Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
Stock Return Predictability through Financial Ratios
(Financial Sectors of KSE)
Anas Aftab1 and Kiran Naseer2
The aim of the current study is to examine the predictability of the return of
common stock of the financial sector of KSE (Karachi Stock Exchange) through
financial ratios. By applying fixed effect model, findings of the study
of 31
financial companies listed in Karachi Stock Exchange from 2003-2012 is showing
that
dividend yield, earning yield and earnings per share has significant
relationship with stock returns .while return on equity and equity to asset ratio is
insignificant.
Keywords: Stock Return, Financial ratios, Listed Financial Companies, Karachi Stock
Exchange.
1. Introduction
Financial statements are imperative to analyse the financial position and performance of
firms. Financial managers design financial statement in such a way that can reflect almost
all aspects of the enterprise. These statements consist of both types of information’s i.e.
Long run information and short run information. And there are many studies which
scrutinize these information for financial decisions. One important approach to evaluate
common stocks is based on analysis of financial statements. Financial statement analysis
has conventionally been seen as piece of the basic analysis required for common stock or
equity valuation. Albeit financial reports information is used in some researches to predict
firms’ prospect monetary performance, such as earnings and growth[24].Where as other
researches explain the impact of financial reports data on share price[15]. Financial ratios
are designed keeping in view the level of information available in financial statements.
Recent studies have shown that accounting ratios can be used to evaluate the future
performance of firms. Investors can be facilitated through financial ratios analysis to make
their investment decisions and predicting firm’s stock returns. The predictability of stock
return can contribute to attaining the highest return with the lowest risk, so it has become
foremost themes for worldwide investors. In previous centuries it was quite difficult to
predict stock returns. This was difficult because the level of market efficiency was not clear.
In contrast, several research studies documented the predictability of stock return based
on different predictors. Researchers try to find out most accurate variables for predicting
stock prices. Financial ratios also became the hot spots of various stock return researches,
as indicated in the work of [17][5][13][20]. Some researchers were tending towards
financial and some were towards profitability ratios i.e. Book to market ratio, price to
earnings ratio, dividend yield. Meanwhile some researchers have used cash flow ratios
like price to cash flow ratio, cash burn ratio, and some focused on macroeconomic
variable like interest rate, law and order situation, foreign exchange and inflation rate etc.
______________________________________________________________________
1
2 1
Anas Aftab ; Kiran Naseer , Facilities & Fleet Officer, British American Tobacco, Pakistan
2
Department of Management sciences, SZABIST Islamabad, Pakistan
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
Albeit many studies are carried out to predict the stock returns of the different markets of developed
as well as developing countries using financial statement information, but unfortunately financial
institutions have been excluded in most of the studies. Because these institutions have special
nature of the last few decades Pakistani financial institutions have been headed by structural
changes that are different than non financial sector. These changes occurred due to the external
environment variation, especially as a ramification of the ample global financial regulations and
monetary policies.
The current study explores the power of financial ratios, to predict common stock return of
financial companies listed on Karachi Stock Exchange. There are ample of studies that have
explored the stock return predictability using financial ratios in the developed as well as in the
emerging economies. Some studies investigate the non financial sector while few have focused on
the financial sector stock return predictability by using financial ratios. This study will help
investors to identify that which ratio has more explanatory power for common stocks. Moreover,
According to my finest information, it is the only study in Pakistan which uses the set of financial
ratios to predict stock returns of financial sector of Karachi Stock Exchange “KSE”. The aim of the
study is to explore the strength of financial ratios to predict stock returns of financial sector of KSE.
This study is focusing on only few ratios. Moreover, this study is only predicting the stock returns
of financial sector. Future studies can test volatility and long run relationship between accounting
ratios and stock returns. The research is delimited due to time constraints to just investigate the role
of few financial ratios to predict stock returns of (financial sector) listed companies of KSE.
II. LITEREATURE REVIEW
In literature there is strong evidence of influence of financial ratios in the prediction on stock
returns .There are a number of researches which test the market of different developed and
underdeveloped countries. The main studies of developed economies [5][6][27][13][14] find the
connection among financial ratios and stock returns. In developing economies studies are also
conducted to unearth the association between various ratios and stock returns. Most of the stocks do
not have their market value same to its intrinsic value. They are either overvalued or undervalued.
The difference in prices of common stock is because of number of factors. The speculative nature of
market, availability of information to all investors, manipulation, incomplete disclosure of data and
non constant performance by firms are key factors in variation in stock prices [19]. Use of
inappropriate tools for evaluation by investors is also key factor in the variation in prices of
common stocks. Another study was conducted by[12] also used different ratios to find out the
intrinsic value of common stocks. Accounting number has the ability to define firm’s value directly.
