Download Stock prices and firm earning per share in Nigeria

JORIND 11(2) December, 2013. ISSN 1596-8303. www.transcampus.org/journals; www.ajol.info/journals/jorind
STOCK PRICES AND FIRM EARNING PER SHARE IN NIGERIA
Muhammad Sani Umar
Department of Business Administration, Usmanu Danfodiyo University, Sokoto
&
Tijjani Bashir Musa
Department of Business Administration, Ahmadu Bello University, Zaria
[email protected] +2348067143514
Abstract
The relationship between stock prices and firm earning per share (EPS) appeared to be
contestable like any other performance measures. This study intends to examine the relationship
between stock prices and firm EPS from 2005 to 2009. A simple linear regression model was
employed on a panel of 140 Nigerian firms from a total population of 216 firms’ operated in
Nigerian Stock Exchange (NSE). It was discovered that an insignificant relationship exists
between stock prices and firm EPS in Nigeria. In fact, firm EPS has no predictive power on stock
prices. It was suggested that firm EPS should not be relied upon for the prediction of the
behavior of stock prices in Nigeria.
Keywords: Earning per share, stock price, performance measures
Introduction
The primary goal or objective of a firm should
be to maximize the value or price of a firms
stock. The success or failure of management
decision can be evaluated only in the light of
the impact of firm stock prices (Remi, 2005).
According to Remi (2005) the firm stock
prices has direct purview in the managerial
efficiency which is one of the signals of firm
performances. One of the components of this
firm performance is earning per share (EPS).
EPS is one of the measures of managerial
efficiency as well as firm performance. The
debate on whether EPS has any predictive
power on stock prices is not very clear in
financial literature. Some analysts believe that,
EPS has predictive power on stock prices. This
argument holds the view that, EPS has
influence on stock prices. While the other
argument is that, only positive information
regarding EPS cause the demand for a stock
which result to increase in stock prices. When
viewed over long periods the share prices are
directly related to EPS of the firm. Over short
periods, especially for younger or small firms,
the relationship between stock prices and EPS
is quite unmatched (NSEC, 2006).
The predictive power of EPS on stock prices is
not very clear (NSEC Committee reports,
2007). There are two arguments regarding the
predictive power of EPS on stock prices. One
group argues that, stock prices go up and
down. When there is good news or higher EPS
reports the price of the firm goes up. But if
there is ill news, the price goes down. Looking
at the pattern, is the stock prices determined by
EPS? This group maintains that, stock prices
are not directly determined by EPS. But it is
directly determined by the balance between the
demand and supply of firm stock prices. This
demand and supply causes the stock prices to
fluctuate. In contrast, the other group argues
that, EPS do not determined stock prices.
Kopcke (2000) reports that, in New England
since 1982 stock prices have more than tripled,
while EPS of corporations has risen by less
than one half. From 1997-2000 prices have
increased by more than one half while EPS has
fallen. In January, 2000 the price of stocks for
standard and poor composite 500, stock price
exceeded 23times EPS, a comparatively high
multiple by historical standard.
In Nigeria, the relationship between stock
prices and EPS is also ambiguous. Some firms
are not even in operations, while others are at
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the bridge of collapse, but their stock prices are
increasing (NSEC, 2007). This study intends to
find out the extent of the relationship between
stock prices and EPS in Nigeria. It also
attempts to examine how EPS influences stock
prices in Nigeria?
This study is expected to reveal the predictive
power of firm EPS on stock prices in Nigeria.
If the predictive power of EPS on stock prices
is established it would assist prospective
investors to know the criteria to be used in
channeling their investment fund to the right
portfolio in their quest for investment. The
study covers the period between 2005 to 2009.
Literature review
The concept of stock prices originated from
Random Walk theory in the work of Fama
(1980). The early studies by Fama (1965),
Samuelson (1965) and Working (1960) could
not reject a random walk theory. Shiller (2000)
indicates that there are reasons that the random
walk behavior of stock prices should hold.
There is evidence suggesting that stock prices
do follow a random walk.
Findings by Shiller (2000) support that stock
prices are very much uncertain and this may
not be true because firms fundamentals may to
a great extent influence stock prices. This
argument is supported by early rejection of a
random walk theory by Hoffer and Osborne
(1966) and Porterba and Summer (2000) who
argue that there is little theoretical basis for
strong attachment to the null hypothesis that
stock prices follow a random walk.
Stock prices could be determined by micro and
macro economic factors (Christopher, Rufus
and Jimoh, 2009). These factors which include
book value of the firm, dividend per share,
EPS, price- earning ratio and dividend cover
(Gompers, Ishii and Metrick, 2003). Moore
and Beltz (2002) argue that stock prices of a
firm is influenced by firm beta ratios i.e. its
market value to book value. Hordahl and
Packer (2006) challenge Moore and Belt
(2002) position. They argue that stochastic
discount factor and future pay offs determine
the stock prices. Corwins (2003) identifies
uncertainty and asymmetric information as a
strong influence of firms stock pricing which
led to under price.
