Corporate governance and transparency evidence from stock return synchronicity

Description
The purpose of the study is to examine the influence of corporate governance on the flow of
firm-specific information in an emerging market.

Journal of Financial Economic Policy
Corporate governance and transparency: evidence from stock return synchronicity
Matthew Ntow-Gyamfi Godfred Alufar Bokpin Albert Gemegah
Article information:
To cite this document:
Matthew Ntow-Gyamfi Godfred Alufar Bokpin Albert Gemegah , (2015),"Corporate governance and
transparency: evidence from stock return synchronicity", J ournal of Financial Economic Policy, Vol. 7
Iss 2 pp. 157 - 179
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Corporate governance and
transparency: evidence from
stock return synchronicity
Matthew Ntow-Gyamf, Godfred Alufar Bokpin and
Albert Gemegah
Department of Finance, University of Ghana Business School,
Accra, Ghana
Abstract
Purpose – The purpose of the study is to examine the infuence of corporate governance on the fowof
frm-specifc information in an emerging market.
Design/methodology/approach – Synchronicity is estimated under assumptions of contemporaneous
and non-contemporaneous relationship between individual stock returns and the market return. Possible
thin-trading effect is also corrected using the Dimson’s Beta approach to estimate synchronicity. In the main
empirical model, both the Panel-Corrected Standard Errors and the Generalized Least Square estimations
were used to provided robust evidence of governance infuencing transparency.
Findings – Corporate governance was found to broadly infuence the release of frm-specifc
information in a relatively opaque market through the information environment. However, no evidence
in support of the “auditor-reputation effects” theory was found. As well, CEOduality does not create an
individual powerful enough to reduce the monitoring role of boards. We further document the presence
of noise trading on the Ghana Stock Exchange.
Practical implications – This study suggests that specifc corporate mechanism practices have
implications for stockselectioninarelativelyhighinformationasymmetryCapital Market. Investors require
transparency; hence, frms with governance mechanisms that elicit such transparency are likely to attract
investors.
Originality/value – This study is the frst to examine the relationship between governance and
transparency while using stock return synchronicity as a proxy for transparency in an emerging
Ghanaian Capital Market.
Keywords Corporate fnance and governance, Accounting and auditing
Paper type Research paper
1. Introduction
The purposes of many of the corporate governance reforms that are made by
stakeholders are ones geared toward reducing the event that some parties will have
more information about a frm than others do (informational asymmetry). In the
reduction of information asymmetry, transparency is ensured. This position has not
been controversial in literature, in that, the ability of corporate transparency and
corporate governance to elicit good effects is undisputable (Kyereboah-Coleman et al.,
2006). For Beeks and Brown (2005), frms with high corporate governance quality make
more informative disclosures; adding that, frms with an institutionalized corporate
JEL classifcation – M4
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1757-6385.htm
Corporate
governance
and
transparency
157
Received10 October 2013
Revised23 January2014
15 July2014
26 September 2014
Accepted5 November 2014
Journal of Financial Economic
Policy
Vol. 7 No. 2, 2015
pp. 157-179
©Emerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-10-2013-0055
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governance structure would be more transparent than frms that have weaker corporate
governance frameworks. In recent literature, stock return synchronicity has been found
to provide an understanding of the extent of corporate disclosures made by frms. This
has caused an increase in debate around the concepts of corporate information
disclosure, governance and synchronicity.
Explaining stock return synchronicity, Morck et al. (2000), who were among the
frst people to research into the area, documented that it is the extent to which the
return of the stock of a particular frm co-moves with the market return. Years after
Morck et al. (2000), the understanding of stock return synchronicity has not varied.
According to Du et al. (2007), synchronicity of stock price movement refers to the
extent to which individual stock prices move up and down en masse. Khandaker
(2011) also explains that stock price synchronicity is the tendency of a stock market
to move in the same direction in a particular period of time, such as a given day or
week. By these explanations, a market is more synchronous if generally the prices of
individual stocks vary together. Sometimes, the concept of asset beta and its
synchronicity becomes diffcult to separate. This is partly due to the fact that both
concepts have to do with proportional relationships between an asset return and the
market return. However, there is a fundamental difference between these two
concepts. Synchronicity is explained to mean the extent to which the market return
explains the return of an asset while asset beta which happens to be the systematic
risk of an asset is typically conceived as a measure of the contribution of the asset to
the risk of a diversifed portfolio. The market portfolio being the most diversifed
portfolio, an asset beta is the contribution of the asset to the risk of the market
portfolio. It is the asset’s contribution to the market variance. In a much simpler way
for understanding, beta is the contribution of the asset in the life of the market, while
synchronicity is the contribution of the market in the life of the asset. In contrast,
both concepts explain howexplain the proportionality that exist between the market
return and an asset’s return.
Bushman et al. (2004), in explaining corporate transparency, documented that, it is the
availability of frm-specifc information to those outside publicly traded frms or the
dissemination of information to market participants. Jin and Myers (2006) put up a strong
argument that stock return synchronicity could be interpreted as a measure of corporate
transparency because it represents how much market indices explain individual frm
returns. In separate studies, Jin and Myers (2006) and Bushman et al. (2004) have all
established that stock return synchronicity which they determine using the R
2
from the
market model could be used as a measure of transparency.
Albeit the introduction of this newcorporate transparency measure, extant literature
that look at corporate governance and transparency used constructed governance and
transparency measures within an international context (Bokpin and Isshaq, 2009;
Tsamenyi et al., 2007; Aksu and Kosedag, 2006). Many of these studies have used the
total disclosure score (TDS) approach in measuring transparency. However, the
construction of TDS includes some corporate governance measures, making it diffcult
to disentangle the separate effect of transparency fromcorporate governance (Aksu and
Kosedag, 2006).
Some studies have sought to solve the problem by modifying the index to
preclude those items that measure corporate governance in the construct (Bokpin
and Isshaq, 2009). However, it still does not change the fact that disentangling the
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separate effects of corporate governance from transparency in the TDS is a diffcult
one, as the modifcation that is done depends on the researcher in point. The TDS
rates companies on their ability to disclose information consistent with some
fnancial statement disclosure practices but does not explicitly consider the quality
of information within those disclosures, a situation that leads to construct validity
problem. Second, the measure requires that frms make certain information
available, but the degree to which such information is available is not investigated
by the construct. Hence, TDS considers availability but fails to investigate quantity
of such information. Also, traditionally, the TDS measure was constructed along the
International Accounting Standards (IAS) and US Generally Accepted Accounting
Principles (GAAP) as implicit benchmarks (Patel et al., 2002). However, in recent
times, companies have adopted the International Financial Reporting Standards
(IFRS). Therefore, using benchmarks other than the IFRS poses methodological
challenges to the TDS construct. According to Granados et al. (2006), it is inaccurate
to measure an item against a standard if the item itself refrains from following the
standard. As a way of solving this problem, studies have modifed the list of
questions to preclude the non-applicable cases and also include applicable questions
that originally were not in the S&P’s list of questions for the TDS measure. Again,
this approach to solving the problem takes away standardization of the TDS
measure.
