
0.31531
-0.227
-0.4914
-0.8856
-0.4989
-1.0615
0.06307
-0.6148
-0.318
0.12411
0.99257
0.11166
-0.1797
0.51768
0.28695
0.84103
1.60456
2.95558
3.95261
-1.4934
-1.6207
-1.1948
-0.9862
-0.1229
-0.0462
0.382910298
0.377024118
0.205461844
-0.336826867
-0.601276249
-0.995490358
-0.60877187
-1.171362861
-0.04677935
-0.724643764
-0.427858835
0.014261757
0.882721682
0.001811852
-0.289553992
0.407832494
0.177102572
0.731173589
1.494703739
2.845731687
3.842753513
-1.603260341
-1.73055456
-1.304632383
-1.096002244
-0.232761813
-0.156026324
36
0.382910298
0.759934416
0.96539626
0.628569392
0.027293143
-0.968197215
-1.576969086
-2.748331947
-2.795111296
-3.51975506
-3.947613895
-3.933352137
-3.050630455
-3.048818604
-3.338372595
-2.930540102
-2.753437529
-2.02226394
-0.527560201
2.318171487
6.160925
4.557664659
2.827110099
1.522477715
0.426475472
0.193713658
0.037687334
13
14
15
4708.56
4713.6
4732.79
-0.2223
0.10704
0.40712
Average Return
-0.33214242
-0.294455086
-0.002812822
-0.297267907
0.297267907 0.00000000000000089
0.10985
8
5
6
4
3
4
Return
2
2
1
Cumulative Abnormal
Return
0
Abnormal Return
0
-20
-10
0
10
20
-2
-1
-4
-2
-6
-3
Figure 4.10: 2013 General elections return, abnormal returns and Cumulative
returns
For the 2013 general election, the normal and abnormal returns move in uniform
throughout the event window. The cumulative abnormal returns gradually moved to the
negative before the event (general election) and subsequently to the positive after the
event and subsequently back to the negative.
4.7
Tests of Significance
Parametric t-test was used to establish the statistical significance of the abnormal returns
(AR) and the cumulative abnormal returns (CAR) over the event window period.
4.7.1
T – test for Abnormal Returns
This study tests the following hypothesis:
Null Hypothesis: General election has no effect on the Nairobi Securities Exchange
Alternate Hypothesis: General election has an effect on the Nairobi Securities Exchange.
37
Table 4.5: Descriptive Statistics for Abnormal Returns
One-Sample Statistics
N
Mean
Std. Deviation
Std. Error Mean
AR 1997
30
.0000000
.51479428
.09398815
AR 2002
30
.0000000
1.51935929
.27739579
AR 2007
30
.0000000
1.80390395
.32934629
AR 2013
30
.0000000
1.16988689
.21359115
The descriptive statistics for the variables have been provided as the number of
observations (N), the mean and the standard deviation for the 1997, 2002, 2007 and 2013
general elections abnormal returns (AR). The standard error is the estimated deviation of
the mean of the sample used for the statistical test. For the 1997 general election
abnormal returns (AR), the standard error of the sample mean is merely 0.093 which is
relatively small. Therefore, there is a high likelihood that the sample mean is close to the
population mean. The standard error of the sample mean for the 2002 general election
abnormal returns (AR) is 0.277 which is relatively small meaning that it too adequately
represents the population mean. Similarly, the standard errors for 2007 and 2013 general
elections abnormal returns are 0.329 and 0.214 respectively which are relatively small
meaning that they too adequately represents the population mean.
Table 4.6: T – test on Abnormal Returns
One-Sample Test
Test Value = 0
95% Confidence Interval of the
Difference
t
df
Sig. (2-tailed)
Mean Difference
Lower
Upper
AR 1997
.000
29
1.000
.00000000
-.1922273
.1922273
AR 2002
.000
29
1.000
.00000000
-.5673381
.5673381
AR 2007
.000
29
1.000
.00000000
-.6735888
.6735888
AR 2013
.000
29
1.000
.00000000
-.4368429
.4368429
38
This output gives the t-test value, the degrees of freedom and the two-tailed significance.
Since the p values for 1997, 2002, 2007 and 2013 abnormal returns are all 1.000 which
are more than 0.05, the null hypothesis cannot be rejected. The t-statistical test at 5%
level of significance indicates that event - day abnormal returns (AR) were insignificant
for the general elections.