This ability of financial ratios makes it use more prominent because of pedagogy and its practicality.
Financial statements are considered as fundamental tool that can be used to forecast return of
common stocks. Financial statements are imperative to discuss firm’s conditions. There are number
of studies which examine the financial reports from both paradigms i.e. both annual and interim
reports like quarterly, semi-annually and monthly). Even though the use of information from
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
financial reports is increasing to predict financial performance of the firm [24], but still other
researchers are using these information for common stock evaluation [15].
Study of literature shows that, there is strong support of financial ratios in the predictability of
common stock future returns. Evidence to support the use of financial ratios can be found in both
developing and developed countries. The notion of stock return dates back to 1950 when the dire
need for developing mathematical & statistical models spruced up numerous aspects of the
business. One of the subjects of these models is the advent of the portfolio theory,
proposed by[10]. Later studies on stock returns were derivations from the Markowitz model. An
extensive time series literature was written by [22] to use of financial statement and accounting
ratios to predict return of common stock.
Financial ratios play crucial roles in predicting stock returns. Literature on the predictability of
stock returns shows that among the financial ratios aforementioned ratios have a vigorous
theoretical background supported by predictive models. Investors expect from their investment
returns that can be either in the form of capital gains or dividend yield. On the basis of this
phenomenon the exhaustive ratios which are included among the set of variables to predict stock
returns are Earning Yield (EY), Dividend yield (DY), Return on equity (ROE), Equity to asset (EA)
and Earning per share (EPS). The previous theoretical and empirical literatures indicate that these
three financial ratios are more significant and important on stock return predictability that
encompasses a wide range of prediction. These ratios consist of specific characteristics.
A . Dividend Yield ( DY) and Stock Return
Earlier study shows, return of common stock has a positive relationship with a DY
“dividend yield” in cross-section & time-series respectively. The dividend yield has projecting
influence for a cross-section return of the common stock [2][27][11]. While many studies also
delineate the association between stock returns and dividend yield of time
series.[16][5][6][27][21].[1] in their studies tries to forecast interest rate and stock returns with the
help of predictive power of dividend yield. The result shows that in the short run dividend yield
forecasting is more than the long run. The DY “dividend yield” is measured as dividend per share
on market price per share.
The following formula demonstrates how to calculate dividend yield:
Dividend Yield (%) = (Dividend per Share divided by Market rate per share) x 100
B. Return on Equity (ROE)
Return on equity is measure how efficiently any company will use its assets to generate earnings.
The relationship between the company's profit and the investor's return makes ROE a particularly
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
important metric to be scrutinized. Existing literature findings on return on equity power to predict
stock return shows mixed results. [18] in his study test the association between return on equity and
stock prices of Jordon stock exchange result of his study reveals that return on equity separately
does not have power to predict stock prices. While when it is combined with other ratios then it has
power to predict stock returns.
Return on Equity = (Net Income After Tax/share holders Equity)
C.Earnings Yield ( EY) with Stock Return
Approximately seventy year before, the ratio of price to earnings (the reverse of earnings
yield) was used to predict stock returns of that era[3].Price to earnings ratio is considered as
renowned measurers of valuation today. The empirical literatures put the fundamentals of the
predictive power of EY on stock return, the association between stock return and the earnings yield
is significant, because the earnings yield plays as a risk factor in relation with stock return. Besides,
the earnings yield can also show the efficiency of a market.[26] investigates the relationship
between earnings yield, market value and common stock return for NYSE. The finding of the study
reveals that on average the common stock of high earnings yield firms earn higher risk-adjusted
returns than the common stock of low earnings yield firms. A study conducted by [28] unearth that
earnings yield has the positive impact with stock returns in stock market of Malaysia. [16][21]
argue that earnings yield has independent predictability of stock returns in addition to the dividend
yield.[25]use cross sectional stock return predictability of Philippine Stock Exchange finding of
the study shows that earning yield has predictive power on the stock returns. Earnings yield will be
measured as
Earnings Yield (%) = (Earning per Share / Market rate per share) x 100
B.