We deviate from the use of variables constructed in the international context to one
that can be verifed through calculations with available data. This approach is
supported by the positions held in literature by researchers such as Jin and Myers (2006).
They argue that stock return synchronicity can be interpreted as a measure of corporate
transparency because it represents how much market indices explain individual frm
returns. The originality of this study lies in our use of stock return synchronicity as a
proxy for corporate transparency for the frst time in Ghana and Sub-Saharan Africa.
Our use of synchronicity as a measure of transparency has the advantage of being
objectively observable and reproducible (Li et al., 2003). Unlike the other
researcher-constructed concepts for measuring transparency, synchronicity allows
different researchers at difference places and points in time given same data to arrive at
a common conclusion. This makes the result of scientifc research much trusted, as it
lessens the biases of the researcher.
Furthermore, the justifcation for the choice of Ghana as the country of interest for the
study stems from the fact that Ghana has no strong legal framework for the
development of its stock market. Additionally, there are no stringent information
disclosure laws in Ghana that will compel frms to disclose true and fair information
(relative to other developed countries). In the absence of an effective framework for
compliance, effective corporate governance at frmlevel is expected to play a crucial role
in improving disclosure of corporate information and, hence, transparency. It is our
belief that corporate governance mechanisms used by owners who set managerial
constraints and their incentives can infuence synchronicity (transparency) through the
information environment.
The rest of the study is arranged as follows: Section 2 deals with a brief discussion of
extant literature; Section 3 discusses the methodological approach for the study, while
Section 4 addresses the results and discussion of fndings. Finally, Section 5 discusses
the conclusions of the study.
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2. Literature review
The seminal study that provides the theoretical basis for corporate governance was
done by Berle and Means (1932) in their work “The Modern Corporation and Private
Property”. Their work was used to identify the agency problemin corporate governance
that results fromthe fact that managers and owners of corporations are separated. After
the thesis by Berle and Means (1932), there have been several theories that have also
evolved around the concept of corporate governance. These theories include but not
limited to the agency cost theory, stewardship theory, the resources dependence theory
and the stakeholder theory.
2.1 Agency theory
According to Jensen and Meckling (1976), the agency relationship is legal arrangement
whereby “one or more persons (principal) engage another person (agent) to perform
some service on their behalf, which involves delegating some decision-making authority
to the agent”. The delegation of decision-making authority gives rise to the possibility of
agents not acting in the best interest of the principal – thereby seeking their own
parochial interest. The tension could result in the fact that managers instead of investing
in projects that will add value to shareholder’s investment, will rather perk out frm
resources for personal use. This tendency gives rise to agency cost to the principal. With
this, shareholders are required to use effective ways of aligning managers’ interest to
their (shareholders’) interest. Agency cost refers to the expenditure incurred on the
mechanisms to align management and shareholder interest while reducing the
maximizations of managers’ parochial interest. One way shareholders do this is to link
management compensation to frm performance. But even so, there have been studies
that suggest that linking managers’ compensation to performance provides incentive
for earnings management (Thiruvadi and Huang, 2011). Other agency costs include
expenses on auditing, budgeting, control and compensation systems, bonding and other
losses traceable to the separation of ownership and control of frms.
2.2 Stakeholder theory
The stakeholder theory of corporate governance was proposed by Freeman (1984) when
he defned the theory as “any group or individual who can affect or is affected by the
achievement of the organization’s objectives”. This theory is said to have been emanated
from the combination of a number of sociological and other organizational disciplines
(Wheeler et al., 2003). According to this theory, because of globalization of markets and
the use of technology, businesses are nowinfuenced by a number of stakeholders other
than their shareholders, and these stakeholders are to be considered in deciding on
critical success factors of the frm. This theory of corporate governance argues about the
fact that attention should be given to all other stakeholder groups in addition to the
investors in the frm (Freeman, 1984; Gibson, 2000). Some of these interest groups are
customers, suppliers, employees and even the local community. It is therefore important
that, as far as possible, these groups are represented on the board to ensure effective
corporate governance. In this regard, corporate boards are to be as divergent as possible
such that representatives of all parties are involved in the decision making process that
have the tendency to impact on the organizational success.
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2.3 Stewardship theory
Unlike the agency theory whose root is found in economics, the stewardship theory has
its root frompsychology and sociology. In psychology and sociology, there are theories
that are concerned with the behaviors of man. In some of these theories, leaders and
managers, for that matter, are motivated by the need to achieve. The achievement of
success in especially challenging situations provides a feeling of intrinsic satisfaction
and gain recognition from peers and bosses (McClelland, 1961; Herzberg et al., 1959).
Sometimes the individuals are melded with corporations and that managers’ self-esteem
is equated to his corporation’s prestige (Donaldson and Davis, 1991). When this
relationship occurs, in situations where managers regard an action as not personally
rewarding, they may still carry it out from the sense of duty: normatively induced
compliance (Etzioni, 1975). According to Silverman (1970), what motivates individual
calculative action by managers is their personal perception, an assumption that deviates
fromwhat the agency theorists posits (Jensen and Meckling, 1976). In the words of Davis
et al. (1997), the stewardship theory is explained as follows: “a steward protects and
maximises shareholders wealth through frm performance, because by so doing, the
steward’s utility functions are maximised”. Under this theory, the assumption is that
both the steward and the principal benefts froma well-built and strong organization. In
this relationship, stewards are company executives and managers whose aims are to
work for the shareholder, protect their interest and make returns on their (shareholders)
investment for them.
2.4 Resource dependency theory
Resource dependence theory suggests that organizations’ survival and success are
contingent on their ability to control the fow of resources (Pfeffer and Salancik, 1978).
The resource dependency theory is attributed to Pfeffer (1973) and Pfeffer and Salancik
(1978) as the proponents of the theory. The theory emphasizes that non-executive
directors enhance the ability of a frmto protect itself against the external environment,
reduce uncertainty or co-opt resources that increase the frm’s ability to raise funds or
increase its status and recognition (Abor and Biekpe, 2007). The survival and growth of
a frmis, to a large extent, dependent on the amount of resources available to it. For this
matter, rigorous efforts are made to ensure the availability of resources necessary for the
survival and development of the frm. According to Abor and Biekpe (2007), the board is
hence seen as one of a number of instruments that may facilitate access to resources
critical to company success.
Compared to other theories and concepts like capital structure, dividend policy and
corporate governance, stock return synchronicity is new in fnance literature. Seminal
studies into the area started with Morck et al. (2000). By the defnitions provided (Morck
et al., 2000; Du et al., 2007; Khandaker, 2011), stock return synchronicity could be seen
from two main focal points: market-wide synchronicity and then frm-level
synchronicity. Market-wide synchronicity can be described as the extent to which
stocks on a particular market moves together (either up or down) within a given time.