4.7.2
T – test for Cumulative Abnormal Returns
Table 4.7: Descriptive Statistics for Cumulative Abnormal Returns
One-Sample Statistics
N
Mean
Std. Deviation
Std. Error Mean
CAR 1997
30
-.5807411
1.43411591
.26183254
CAR 2002
30
1.1008060
4.53934033
.82876636
CAR 2007
30
3.0701212
2.11975709
.38701293
CAR 2013
30
-.5648116
2.49004039
.45461710
The descriptive statistics for the variables have been provided as the number of
observations (N), the mean and the standard deviation for the 1997, 2002, 2007 and 2013
general elections cumulative abnormal returns (CAR). For the 1997 general election
cumulative abnormal returns (CAR), the standard error of the sample mean is merely
0.261, for the 2007 general election cumulative abnormal returns (CAR), the standard
error of the sample mean is merely 0.387 which is relatively small, for the 2013 general
election cumulative abnormal returns (CAR), the standard error of the sample mean is
merely 0.455. For these years (1997, 2007 and 2013), there is a high likelihood that the
sample mean is close to the population mean. The standard error of the sample mean for
the 2002 general election cumulative abnormal returns (CAR) is 0.828 which indicates
that it is not adequately representative of the population mean.
39
Table 4.8: T – test for Cumulative Abnormal Returns
One-Sample Test
Test Value = 0
95% Confidence Interval of the
Difference
t
df
Sig. (2-tailed)
Mean Difference
Lower
Upper
CAR 1997
-2.218
29
.035
-.58074115
-1.1162488
-.0452335
CAR 2002
1.328
29
.194
1.10080601
-.5942115
2.7958235
CAR 2007
7.933
29
.000
3.07012117
2.2785909
3.8616515
CAR 2013
-1.242
29
.224
-.56481160
-1.4946080
.3649848
4.8
Summary and Interpretation of the Findings
4.8.1 Summary
The objective of this study was to investigate whether there is a relationship between the
general elections and the market performance for firms listed in the Nairobi Securities
Exchange. The t-statistic test shows that for all the four general elections (100%) namely
the 1997, 2002, 2007 and 2013, abnormal returns were statistically insignificant. The
Cumulative abnormal returns for the 1997 and 2007 general elections were found to be
statistically significant while the cumulative abnormal returns for the 2002 and 2013
general elections were established to be statistically insignificant at 5% level of
significance.
This finding may imply that Nairobi stock exchange market viewed the 2002 and 2013
general election events as inconsequential and hence rebounded and stabilized
immediately, hence the insignificance of cumulative abnormal returns (CAR) of the 2002
and 2013 general elections.
40
The findings suggest that the NSE 20 share index as well as the individual stock returns
for the 1997 and 2007 general elections deviated significantly from their means while
those for the 2002 and 2013 elections showed no significant deviation from their means.
4.8.2 Interpretation
The t test values for the 1997, 2002, 2007 and 2013 general elections cumulative
abnormal returns (CAR) are calculated as -2.218, 1.328, 7.933 and -1.242 respectively.
Since the p values for 1997 and 2007 cumulative abnormal returns are 0.035 and 0.000
respectively which are less than 0.05, the null hypothesis is rejected. However, for 2002
and 2013 cumulative abnormal returns (CAR), the p values of 0.194 and 0.224
respectively are greater than 0.05 and therefore, the null hypothesis cannot be rejected.
As per the t-statistical test for the cumulative abnormal returns (CAR), the 2002 and 2013
general elections were found to be insignificant while the 1997 and 2007 general
elections were found to be significant at 5% level of significance. This means that the
NSE 20 share index as well as the individual stock returns for the 1997 and 2007 general
elections deviated significantly from their means while those for the 2002 and 2013
elections showed no significant deviation from their means.
4.8.3 Previous Studies
Earlier empirical studies showed that the average cumulative abnormal returns exhibited a
reducing trend in the periods preceding announcement and a slower increase after
announcement pointing to market absorption of the information in the long run period
after the announcement (Irungu, 2012). Menge, et al. (2014) studying the effect of
elections on stock market returns at the Nairobi securities exchange adopting events study
methodology covering periods between 2002 and 2013 found that actual stock returns
were significantly higher before elections than after election periods. These studies are
consistent with the findings of this study.