The relationship between stock prices and firm
EPS has received considerable attention in the
literature. One of these studies is the one
conducted by Lev (2001) who review several
studies on the information content of firm EPS
and reports that EPS changes only on weekly
related to contemporaneous stock prices.
Shiller (2000), Fama and French (2002) use
regression of stock prices on the lagged firm
EPS and find that they have explanatory power
to stock prices movement. In the same vain,
Ball and Brown (2001) conducted a study to
investigate the annual association between
annual change in stock prices and annual
changes in firms EPS. The result obtained
shows that annual changes in stock prices
cause firm EPS to change in the following
year. Chang and Wang (2008) conducted a
study using Ohlson (1995) model on Taiwan
firms in 2004. The result indicates that firm’s
stock prices movement has a positive
significant relationship with firm EPS.
Shiller (2000) argues that stock prices can be
viewed as a predictions of investors earnings,
therefore, it is reasonable that the variation in
prices should be no greater than variation in
firm EPS. Sheller’s findings have been
investigated thoroughly and reach no
agreement on the results. One important study
of the relationship between stock prices and
firm EPS is the work of Docking and Koch
(2005) who assert that there is direct
relationship between firm EPS announcement
and stock price behavior. In the same vein,
Chetty, Rosenberg and Saez (2007) explain
that stock prices changes behavior when firms
EPS are announced.
Zhao (2000) studies the relationship between
stock prices and firm EPS using regression
model. He found that firm EPS have an
important impact on stock prices, especially on
long horizons, but the hypothesis that move
one-for-one with ex-ante is rejected. In broader
perspective Lee (2002) uses three-years rolling
regressions to analyze the relationship between
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stock prices and firm EPS. He tries to forecast
stock prices on the standard and poor 500
index with the short term firm EPS, but finds
that the relationship is not stable over time. It
gradually changes from a significantly
negative to no relationship then to positive;
although insignificant relationship. In line with
Lee (2002), Spyrou (2001) also studies the
relationship between firm EPS and stock prices
but for the emerging economy of Greece. He
finds that firm EPS are negatively related but
only up to 1995 after which the relationship
become insignificant.
Harasty and Roulet (2000) work on seventeen
developed countries and shows that stock
prices are co-integrated with firm EPS. Hsing
(2004) uses structural VAR model for the
simultaneous
determination
of
firm
fundamental and finds that there is an inverse
relationship between stock prices and firm
EPS. The finding of Hsing (2004), Harasty and
Roulet (2000) indicated that even if the
relationship exist is weak to some extent
between stock price and EPS.
Research methodology
The study is a survey research because it has to
do with the collection of data from a large
finite population. The survey design is suitable
for this study because quoted Nigerian firms
have similar characteristics and behavior in the
Nigerian Stock Exchange. The study covers
216 quoted firms in the Nigerian stock
Exchange. These quoted firms cover thirty one
sectors which include; Insurance, Banking,
Food
and
Beverages,
Petroleum,
Conglomerates,
Agriculture,
Breweries,
Industrials and Domestic Products, Building
Materials, Chemical and Construction among
others.
The sample size was statistically determined
using Yamane (1967) formula for a finite
population. Since the total population of this
study is 216 firms in 31 sectors, then the
sample size can be determined using the
formula:
n = N/1+N (e)2
Where n is the sample size, N is the finite
population, e is the level of significance and is
unity (a constant).
Given the degree of confidence at 5%, the
sample size is 140 firms. This sample size was
divided into four strata. These include the
firms with the highest EPS, the firm with the
lowest EPS, the most performing Stock and the
least performing stocks. Each stratum contains
35 firms.
The study collected data from secondary
sources generated from Nigerian Stock
Exchange (NSE), Nigerian Security and
Exchange Commission (NSEC), documents
from quoted firms and other members of NSE.
A simple linear regression model was built:
Stock pric = α + βearnpsh + Ƹ
Where β isregression parameters which is
defined as coefficient of firms EPS. earnps is
the EPS for the period under study which is
defined as the amount of firm price in relation
to its earnings. stock pric is the stock prices, α
is theregression intercept which is constant and
is the error term of the model.
The model is employed because Beaver (2002)
successfully employed similar model to look at
the general link between security returns and
interest rate using a similar model gt = α +
βGt .
Descriptive results
This section intends to present data from Fact
Book of NSE and individual firms from 2005
to 2009. Some of these data are in absolute
term while others are in ratio form. The stock
prices used for this study was the stock prices
of the year end 25th December, where 25th
falls not on the trading date 24th December is
considered. The firm EPS used is the reported
firm EPS for the selected firms. All data for
the five years have under gone Shapirio Wilk
test for normal data.
The result reveal Z = 12.56 and 13.44 for stock
price and EPS. The probabilities of Z are 0.000
each for stock price and EPS. This made us to
accept the null hypothesis (H0) that the data
are not normal. This abnormality could not
invalidate the study regression test. This
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normality test provides us with premise and
insight to subject our data to descriptive
statistic test.