Firm-level synchronicity can be described as the extent to which a particular stocks
price moves together with the market return within a given time. This study
concentrates on frm level synchronicity. It is also important to note that studies have
averaged frm-level synchronicity to ascertain market wide synchronicity. The concept
of stock return synchronicity assumes that stock prices and returns are explained
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mainly by two sets of information. The frst is information that is related to the specifc
frmwhose stock price or return is in question and second by market-wide information.
If a stock’s return is explained more by the market information, then that stock’s return
exhibits more synchronicity. In contrast, if the stock return is explained more by the
frm-specifc information, then that stock exhibits idiosyncratic dependency.
Widely in literature, this has been used as price informativeness and an inverse
measure of transparency. In a study by Mbarek and Hmaied (2012), opaque banks are
interpreted as banks with higher stock return synchronicity. Shaiban and Saleh (2010)
document that their fndings show signifcant support for the current debate regarding
stock price synchronicity as a measure of share price informativeness. Gul et al. (2010)
also showthat the amount of earnings information refected in stock returns is lower for
frms with high synchronicity. The understanding is that stock prices refect two main
types of information: frst market-wide information and second frm-specifc
information. When the market model is estimated, the R
2
of the estimation is interpreted
as the extent to which the market return explains the individual stock return. This
means that the difference between one and the R
2
(1- R
2
) is the extent to which
frm-specifc information is refected in the stock price, a measure of opaqueness of the
frm.
In literature, some studies have discussed howthe relationship between information
disclosure and R
2
could be ambiguous given the market-level effciency. According to
studies such as Dasgupta et al. (2006), a higher R
2
may be associated with increased
transparency in an effcient market. Their argument is that in an effcient market, if the
disclosure is suffciently lumpy, in the sense that the market receives a big chunk of
information which otherwise might have been disclosed later or not at all, the R
2
will
increase subsequently. Their debate is much elucidated in their words as follows:
In effcient markets, stock prices should be informative about future events: consequently,
more informative stock prices should be associated with less “surprise”, and hence less
idiosyncratic return variation and higher R
2
.
This argument contradicts the frameworks of studies such as Jin and Myers (2006),
Piotroski and Roulstone (2003), Chan and Hameed (2006), Morck et al. (2000) who
proposed that if the frm’s environment causes stock prices to aggregate more
frm-specifc information, market factors should explain a smaller proportion of the
variation in stock returns. In other words, the R
2
from a standard market model
regression should be lower.
Dasgupta et al. (2006) in that their argument draw a dynamic relationship between
information environment effciency and a frms’ future R
2
, this view, however, is outside
of the scope of this study. This study rather looks at the relationship between the two on
level but not in a dynamic panel manner. That notwithstanding, in separate studies,
Campbell et al. (2001) and Morck et al. (2000) found that over the decades, synchronicity
on the US market has been decreasing steadily. If frm-specifc variation were to be as a
result of ineffciency, then the US market has become steadily ineffcient over the
decades of the twentieth century, and that the markets of developed economies are less
effcient than emerging markets (Li et al., 2003). This study therefore follows the work of
Li et al. (2003) in applying lex parsimoniae (Ockham’s razor) which, at the current time,
is in line with the conceptual arguments that increased frm-specifc variation signifes
increased transparency.
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In extant literature, there have been some governance mechanisms that have been
established to have potential relationships with transparency and information
disclosure. These mechanisms are reviewed below.
2.5 CEO duality
Studies have acknowledged that concentrated decision-making power as a result of CEO
duality may constrain board independence and impair the board’s oversight and
governance roles including corporate disclosure/transparency policies. These studies
have often cited the agency theory as the basis for their conclusions (Gul and Leung,
2004; Fama and Jensen, 1983). CEO duality creates a situation where there exists a
strong individual power that has the potential of eroding the ability of the larger board
to exercise their monitoring and effective controlling duties (Gul and Leung, 2004). A
less persuasive perspective based on stewardship theory suggests that CEO duality
helps CEOs provide strong unambiguous leadership and better position themselves to
make decisions that are in the interest of the frm (Gul and Leung, 2004).
2.6 Board composition/independence
Board composition and independence have been used interchangeably. Studies that use
board composition refer to it as the proportion of independent, outside directors of
the board. As the number/proportion of independent, outside directors increases, board
independence increases as well (Cheng and Courtenay, 2006). These independent
directors are to ensure that the likely effects predicted by the agency theory of corporate
governance do not emanate. It is important to note that checks on management are
necessitated by shareholders and outsiders’ desire for transparency. However,
empirically, there have been mixed results on whether board composition affects
management’s disclosure tendencies.
2.7 Board size
If board checks on management breaks the tendencies of opaqueness of management
activities, what should be the appropriate board size? If corporate boards ensure
transparency, does an increased board size necessarily increase transparency?
According to Jensen (1993), a larger board size can lead to less candid discussion of
critical issues which could also lead to poor monitoring. The study concluded that the
optimal board size that companies should keep should be eight. Conversely, Adams and
Mehran (2003) contend that a bigger board can effectively monitor the actions of
management and provides better expertise.
2.8 Audit quality/Big4Auditors
The theoretical underpinnings of the demand for the services of external auditors stems
from the agency theory (Chaney et al., 2004). A careful review of literature reveals two
main tenets of audit quality (Lin and Liu, 2009). First is the ability to detect
misstatements and, second, the willingness to report the misstatements uncovered in an
audit engagement. According to Beasley et al. (2005), most studies classify the largest
international accounting frms, the Big4 frms, as high-quality auditors. These frms are
PricewaterhouseCoopers, Ernst & Young, Deloitte and Touche and KPMG. Previous
studies argue that the Big4 audit frms have the ability to provide quality audit better
than the non-Big4 audit frms theoretically due to the fact that large audit frms with
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greater investment in reputational capital have more incentives to minimizes audit
errors through “auditor-reputation effects” (DeAngelo, 1981).
2.9 Institutional ownership
Institutional investors also have fduciary duties to perform for their ultimate owners,
thereby the need to protect every investment made with owners’ funds. The close
monitoring role played by institutional owners/investors results in the reduction of
information asymmetry and the enhancement of transparency. In this study, we expect
institutional ownership to positively infuence transparency. However, we are mindful
of the fact that pockets of studies do not fnd signifcant evidence to support the
increased transparency/disclosure that results from institutional ownership (Haniffa
and Cooke, 2002).
3. Methodology
The measurement of stock return synchronicity was pioneered by Morck et al. (2000).