41
CHAPTER FIVE
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1
Summary
The study finds that the NSE 20 share index has exhibited seasonality over the months
from the year 1997 to 2013. The returns are exhibiting seasonality and volatility over the
periods. For all the four events (general elections), in two events (50%) the normal and
the abnormal returns move in uniformity while in other two events (50%), the normal and
the abnormal returns have the same trend as they move in synchronicity. For three of the
events (75%), the pre-election days have negative cumulative abnormal returns which
turn to positive after the election. For one election, Year 2007 election, the cumulative
abnormal returns are positive before the election and turns negative briefly after the
election after which the returns swing to positive and declines in the remainder of the
period.
The t-statistic test shows that for all the four general elections (100%) namely the 1997,
2002, 2007 and 2013, abnormal returns were statistically insignificant. The Cumulative
abnormal returns for the 1997 and 2007 general elections were found to be statistically
significant while the cumulative abnormal returns for the 2002 and 2013 general elections
were established to be statistically insignificant at 5% level of significance. This finding
may imply that Nairobi stock exchange market viewed the 2002 and 2013 general
election events as inconsequential and hence rebounded and stabilized immediately,
hence the insignificance of cumulative abnormal returns (CAR) of the 2002 and 2013
general elections. The findings suggest that the NSE 20 share index as well as the
individual stock returns for the 1997 and 2007 general elections deviated significantly
from their means while those for the 2002 and 2013 elections showed no significant
deviation from their means.
42
5.2
Conclusions
From the findings, it is concluded that market reaction to elections is highly negative or
positive depending on the election at hand and hence the information made by general
election is useful for valuing the securities in the markets. For example, in the 2007
general elections, the abnoral return declined to -4.936 on the first day of trading after the
election. It can thus be observed that election affects the performance of the stock market
and hence shareholders and other stakeholders should not overlook electioneering events.
Volatile elections negatively affects transactions processing in the market place and
impedes the buying and selling of securities by instilling fear on investors as well as
destroying infrastructural facilities. This is depicted from the sharp decline of the
abnormal returns in the post event period after the 2007 elections noted in the study.
The information made by election announcements is useful for valuing the stocks although
the market does not price the information contained in some elections such as the one in 2002
and 2013. The cumulative abnormal returns exhibited a reducing trend in the periods
preceding announcement and a sharp increase after announcement pointing to market
absorption of the information in the long run period after the announcement. The two election
periods indicate that the elections did not affect the investor confidence.
The study observes that the market return is a good predictor of a stock return. It was
observed that the both the abnormal returns and the return of the market moved in
tándem.The market reacted with the announcements of the election results.The reaction was
however positive or negative.
5.3
Recommendations
Due to reforms in the election process in Kenya, the 2013 general election was credited
as peaceful and as such the abnormal returns one trading day after the election rose from 0.290 to 0.408 which is a pointer to improved investor confidence that may be explained
by constitutional provisions for adressing election disputes. The government should
43
therefore ensure that all the election provisions in the new constitution are implemented
and adhered to.
The government through the Capital Markets Authority should enact policies aimed at
cushioning the market from political interferences. The policies should be aimed at
encouraging more local investors into the securities Exchange.
The investors should carefully analyse whether to hold or sell stocks prior or after the
events of the general elections. A compromise position of the portifolio to be held during
the period need to be carefully considered inorder to save the investors from losses
culminating from herd behaviour in the securities market during the election periods.
The government should sensitize the citizens through civic education the need to embrace
democracy and hence peaceful elections. This is because undemocratic elections may
lead to post elections violence hence uncertainities and adverse effect on the stock prices.
Firms planning to raise capital from the securities Exchange should similarly carefully
analyse the market to ensure that the timing is right. Otherwise it may coincide with a
bearish market trend at the NSE.
5.4
Limitations of the Study
The market performance during the elections may have been affected by other market
anomalies such as the weekend effect, Monday effect, holiday effect. Three of the event
periods that were analysed took place during the festive december holidays.
Factors such as cash flows, growth opportunities, liquidity and dividend payouts were not
considered when estimating the returns. They however affect market returns of firms.
These factors were not isolated during the research and hence could have moderated the
results of this study.