Earnings per Share(EPS)
Every organization is intensely interested to maximize its earnings in order to give
maximum return to its shareholder. Another objective behind it is to achieve long term growth of
business by getting additional funds. Although the researcher has included it in the study, because
fluctuations in financial institution's earnings lean to be less severe over time. It is so because of
the capacity of financial institutions to protect earnings with the reserves of the loan to lose, than
non-financial sector, so the shock of the above mentioned variable has crucial impact on return of
common stock. [25] in his study uses different financial ratios to forecast return of the common
stock of both financial as well as in the non financial sector. The result of the study unearths that
EPS plays a very important role to predict return in both sectors of Philippine stock exchange. [9]
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
investigate the importance of earning per share EPS in Taiwan stock exchange and analyze the long
run relationship between EPS and predictability of stock returns. The finding of his study reveals
that EPS has forecasting power to predict stock returns.[7] in his study test the forecasting power of
ratios in TSE “ Turkey Stock Exchang”. Result of the study is contradictory EPS can predict 6%
the current year stock return while same EPS has 63% power to predict the one year later stock
return In the current study EPS “earning per share” will be calculated as follows;
EPS= Net income After Tax/ Number of Outstanding Shares
E. Book value of equity to total assets (EA)
One of the reasons for financial sector ignorance in the previous studies of common stock
return was the difference of leverage structure. In the current study leverage ratio is used to know
whether change in leverage will hold information to change stock returns of financial sector. To
find out the strength of the capital structure the equity to asset ratio is used. This ratio is used
because it captures the financial soundness of financial sector and tells us about their capital
sufficiency. In previous studies leverage is used as an important factor to explain the performance
of financial sectors of the stock markets.[4] in their study find financial leverage as an important
factor to forecast financial institutions’ returns and to find their risk as well. More explicitly, [23]
finds a significant positive relationship between capital ratios & return of the common stock for
financial companies. He also delineates several important methods used to increase capital ratios;
increases in earnings are linked with the biggest stock price increases. In the current study equity to
asset is measured as
Equity to total asset
= Total Equity / Total Asset.
In Sum, the existing literature presents a comprehensive explanation about common stock
returns predictability and financial ratios. Nonetheless, few findings are contradictory due to several
reasons. Some of them are, change in datasets, stock exchange markets and due to difference in the
country’s environment. Many researches are conducted around the world about stock return
predictability through use of financial ratios but, inadequate work has been done on financial
sectors to test the power of these ratios to forecast common stock return[25][7].
The current study concentrates on the gap identified in the literature and test the relationship among
financial ratios and stock return of financial sectors in context of Pakistan, by using econometrics
tools.
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
III THEORETICAL FRAMEWORK
Hypotheses
Based on the above theoretical evidences from literature, following five hypotheses are
formulated
A.
H1: Dividend yield is associated with stock returns.
H2: Return on equity is associated with stock returns.
H3: Earning Yield is associated stock returns.
H4: Earning per share is associated with stock returns.
H5: Book value of equity to asset is associated with stock returns.
B.
Model
In the present study the data which is used is panel data. Panel data has joint effect of times
series and cross sectional data. Common effect model and fixed effect model has been used.
After applying the HAUSMAN test best model is selected. The equation is as follow:
SRit = α0 + α DYit + α ROEit + α EYit + α EPSit + α ETAit + u
Where;
SR = Stock Returns
DY = Dividend yield
ROE = Return on equity
EY = Earning Yield
EPS = Earnings per share
ETA = Equity to asset ratio
IV METHODOLOGY
To test the relationship among financial ratios and stock returns of financial institutions various
econometric techniques are applied. Separately, descriptive statistics’ is applied on independent and
dependent variables. Correlation is also applied and the assumptions of panel data are also fulfilled.
V ANALYSIS OF DATA
Descriptive Statistics
Table(I)
SR
DY
0.025 0.104
Mean
EY
7.622
EPS
9.344
0.802
20.007
21.044
ETA
9.519
SD
0.201
Min
-0.714
.005
-.598
-196.28
-47.58
3.25
Max
1.117
1.515
13.81
200.15
196.52
14.052
310
310
310
310
310
310
N
0.132
ROE
0.226
6
2.513
Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
Table 1 delineates the descriptive statistics of stock returns and five independent variables for 31
listed financial companies for period of 2003- 2012. Value of arithmetic mean of stock returns (SR)
is .025. In the same way dividend yield has mean score of 0.104 with std. deviation of 0.132 and
return on equity has 0.226 averages with deviation of 0.802. Arithmetic means of earning yield,
earnings per share and equity to asset ratio are 7.62, 9.34 and9.51 with deviation of 20, 21 and 2.51
respectively.
B Correlation among Variables
Table (II)
SR
DY ROE EY
EPS
SR
1
DY
-.182
1
ROE
.083
-.062
1
EY
.146
-.070
.059
1
EPS
.171
-.185
.112
-.018
1
ETA
.021
-.319
.006
.010
.161
ETA
1
To find out the association among the abovementioned set of variables, Pearson correlation is used.
Correlation finding is very fruitful to discover Multicollinearity among all variables. It is an an
important assumption of linear regression. Several studies have cited in their findings that if the
correlation among all variables is 0.90 or more, it would be the major reason of Multicollinearity.
Table 2displays the relationship amongst all variables and it directs that there is no any issue of
multicollinearity.