Their study proposed two main ways of measuring stock return synchronicity. These
were the classical measure and the R
2
measure. Later, Skaife et al. (2006) introduced the
zero return day measure. For the purpose of this study, the R
2
measure is used in
determining synchronicity which is our proxy for corporate transparency. This stems
from the fact that the classical synchronicity measure only aids in calculating the
country or market-level synchronicity and not that of frm level. Also, according to
Khandaker (2011), the zero-return measure requires each frm’s long-term stock return
data to capture the market co-movement. Also, the model uses trading days’
information, while this study only uses daily returns. Our choice of the R
2
measure also
stems from the fact that it has been established to be the most widely used measure of
synchronicity in fnance literature. In Morck et al. (2000), both the R
2
and the Classical
measures were used. Skaife et al. (2006) used the R
2
measure and the zero-return
measure. Several other studies have also used just the R
2
as a measure of synchronicity
(Li et al., 2003; Chan and Hameed, 2006). In our use of the R
2
measure, we estimate the
market model making two different assumptions. First, the ability of the market return
to determine a stock’s return is contemporaneous and so we specify the market model as
follows:
R
i,t
? ?
i
? ?
i
R
m,t
? ?
i,t
(1)
Where R
i,t
is the frm i return for period t, R
m,t
is the market return at t period,E
i,t
is the
error term and ?
i
and ?
i
are estimated parameters. The study estimated the market
model using the daily data for each year for each frm. This was done to arrive at an R
2
fgure for each frmfor each year (a proxy for transparency for each frmfor each year).
Second, we follow the work by Gul et al. (2010) and assume a non-contemporaneous
effect of the market return on the individual return and estimate the market model as
follows:
R
i,t
? ?
i
? ?
1
R
m,t
? ?
2
R
m,t?1
? ?
i,t
(2)
The study used both market models to arrive at two sets of R
2
; R Square and *R
Square, respectively. This helped in comparing fndings in an effcient market where
the transfer of information is contemporaneous and an ineffcient one where the transfer
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is non-contemporaneous. It is worth noting that conclusions based on the two
approaches in literature have not been signifcantly different. After the R squares are
obtained to correct for the bounded nature of the R-square within [0, 1], we used a logistic
transformation of R
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as used by Gul et al. (2010) as follows:
SYNCH
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?
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2 ?
(3)
Where R
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is the coeffcient of determination fromthe estimation of equations (1) and (2)
for frm i in year t. When a frm’s SYNCH
i,t
is high, it means that such a frm is
synchronous with the market; hence, less transparency in such frm. The study
measures SYNCH
i,t
based on daily returns of frmi. We then hypothesize that corporate
governance will infuence the level of corporate transparency and information
effciency. Consequently, we specify the following model for estimation:
SYNCH
i,t
? ? CopGov
i,t
? ? FirmControls
i,t
? ?
i
? ?
t
? ?
i,t
(4)
where i indexes frms and t indexes years. The dependent variable SYNCH
i,t
is estimated
from the market model to measure corporate transparency. ? is a vector of parameters
to be estimated on explanatory variables. CopGov
i,t
is a vector of observations on the
corporate governance variables. ? is a vector of parameters to be estimated on control
variables. FirmControls
i,t
is a vector of frmcontrol variables that have been established
in literature to infuence transparency (synchronicity). ?
i
are frm fxed effects which
control for time-invariant unobserved frm characteristics. ?
t
are year-fxed effects
which control for macroeconomic changes. ?
i,t
is the randomerror termof the equation.
3.1 Data and variables
We use a total of fve corporate governance measures in investigating the determinant
role corporate governance mechanisms have on transparency. These variables are
Board Size (BS), Audit Quality (BIG4AUD), CEO Duality (CEO), Board Composition
(BC) and Institutional Ownership (INSH). Consistent with extant literature, we control
for earnings volatility (STDROA), market-to-book ratio (MB) and Standard deviation of
Stock return (STDDEV). The study uses a 10-year panel data spanning from 2000 to
2009 for 31 frms in the estimation. All frms on the Ghana Stock Exchange (GSE) are
sampled based on the availability of data. Data on the stock return synchronicity are
obtained using the daily return from the GSE. Corporate governance data and all other
control variables are obtained from the annual fact books produced by the GSE.
3.2 Justifcation for variables
Corporate Governance has been found by several studies to infuence the level of
transparency of a frm. According to Jin and Myers (2006), managers have the tendency
to conceal bad news in attempts to protect their jobs. It is the duty of owners to put in
place effective governance mechanisms that have the ability to break through the
opaqueness of management and expose their (managers’) secrets. In this regard, the
specifc governance structure put in place matters in the fght against management
opaqueness. In this section of the study, the various governance and frm-specifc
variables used in the empirical model are discussed.
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3.2.1 CEO duality. A number of corporate governance studies assert that a situation
whereby the CEO happens to chair the board can raise issues of agency problems (Gul
and Leung, 2004; Fama and Jensen, 1983). In that case, the independence of the board
and its ability to check on management is compromised. The basic question is how can
a CEOwho is also a manager chair a board that is meant to check his/her own activities?
Empirically, much evidence is recorded in favor of the fact that CEO duality leads to
increased management opaqueness and hence less transparency (Chau and Gray, 2010;
Gul and Leung, 2004). Some few studies document that CEO duality helps to provide
unambiguous leadership for the frm. However, there is not enough evidence that
unambiguous leadership can have transparency benefts. Owing to this fact, this study
expects CEO duality to infuence R
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(synchronicity) positively.
3.2.2 Board composition. The composition of the corporate board may infuence
synchronicity. According to Wan-Hussin (2009) and Clarke (2006), independent
directors or non-executive directors do not have any inclination to remain in the good
books of managers and so can speak out on issues both in and outside the board room.
This means that an increased proportion of non-executive directors on the board will
increase transparency, as they will have no incentive to cover up the rot of management.
If an increase in synchronicity signifes less of transparency, board composition is
expected to have a negative relationship with synchronicity.
3.2.3 Board size. The debate on the most appropriate board size needed to be in place
to serve as enough check on management continues unabated. Even in earlier studies,
researchers were divided on the size of corporate boards to keep. Jensen (1993) posited
that a larger board can lead to a less candid discussion in board rooms which invariably
reduces monitoring. This view is also shared by Lipton and Lorsch (1992) who assert
that larger boards bring about free-rider issues and hence less effective monitoring.
However, Adams and Mehran (2003) maintain that a larger board can effectively
monitor management in that such a board comes with an array of expertise needed to
unearth all managers’ hidden activities. Board Size is expected to increase with
transparency.
3.2.4 Audit quality. Perhaps the most agreed upon corporate governance variable
documented to infuence transparency is audit quality. The consensus in literature is
that quality audit can expose the opaque activities of managers (Lin and Liu, 2009; Lee
et al., 2003; Copley and Douthett, 2002). These studies agree to the point that to ensure
that the activities of managers are transparent, quality audit services must be used by
shareholders. The question has been, “what constitutes quality audit?” In literature,
studies have tried using constructs such as the BIG4AUDto characterize audit services
provided by the big four auditing frms (PricewaterhouseCoopers, Ernst & Young,
Deloitte and Touche and KPMG) as being of more quality. These frms have the
necessary skill set needed to expose managers and also the incentive to protect their
reputation by delivering quality services. We expect frms that are audited by one of the
big four audit frms to be more transparent and hence, less synchronous with the
market.