The descriptive statistic results reveal that the
mean value of stock price is N20.436 with
minimum value at N0.1 and maximum value at
N331.19. The mean value of EPS is – N 0.194,
the EPS is minimum t is – N 551.16 and
maximum at N108.9. These results reveal that
majority of worth (stock price) for the sample
firms are around N 20.436 and most of the
firms operated at loss to the tune of – N0.194.
Regression results
Table 1 Regression Results
Independent Variable
Earning Per share
Pooled OLS
0.0235796
0.48
R2
0.0081
F- statistic
0.23
No of observation
444
LM=614.72***
Source: Extracted from regression result
Dependent Variable (Stock Price)
Models
Fixed Effect
Random Effect
-0.0040434
0.0235796
-0.08
0.48
0.0081
0.0081
0.01
0.23
444
444
In determining the extent of the relationship of
Firm EPS and stock price the study employed
Pooled OLS regression test at first which
revealed that the model is not adequate in
determining the relationship between EPS and
stock price. The model revealed that at less
than 1 percent EPS can explain the behavior of
stock price while the coefficient is low at
0.0235796. Both the F- Statistics and the tstatistics are very low. Second, the study
invokes more robust approach by the use of
fixed effect regression. The result reveals that
the coefficient of determination is -0.0040434,
Z value is -0.08, the R square is 0.008. F
statistics is 0.01 on 444 observations across
164 firms. The F statistics revealed that the
model is not adequate to explain the
relationship and t statistics attested to that.
Random effect regression could be better when
fixed effect regression misbehave.
The result of random effect regression revealed
the same result with the result of pooled OLS.
This necessitates the used of Breuth – Pagan
Langregian multiplier (LM) to ascertain
whether there is panel effect or no panel effect
(i.e no variance across entities), and if no
variance across then Pooled OLS is better,
hence, the choice between pooled OLS and
random effect regression. The null hypothesis
H0 of (LM) is rejected at probability 0.000
with LM = 614.72. This revealed that there is
panel effect and variance across entities which
are not zero. Therefore, in this regard random
effect regression is better.
Table 3 shows that random effect regression
revealed that EPS has less than 1 percent
(0.0081) explanation about the behavior of
stock price, the coefficient of EPS is 0.0236;
this implies that EPS has about 2.36 percent
contribution in the determination of stock
price. The contribution of EPS on stock price
movement is also low with Z statistics of 0.48
which is less than the normal influence value
of 2. The F statistics revealed that the overall
influence of EPS on stock price with the
present value of F= 0.23 is insignificant.
Hypothesis Testing
Ho1 There is no significant relationship
between firm EPS and stock price in
Nigeria.
If the probability of Z is less than 0.05 then
we reject Ho1 thestudy accept Ho1 if other
wise. The probability of Z statistic is 0.629
and therefore the study accepts Ho1. Thus,
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there is no significant relationship between
firm EPS and stock price in Nigeria. This
finding contradicts
Lee (2002) finding which reveals that there
is a significant negative relationship
between stock prices and firm EPS.
However, the relationship is not stable
overtime, it gradually changes from a
significantly negative to no relationship.
The finding of Spyrous (2001) is in line
with Lee (2002) findings in emerging
economy of Greece. He also finds that firm
EPS are negatively related with stock
prices. This in addition further negates the
findings of this study. The findings of Lee
(2002) and Spyrou (2001) have not
indicated a precise relationship between
stock prices and firm EPS.
Ho2
EPS has no predictive power on stock
prices movement in Nigeria.
The study will accept Ho2 ifthe probability of
F statistics is greater than 0.05, if otherwise the
study will reject Ho2. The probability of F
statistics is 0.6289 which is greater than 0.05,
the study therefore accepts Ho2. This implies
that EPS has no predictive power on stock
pricesmovement in Nigeria.This indicates that
EPS has no predictive power on the behavior
of stock prices in Nigeria. This result
contradicts shiller (2000), Fama and French
(2002) findings where they regressed stock
prices on the lagged firm EPS and find that
they have explanatory power to stock price
movements.
Conclusion
There exist insignificant relationship between
stock prices and EPS in Nigeria. The
relationship is insignificant throughout the
period under study. Thus, EPS could not be
used as a basis for prediction of stock prices
movements. Both financial analysts and
prospective investors require daily information
in predicting the
behavior of stock prices in
Nigeria. EPS has no predictive power on stock
prices and couple with the rate of volatility,
then EPS should not be depended upon for the
purpose of prediction of stock prices in
Nigeria. Nigerian firms should not give much
emphasis on maximizing their EPS but should
concentrate on those firm performance
measures which exert more influence on stock
price movement. Nigerian firms should give
more emphasis on expansion and growth; this
would help greatly in maximizing those
performance parameters that could exert
influence on stock price movement.
Monitoring authorities should also intensify
effort to do away with all forms of
irregularities that would make firms operating
in Nigerian Stock Exchange to become
unpredictable by analysts and researchers. This
can only be achieved when Nigerian firms
disclose their actual EPS.
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