44
Investor behavioral biases may also have come into effect during the study period. These
include issues of capital flights by investors unsure of the policies to be implemented by
the new office holders. Some of the investors may use the wai and see approach during
the period. These behavioral biases however were not considered during the study and
may also have a moderating effect on the results of these findings.
Macroeconomic performance such as inflation, shilling depreciation and global financial
crisis might have also moderated the effect of these events (general election).
Unfortunately, these moderating factors could not be isolated in the study owing to
difficulty in doing so.
5.5
Suggestions for Further Research
In addition to event study methodology, it is suggested that other approaches be adopted
such as the filtered GARCH-EVT approach and the non-parametric methodology for use
in the study of the effect of general election on the stock market performance. GARCHEVT approach enables one to study the event-day effect only, though it is
computationally intensive.
The constitution allows and stipulates that for certain clauses to be amended that a
referendum must be conducted in Kenya. This study recommends that a similar study
could be done on the information content of the constitutional referendum. Probably
further the researcher could analyze whether the effect has similar characteristics as the
national elections.
Further studies could be done to analyze the performance of stock returns in non election
periods to compare their performance with the periods prior to elections as it is in this
study. Researchers should study the effect of terrorism events that are normally followed
by travel advisories that tend to reduce inflow of foreign exchange from sectors such as
tourism.
45
Discovery of oil deposits within the country has been presumed to have a positive effect
on the future economic propects. This study recommends that research could be done on
the information content of discovery pronouncements of oilwells in the country.
It could be interesting to conduct similar studies on other neighbouring countries to see if
their presidential and parliamentary elections in general cause negative abnormal returns,
or if one can find a different relationship in other parts of the world.
46
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APPENDICES
APPENDIX 1: LISTED FIRMS AT NAIROBI SECURITIES EXCHANGE
AGRICULTURAL
Eaagads Ltd
Kapchorua Tea Co. Ltd
Kakuzi Ltd
Limuru Tea Co. Ltd
Rea Vipingo Plantations Ltd
Sasini Ltd
Williamson Tea Kenya Ltd
COMMERCIAL AND SERVICES
Express Ltd
Kenya Airways Ltd
Nation Media Group
Standard Group Ltd
TPS Eastern Africa (Serena) Ltd
Scangroup Ltd
Uchumi Supermarket Ltd
Hutchings Biemer Ltd
Longhorn Kenya Ltd
TELECOMMUNICATION AND TECHNOLOGY
Safaricom Ltd
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AUTOMOBILES AND ACCESSORIES
Car and General (K) Ltd
CMC Holdings Ltd
Sameer Africa Ltd
Marshalls (E.A.) Ltd
BANKING
Barclays Bank Ltd
CFC Stanbic Holdings Ltd
I&M Holdings Ltd
Diamond Trust Bank Kenya Ltd
Housing Finance Co Ltd
Kenya Commercial Bank Ltd
National Bank of Kenya Ltd
NIC Bank Ltd
Standard Chartered Bank Ltd
Equity Bank Ltd
The Co-operative Bank of Kenya Ltd
INSURANCE
Jubilee Holdings Ltd
Pan Africa Insurance Holdings Ltd
Kenya Re-Insurance Corporation Ltd
Liberty Kenya Holdings Ltd
British-American Investments Company ( Kenya) Ltd
CIC Insurance Group Ltd
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INVESTMENT
Olympia Capital Holdings ltd
Centum Investment Co Ltd
Trans-Century Ltd
MANUFACTURING AND ALLIED
B.O.C Kenya Ltd
British American Tobacco Kenya Ltd
Carbacid Investments Ltd
East African Breweries Ltd
Mumias Sugar Co. Ltd
Unga Group Ltd
Eveready East Africa Ltd
Kenya Orchards Ltd
A. Baumann CO Ltd
CONSTRUCTION AND ALLIED
Athi River Mining Ltd
Bamburi Cement Ltd
Crown Berger Ltd
E.A.Cables Ltd
E.A.Portland Cement Ltd
ENERGY AND PETROLEUM
KenolKobil Ltd
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Total Kenya Ltd
KenGen Ltd
Kenya Power & Lighting Co Ltd
Umeme Ltd
GROWTH ENTERPRISE MARKET SEGMENT
Home Afrika Ltd
54