3.2.5 Institutional ownership. The presence of institutional owners on the
shareholder list of companies means more to such company’s transparency level.
Institutional owners are usually large shareholders and managers do not want to
dissatisfy these institutions, actions of whom can send strong and quick signals to the
market. These are also large frm who usually have the resources to monitor
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management activities (Le et al., 2006; Langnan et al., 2007; and Ramzi, 2008). Close
monitoring done by institutional owners results in the reduction of information
asymmetry leading to enhancement of transparency and hence less synchronicity.
Institutional ownership is expected to have a negative relationship with stock return
synchronicity.
3.2.6 Volatility of frm fundamentals. In a study by Skaife et al. (2006), it was
documented that much of frm-specifc variation is experienced in frms that have high
levels of variation in the frm fundamentals. The study used the standard deviation of
return on assets (ROA) as measure of volatility in frm fundamentals. As the
fundamentals of the frmkeep changing, market participants vary the amount of stocks
of such frms held. In this case, frm-specifc variation seen in the stock prices may be as
a result of the volatility in the frm fundamentals (proft). If volatility in frm
fundamentals increases frm-specifc variation, then invariably it reduces market wide
variation. Also in a USA study by Wei and Zhang (2006) greater volatility in a frms’
return on equity is associated with increased stock return volatility. Hence, we expect
that standard deviation of ROA will have a negative relationship with synchronicity.
3.2.7 Market-to-book. Gul et al. (2010) found that Market-to-Book value was
signifcantly negative in predicting synchronicity. Market-to-Book value measures the
growth opportunities of the frm. Firms with higher growth opportunities may want to
signal to the market their abilities. In this case, such frms will be relatively transparent.
They can afford to make outsiders see what the abilities of the frmare. For this reason,
frms with higher Market-to-Book value will exhibit more of frm specifc variation and
less of synchronicity; hence more transparency.
3.2.8 Standard deviation of stock return. Stock return synchronicity is explained to
mean the moving of individual stock returns in line with the market return. By this, for
a stock to be synchronous, there should be movement in its prices and such movement
should be in line with the market return. What this means is that a stock may be seen as
less synchronous not because it is not moving with the market but because it is not
moving at all. Hence, the study includes the standard deviation of the individual stock
returns to control for the difference between moving and non-moving stocks, as well as
between liquid and non-liquid stock (Table I).
We use the Beck and Katz’s panel corrected standard errors in the estimation of the
empirical models; synchronicity under the simple market model and under the
assumption of a non-contemporaneous relationship between market return and
individual stock return. The Generalized Least Square (GLS) was used to check for
robustness of the estimation. To further correct for possible thin-trading that might
have existed in the daily stock return. The study further used the Dimson’s Beta market
model to generate a new set of synchronicity values which was also used as a new
dependent variable in another estimation.
4. Results and discussion
Table II shows the descriptive statistics of the variables that were used in the regression
analysis in the determination of the factors that explain the level of stock return
synchronicity (transparency). Table II also provides information on the skewness and
kurtosis to provide an indication of howthe data are distributed. Table II shows as well
the results of the Sharpiro–Wilk normality test performed to test the normality of the
variables. The null hypothesis test in the Sharpiro–Wilk normality test is that data are
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normally distributed. However, the results, as shown in the Table II, reject the null
hypothesis under almost all the variables, indicating that almost all the variables were
not normally distributed. The descriptive statistics also showthat at every point in time
(whether mean, minimum or maximum), *SYNCH was seen to be higher than SYNCH.
This is as a result of that fact that SYNCH was estimated using the R
2
from the simple
market model, while, in generating *SYNCH, the lag of the market return was included
as an explanatory variable leading to higher set of R
2
generated. Also various variables
have varying number of observations due to the fact that the data used in the estimation
were an unbalanced panel data set with some few missing data points.
Table III shows the correlation matrix between the various variables under
study. The Pearson’s correlation shown in the Table III also serves as the test for
multicollinearity of the variables that were included as part of the explanatory
variables for the study. As shown in the Table III, none of the explanatory variables
is found to be highly correlated (0.5 or above). We fnd a high positive correlation
between the two measures of synchronicity. The correlation between these two
Table I.
Variables and the
measurements
Variables Defnitions
BS Natural log of total number of board members
CEO Dummy variable with the value of “1” if the CEO is the same as the chairman and “0”
if otherwise
B4AUD Dummy variable with the value of “1” if the frm is audited by any of the Big four
Auditors and “0” if otherwise
INSH The percentage of institutional shareholding relative to the total number of shares of
the frm
BC The proportion of independent directors on the board
STDROA Volatility of a frm’s earnings stream measured by the standard deviation of a frm’s
Return on Assets (ROA) over the preceding fve-year period, including the current year
STDDEV Standard deviation of Stock return computed as the standard deviation in the daily
stock returns of a frm in a year
MB Market-to-book ratio, computed as the total market value of equity, divided by the
total net assets at the end of the fscal year
Table II.
Descriptive statistics
of variables used in
the models
Variables Mean Minimum Maximum SD Kurtosis Skew N Sharpiro-Wilk
SYNCH ?1.9930 ?7.8726 1.0276 1.6593 2.7714 ?0.3772 247 3.282***
*SYNCH ?1.4703 ?4.0000 1.3003 1.2847 2.0762 0.0390 255 3.684***
BS 0.9434 0.6990 1.1461 0.0966 2.7810 ?0.2640 252 3.525***
BC 0.7506 0.3333 0.9091 0.1229 3.3727 ?0.7147 251 5.945***
CEO 0.6414 0.0000 1.0000 0.4805 1.3479 ?0.5898 251 ?1.586
INO 0.8222 0.4820 0.9523 0.1035 4.6618 ?1.0530 241 6.97***
BIG4AUD 0.8235 0.0000 1.0000 0.3820 3.8810 ?1.6973 255 3.513***
MB 2.6551 0.0025 17.5439 2.4355 13.5240 2.7674 201 8.416***
SDROA 0.0477 0.0008 0.1765 0.0397 3.5834 1.0922 253 6.918***
STDDEV 0.1002 0.0000 9.3518 0.7077 136.1032 11.1107 230 11.588***
Note: ***1% signifcance level
Source: Computations from research data, 2013
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variables being strongly positive but a little less than 1 suggests that these two
variables are different in themselves but the behavior pattern between them is, to a
greater extent, similar.
We frst sought to use the ordinary least square (OLS) estimation in the regression
process. However, before then, the basic assumptions of the OLS were tested to ascertain
whether the OLS could provide Best Linear Unbiased Estimator (BLUE). According to
the Gauss–Markov theorem, the OLS will be BLUEwhen there are no diffculties such as
autocorrelation and hetroskedasticity. In deciding on the OLS, three different tests were
performed. First, we performedtest for normalityusingSharpiro–Wilknormalitytest as
well as the Doornik–Hansen test for multivariate normality; second, Wooldridge’s test
for autocorrelation in panel data and fnally Breusch–Pagan/Cook–Weisberg test for
heteroskedasticity.