C Linear Regression Model (Common Effect Model)
Table(III)
Coefficients Standard Error
t Stat
Intercept
.067
.048
1.35
DY
-.243
.089
-2.71*
ROE
.012
.013
0.88
EY
.002
.001
2.45*
EPS
.0013
.001
2.60*
ETA
-.0044
.004
-0.95
R Square
0.07
Adjusted R Square
0.06
F Statistics
5.09*
Observations
310
*Significant at the level of 5%
.Heteroskedasiticity Test
Ho = There is no Heteroskedasiticity
H1 = There is Heteroskedasiticity
BP / CW test:
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
Chi 2= 0.76
Prob = 0.38
Table 3 shows the analysis of linear regression or common effect model. According to these results
three hypothesis are accepted. Dividend yield is showing the negative but significant relationship
with dependent variable which is stock price. Means by increasing one unit of dividend yield it will
decrease 0.234 unit of stock return and this decrease would be significant. Earning yield and
earnings per share are also showing significant relationship with stock returns and this relationship
is positive while return on equity and equity to asset ratio is insignificant at level of 5 %. The
current model is linear regression model which is also called common effect model. In case of panel
data there are some assumptions of common effect model which should be checked. The most
important is Heteroskedasiticity. According to the chi square and probability test the value is 0.38
which is insignificant. It leads to reject H1 and shows that there is not any problem of
Heteroskedasiticity in current data. Further fixed effect, random effect model and Hausman test for
best model is also estimated. In panel data most researches has shown that fixed effect model is
appropriate instead of simple linear model or common effect model.
D. Results of Fixed Effect Model
Table(IV)
Coefficients Standard Error
t Stat
Intercept
.117
.293
0.40
DY
-.405
.107
-3.78*
ROE
.001
.014
0.07
EY
.002
.005
3.37*
EPS
.0022
.005
3.59*
ETA
-.009
.031
-0.29
R Square
0.13
F Statistics
7.90*
Observations
310
*Significant at the level of 5%.
Hausman Test for best Model
Ho = Difference among coefficients are not systematic (Either fixed or random or common or between)
H1 = Difference among coefficients are systematic (Fixed Effect)
Chi2 = 15.22
Prob = .0095
E Discussion
For Panel data estimation especially when all models in which common effect, fixed effect, random
effect and between fixed and random model are estimated the important thing is to choose the best
among all models. For this purpose Husman test is estimated. Null hypothesis of Husman test is that
there is not systematic difference among coefficients which means either fixed effect or random
effect; the result will show the same analysis. Alternative hypothesis is that there is systematic
difference among models and fixed effect is best choice for analysis. Significant value of chi square
is showing that null hypothesis is rejected and alternative accepted and it means fixed effect model
is best choice among all models for estimation of this study.
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
Table 4 shows the fixed effect model. According to fixed effect model three hypotheses are
accepted. As discussed above common effect model this Dividend yield is showing the negative but
significant relationship with dependent variable by using fixed effect model as well. Further earning
yield and earnings per share are also showing significant relationship with stock returns and this
relationship is positive while return on equity and equity to asset ratio is insignificant at level of
5 %. R square is 0.13 shows the explanation of dependent variable by independent variable. In case
of panel data this value of R square is acceptable because panel data has combine effect of time
series and cross section data. F statistics shows the fitness of model which means over all model is
significant for this estimation or not. Significant value of F stat at 5 % level shows that this model is
fit for current estimations.
VI
CONCLUSION
Present study explores the relationship among return of common stock and five financial
variables(dividend yield, earning yield, return on equity, earning per share and equity to asset
ratio)Data of ten years of 31 financial companies (2003-20012) listed in Karachi Stock Exchange is
used to apply statistics models. Based on earlier studies five hypotheses have developed. By
applying all models for estimation of panel data fixed effect model is selected for estimation
through hausman test.Result shows that dividend yield, earning yield and earnings per share have
significant relationship with stock returns , while return on equity and equity to asset ratio is
insignificant.
Albeit the current study is an attempt to provide insight to finance managers and to investors
however, current study has few limitations. One of them is that the sample size is not big enough it
is small and only financial institutions are selected. The sampling technique which is adopted is
convenient and it may be possible that might not be generalize able on the whole set of
population .In the developed economies there are studies which have found return of common stock
of different sector it may be a crucial point for future studies. More variables can be added like
macroeconomic variables with large sample size for different sectors to get the more generalized
result. Besides, a comparative study can be conducted to test the predictability of stock returns of
financial and non-financial institutions.
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Proceedings of Annual Paris Economics, Finance and Business Conference
7 - 8 April 2016, Espace Vocation Haussmann, Paris, France
ISBN: 978-1-925488-04-3
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