In both models, the null hypothesis of normality was rejected. This indicates that
the assumption of normality was not met in the OLS. The null hypothesis in the
Wooldridge’s test is that there is no frst-order autocorrelation. In Table IV, all the
models met the assumption of no frst-order autocorrelation, as the null hypotheses were
not rejected. However, none of the two models met the assumption of homoskedasticity.
In both cases, the null hypothesis of constant variance among the error terms was
rejected. Hence, to produce robust coeffcients from the estimation, Beck and Katz’s
Table IV.
Diagnostics tests
Variables
Dependent variables
SYNCH *SYNCH
Doornik–Hansen chi2(18) ?7,777.408
Prob ?chi2 ?0.0000
chi2(18) ?7,926.467
Prob ?chi2 ?0.0000
Wooldridge AR(1) F(1, 21) ?0.010
Prob ?F ?0.9207
F(1, 21) ?0.041
Prob ?F ?0.8416
BP/CW Hettest chi2(1) ?21.13
Prob ?chi2 ?0.0000
chi2(1) ?24.71
Prob ?chi2 ?0.0000
Source: Computations from research data, 2013
Table III.
Correlation matrix
Variables 1 2 3 4 5 6 7 8 9 10
SYNCH (1) 1.00
*SYNCH (2) 0.81*** 1.00
BS (3) 0.23*** 0.16*** 1.00
BC (4) ?0.02 ?0.02 0.39*** 1.00
CEO (5) ?0.03 ?0.12* 0.12* 0.11* 1.00
INO (6) ?0.04 ?0.03 0.10 ?0.07 0.33*** 1.00
BIG4AUD (7) 0.01 0.01 0.02 0.11* 0.00 0.06 1.00
MB (8) 0.16** 0.14** 0.10 0.03 ?0.01 0.06 ?0.12* 1.00
SDROA (9) 0.08 0.10 0.00 0.20*** 0.16*** 0.11* ?0.08 0.03 1.00
STDDEV (10) ?0.01 ?0.04 ?0.12* ?0.13 0.07 ?0.03 0.04 ?0.03 ?0.03 1.00
Notes: ***1% signifcance level; **5% signifcance level; *10% signifcance level
Source: Computations from research data, 2013
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(1995) panel corrected standard errors estimation technique was used in estimating both
models, while the GLS was used as robustness check (Table V).
Board size was found to have a signifcant positive relationship with stock return
synchronicity. The positive relationship indicates that larger board sizes are associated
with higher levels of synchronicity. Our results support the argument of the free-rider
effect associated with large board size and also confrms Jensen (1993)’s argument that
larger boards can lead to less candid discussion of critical issues which could also lead
to poor monitoring. Contrary to prior expectation that the quality of audit used by frms
will have a signifcant relationship with transparency, we fnd no evidence in support of
that assertion. We fnd no empirical support for DeAngelo’s (1981) “auditor-reputation
effects” theory that posits that large audit frms with greater investment in reputational
capital have more incentives to minimizes audit errors and hence ensure transparency.
Findings of the study reveal a signifcant negative relationship between board
composition measured as the ratio of non-executive directors to total number of
directors and stock return synchronicity. This provides empirical support for Clarke
(2006)’s theoretical conjecturing that:
[…] independent directors can monitor management effectively as they have no need or
inclination to stay in the good graces of management, and can speak out, inside and outside the
boardroom, in the face of management misdeeds, in order to protect the interests of
shareholders.
This fnding is consistent under both measures of synchronicity. This means that board
composition is positively related to corporate transparency. An increased number of
non-executive directors on the board increases the independence of the board in that
such members have no incentive to please management.
The fndings of this study showthat in the event that the CEOdoubles as chair of the
board, such a frm is likely to exhibit lower levels of stock return synchronicity and
Table V.
Panel corrected
standard errors
estimation
Variables
Dependent variable
SYNCH *SYNCH
Constant ?3.9842 (?2.81)*** ?4.6378 (?4.82)***
BS 4.1235 (3.23)*** 3.4789 (3.89)***
BIG4AUD 0.2089 (0.75) ?0.0807 (?0.41)
BC ?1.9891 (?2.95)*** ?1.1715 (?2.05)**
CEO ?0.4953 (?2.17)** ?0.6359 (?4.12)***
INO ?1.6080 (?1.62) 0.5945 (0.9)
MB 0.1759 (4.44)*** 0.1500 (4.42)***
SDROA 8.0459 (3.69)*** 4.5171 (2.54)**
STDDEV 2.2647 (3.77)*** 1.8019 (4.35)***
R
2
0.4772 0.5201
Wald ?
2
(8) 79.19 73.02
Prob ??
2
0.0000 0.0000
Observations 168 168
Number of frms 31 31
Notes: ***, **, signifcance levels of 1 and 5% respectively; z-statistics are in parenthesis
Source: Computations from Research Data, 2013
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hence higher levels of transparency. By this fnding, we document evidence to the effect
that the benefts of CEOduality mentioned by Gul and Leung (2004) may, in fact, be seen
to increase transparency. This may be so because in Ghana, majority of the frms that
practice CEO duality are the small frms, of which the CEO is usually the owner of the
frm. In such situations, there is incentive for the CEO to push for a more transparent
frm. We fnd a negative relationship between institutional shareholdings stock return
synchronicity indicating that increased institutional ownership translates into higher
levels of transparency. However, this relationship is not statistically signifcant. This
fnding contradicts earlier expectations that increased institutional ownership leads to
increased transparency. However, Haniffa and Cooke (2002) document results similar to
ours. We interpret our results to mean that in the event that institutional investors enter
the capital market as a way of putting their excess cash to use but not executing the
fduciary duties of their owners in search of positive NPV projects, they may be less
interested in the activities of the frms whose shares they own. The study fnds
Market-to-Book ratio to have a signifcantly positive relationship with stock return
synchronicity contrary to the fndings of Gul et al. (2010). We interpret our fndings to
mean that high growth frms are usually those that are newly listed unlike matured
frms that might have stayed on the exchange for a longer period. As frms mature
(market-to-book value reduces) and keep long on the exchange, they become more
transparent (less synchronous); in that the market participants get a better knowledge of
the frm and incorporate frm-specifc information in stock prices.
We fnd a signifcant positive relationship between volatility of frm fundamental
and stock return synchronicity. According to Skaife et al. (2006), frm-specifc variation
is experienced in frms that have high level of variation in the frm fundamentals. It is
expected that as frmfundamentals change, market participants will change the amount
of stocks of such frm held leading to a change in the stock prices. However, fndings
from this study are contrary. This study provides three possible reasons that may
account for not realizing a signifcant negative relationship between volatility of frm
fundamental and synchronicity. First, changes in the frmfundamentals are expected to
elicit changes in the stock prices of the frm due to the fact that such frm-specifc
information will translate into the stock prices. Albeit if changes in frm fundamentals
are synchronous in themselves, then there is a high likelihood that the changes that are
experienced in stock returns will be synchronous as well, leading to an increased
synchronicity. However, this study did not explore the possible infuence of
synchronicity in the frm fundamental changes. Second, changes in frm fundamentals
may not automatically cause traders to vary the amount of stocks of the frm held.
According to Skaife et al. (2006), for a marginal investor to trade, the information signal
received should be enough to exceed the cost of transaction. This suggests that the
infuence of changes in frm fundamentals on stock prices is, to some extent, dependent
on the transaction cost. Finally, there is the possibility of high incidence of
informationally “idiot traders” (Krugman, 2009) or noise trading on the market.
However, the possible presence of noise making does not in any way lessen the use of R
2
as a measure of synchronicity and hence transparency. We discuss this in the literature
review while citing studies such as Li et al. (2003) in support of our position.
The standard deviation of stock return is used as part of the control variables used in
the study to reduce specifcation bias. Stock return synchronicity deals with the extent
to which the return of a stock moves (changes) with that of the market. This suggests a
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stock may be less synchronous not because such a frm is more transparent but due to
non-trading of such stock. Standard deviation of the stock return was used so as to
control for such tendencies. The study fnds a statistically signifcant positive relation
between standard deviation of stock return and stock return synchronicity.
4.1 Further robustness check
To check for the robustness of the relationship between the independent variables and
the dependent variables, we make use of the Generalize Least Square method to estimate
the two models discussed earlier. Results of the GLS estimation are reported in Table VI.
Both models are signifcant as shown by the p-values of their WaldX
2
.
Results from the GLS estimation are consistent with those reported for the Panel
Corrected Standard Errors. This shows the evidence provided by this study in relation
to the relationship between corporate governance and transparency (synchronicity) is
robust. Also due to the fact that daily stock returns were used in the computation of the
stock return synchronicity, there is the possibility of thin-trading. As a form of
robustness check, the study estimates a new set of synchronicity variables while
including the lead of the market return as a regressor in the market model as used by
Dimson (1979) in estimation of the Dimson’s Beta as follows:
R
i,t
? ?
i
? ?
1
R
m,t
? ?
2
R
m,t?1
? ?
2
R
m,t?1
? ?
i,t
(5)
The R
2
from this model is transformed using the logistic transformation in equation (3)
to generate new set of synchronicity variable, LDSYNCH. We then performs an
ANOVAtest to ascertain whether there are differences between these three measures of
synchronicity (SYNCH, *SYNCH and LDSYNCH). The result of the test of ANOVA is
reported in Table VII.
Table VI.
Generalized least
square estimation
Variables
Dependent variable
SYNCH *SYNCH
Constant ?4.9702 (?3.45)*** ?4.2118 (?3.61)***
BS 5.7961 (4.59)*** 3.9266 (3.84)***
BC ?2.4949 (?2.42)** ?1.7229 (?2.06)**
CEO ?0.5270 (?2.07)** ?0.5273 (?2.54)**
INO ?1.5816 (?1.31) ?0.1015 (?0.10)
BIG4AUD 0.3915 (1.25) 0.1515 (0.61)
MB 0.1210 (2.57)** 0.0843 (2.20)**
SDROA 6.4015 (2.31)** 6.5083 (2.90)***
STDDEV 2.1765 (4.16)*** 1.9254 (4.52)***
Wald ?
2
(8) 49.26 47.38
Prob ??
2
0.0000 0.0000
Log Likelihood ?291.9312 ?260.8224
Observation 168 168
Number of frms 31 31
Notes: ***, **, signifcance levels of 1 and 5% respectively; z-statistics are in parenthesis
Source: Computations from research data, 2013
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As shown in Table VII, the F statistics is signifcant, indicating that the null hypothesis
is rejected in favor of the alternative that there is a signifcant different between the
variables. This provides justifcation for using all these different measures of
synchronicity differently. Tables VIII and IX show the model diagnostics and
regression results using the panel corrected standard model with LDSYNCH as the
dependent variable.
Results shown in Table IX consistent with the earlier fndings of the study indicate
that Board size is statistically signifcant and has a positive relationship with the
dependent variable. Board Composition is as well statistically signifcant and
Table VII.
Difference between
various measures of
synchronicity
Source of variation SS df MS F p-value
Between groups 34.3211 2 17.1606 8.9882 0.0001
Within groups 1,336.4562 700 1.9092
Total 1,370.7773 702
Source: Computations from research data, 2013
Table VIII.
Model diagnostics for
LDSYNCH
AR 1: F(1, 17) 0.136
Prob ?F 0.7173
BP/CW Hettest 14.04
Prob ??
2
0.0002***
Doornik-Hansen ?
2
(18) 5,680.67
Prob ??
2
0.0000***
Note: ***Signifcant at 1%
Source: Computations from research data, 2013
Table IX.
Panel corrected
standard errors
estimation for
LDSYNCH
Variables
Dependent variable: LDSYNCH
Coeffcients SE z p ?z
Constant ?3.4400 1.0130 ?3.40 0.0010
MB 0.2120 0.0402 5.28 0.0000
SDROA 1.2849 1.9046 0.67 0.5000
STDDEV 1.9712 0.3255 6.06 0.0000
BS 2.1754 0.9562 2.28 0.0230
BC ?0.9130 0.5455 ?1.67 0.0940
CEO ?0.1878 0.2298 ?0.82 0.4140
INO ?0.3308 0.7419 ?0.45 0.6560
BIG4AUD 0.2203 0.2035 1.08 0.2790
Wald ?
2
(8) 88.23
Prob ??
2
0.0000
R
2
0.5589
Observations 137
Source: Computations from research data, 2013
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negatively related to the dependent variable. Both Institutional Shareholding and Audit
Quality are consistently not signifcant while both Market-to-Book ratio and standard
deviation of returns are statistically signifcant with consistent signs for their
coeffcients. The only difference reported is with CEOduality and Standard deviation of
ROA, both of which were signifcant using the SYNCH and *SYNCH but are not
signifcant with the use of LDSYNCH as dependent variable.
4.2 Comparative analysis
Alsoas part of the empirical analysis, we conduct comparisons betweenfrms onthe basis of
age, size and industry type. We test for signifcant differences in the R
2
recorded for the
various groups of frms. In deciding on whether to use a parametric or non-parametric
approach, we frst perform test of normality on both sets of R squares. We perform a
Shapiro–Wilk Wtest for normal data, the results of which is shown in Table X.
The test for normality rejected the null hypothesis that the data on the two sets of R
squares is normal. Due to the fact that the data breach the assumption of normality
under a parametric approach, we make use of a non-parametric approach by performing
the Wilcoxon Rank’s Sumtest which is the non-parametric counterpart to the Z or t test.
As shown in Table XI, the difference recorded in the R
2
between old frms and newly
listed frms is found to be statistically signifcant under both sets of R Squares. This
means that frms that have been on the exchange for a relatively longer period tend to
have lower levels of synchronicity than their counterparts that are newly listed. Because
synchronicity is an inverse measure of transparency, it can be concluded that newly
listed frms are less transparent than their counterparts who have been on the exchange
for a longer period. The study conjectures that as frms stay listed and public, there is an
increased scrutiny from market participants, especially from investors in the stocks of
such companies. This causes such companies to be more transparent.
Table XII shows the results from the Wilcoxon Rank’s Sum test performed to test the
statistical signifcance of the difference recorded in the R Squares for smaller and larger
frms. As a measure of size of the frm, we use a dummy variable; 1 if the size of the frmis
Table X.
Shapiro–Wilk
normality test
Variable Observation W V z Prob ?z
R
2
255 0.40833 109.193 10.93 0.0000
*R
2
255 0.41929 107.17 10.886 0.0000
Source: Computations from research data, 2013
Table XI.
Synchronicity of old
vs new frms
R
2
Observation Rank sum Expected *R
2
Observation Rank sum Expected
Old frms 95 8,613.5 11,685 Old frms 95 8,661 11,685
New frms 150 21,521.5 18,450 New frms 150 21,474 18,450
Combined 245 30,135 30,135 Combined 245 30,135 30,135
z ?5.704 z ?5.625
Prob ?|z| 0.0000 Prob ?|z| 0.0000
Source: Computations from research data, 2013
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greater than the mean size; and 0 otherwise. The results show that there is a signifcant
difference in the R
2
values recorded for the two groups of frms (smaller and larger) across
the two sets of R
2
values [fromequations (1) and (2)]. This may be as a result of the fact that
the market return is a weighted average index on the exchange. As such, the size of a frm
mayhaveaninfuenceontheentiremarket returndetermination. Largefrmsaremorelikely
to infuence the direction of the market return in line with their individual return. Larger
frms are therefore more likely to exhibit more synchronicity since they are likely to move
more with the market.
Table XIII provides statistical evidence in support of the fact that the R
2
values of
fnancial frms are signifcantly higher than the R
2
values of non-fnancial frms. This may
be as result of the fact that the composite share indexwhichwas usedinthe calculationof the
market return is mainly driven by the fnancial stocks on the GSE. Once the fnancial stocks
(fnancial stock index) drives much of the variations seen in the composite index, fnancial
stocks are more likely to co-move with the market than non-fnancial frms.
5. Conclusion
Consistent with extant literature, this study provides strong evidence of transparency as a
function of governance in the light of an emerging trend in transparency measurement. The
study concludes that in the determination of synchronicity, both assumptions of
instantaneous and non-contemporaneous relationships between the market return and the
individual stock return yield consistent results when used as inverse measures of
transparency. The study provides strong evidence to support the argument of reduced
monitoring by larger board size and free rider effect. Larger board sizes are associated with
higher levels of synchronicity leading to a reduction in transparency. Board Composition
measuredas the ratio of non-executive directors to total directors was foundto be negatively
Table XII.
Synchronicity of
smaller vs larger
frms
R
2
Observation Rank sum Expected *R
2
Observation Rank sum Expected
Smaller 115 10,934.5 13,512.5 Smaller 115 11,122 13,512.5
Larger 119 16,560.5 13,982.5 Larger 119 16,373 13,982.5
Combined 234 27,495 27,495 Combined 234 27,495 27,495
z ?4.998 z ?4.642
Prob ?|z| 0.0000 Prob ?|z| 0.0000
Source: Computations from research data, 2013
Table XIII.
Synchronicity of
fnancial vs non-
fnancial frms
R
2
Observation
Rank
sum Expected *R
2
Observation
Rank
sum Expected
Non-fnancial
frms
188 21,473.5 24,064 Non-fnancial
frms
188 21,356 24,064
Financial frms 67 11,166.5 8,576 Financial frms 67 11,284 8,576
Combined 255 32,640 32,640 Combined 255 32,640 32,640
z ?5.016 z ?5.252
Prob ?|z| 0.0000 Prob ?|z| 0.0000
Source: Computations from research data, 2013
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related to synchronicity and hence positively related to transparency. An increase in the
proportion of non-executive directors on corporate boards can signifcantly reduce
synchronicityandincreasetransparency. CEOdualitycanimprovethe transparencylevelsof
frms. CEO duality is not enough to create an individual powerful enough to reduce the
monitoringrole of boards. Some studies foundthat there are some benefts associatedwithCEO
duality but could not conclude whether such benefts can be in the formof transparency. This
studyprovides evidence of a possible increasedtransparencywithCEOduality.
We conclude that contrary to popular literature that growth frms may want to be
transparent about their potentials, higher levels of growth opportunities associated with
newfrms may lead to higher levels of synchronicity, hence reduced transparency. Also,
frms with volatile stock returns are more likely to exhibit higher levels of synchronicity
and lower transparency. In as much as this may be due to the presence of noise traders
on the GSE, the results suggests that volatility in frm fundamentals per se does not
increase the idiosyncratic information in stock prices. When volatility in frm
fundamentals are synchronous themselves, such volatility may lead to increased
synchronicity and hence less transparency exhibited.
Financial frms exhibit higher levels of synchronicity due to their ability to move the
entire market return in their direction. Larger frms are more synchronous than smaller
frms. This may be as a result of the ability of larger frms to infuence the composite stock
index(market return). The studyfoundfrms that hadbeenlistedfor a relative longer period
time to be less synchronous than their counterpart that just joined the exchange. Going
public requires that a lot more informationabout the frmbe made public evenbeyondwhat
maybe requiredtobe containedinthe prospectus. The studytherefore concludes that listing
on the exchange increases the level of transparency in a frm. For this reason, as a frm
remains longer on the exchange, transparency is improved since the market learns more
about the frm. Although this study is a frm-level study, there could be some policy
implications for the fndings of the study. For a countrythat is seekingto expandcompanies
and grow industries, the last thing that is to be desired is an opaque fnancial market. The
market should be transparent enough to be able to elicit the trust of participants. It is by so
doing that there will be more investment on the capital market thereby increasing
capitalization. This could be done by instituting quality corporate governance mechanisms
that provide enoughdisincentive for frm-level opaqueness. Regulators of the capital market
should develop and adopt corporate governance regulations that will enjoin frms to
constitute their boards in such a way that it shall reduce synchronicity and thus elicit more
informationdisclosure to the participants of the market. Future studies couldinvestigate the
value relevance of stockreturnsynchronicitytofurther provide justifcationfor frms toseek
lower levels of synchronicity.
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Corresponding author
Matthew Ntow-Gyamf can be contacted at: [email protected]
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