Impact of Capital Structure

ijcrb.webs.com JULY 2011
INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS VOL 3, NO 3

Impact of Capital Structure on Stock Price of Cement
Sector in Pakistan

M. Nehal
Hussain
Muhammad Ali Jinnah University Islamabad Pakistan

Sana Gull
Riphah International University Islamabad Pakistan

Abstract
This study investigates the relationship between capital structure and stock price. Current
study uses Debt to Equity Ratio, Debt to asset ratio, interest Coverage Ratio as an
independent variable and stock price of company as dependent variable to investigate the
relationship between capital structure and stock price. Study based on cement sector,
eleven companies was selected actively trading in Karachi Stock Exchange during the
period 2005 to 2009.Secondary data is collected through financial statements of
companies and stock prices will be collected from Karachi Stock Exchange. Descriptive
statistics, simple and multiple regression analysis is applied to find out the relationship of
firm. However, we found that, there is negative relationship between capital structure and
stock price. The present study is a unique contribution in the existing literature of finance
in the context of emerging market like Pakistan.
Key Words: Capital Structure, Stock Price, Pakistan.
1. Introduction
The firm can choose a mix of financing options to finance its assets so that its overall
value can be maximized and this is known as the capital structure of the firm. The seminal
work of Miller & Modigliani (1958) showed that the market value of a firm is determined
by its earning power and the risk of its underlying assets, and is independent of the way it
chooses to finance its investments or distribute dividends. Remember, a firm can choose
between three methods of financing: issuing shares, borrowing or spending profits (as
opposed to dispersing them to shareholders as dividends). The theorem gets much more
complicated, but the basic idea is that under certain assumptions, it makes no difference
whether a firm finances itself with debt or equity.
In Pakistan, there are more than 25 small and large cement manufacturers
operating within the country producing ordinary grey Portland, white, slag and sulphate
resistant varieties of cements. This industry has an oligopolistic structure because the
product is homogenous. The cement industry in Pakistan has grown gradually with the
passage of time. At the time of independence there were only four units with total
production capacity of nearly half a million tons per annum. By 1972 the number of
cement plants increased to 14 and the production capacity also increased to 2.5 million
tons. Both public and private sectors took initiative to establish new plants. As was the
case for other industries, the cement industry was also nationalized in 1972 and the State
Cement Corporation of Pakistan (SCCP) was established and given the responsibility to
manage the production of cement in the country. Considering the higher cement demand
as compared to supply, cement import was also allowed in FY 76-77 that continued until
FY 94-95. With a change in policy of state control over industrial units, the state owned
cement plants were also put-up for privatization along with other industries. The private
sector was allowed to invest in the cement manufacturing. Consequently, the role of
COPY RIGHT ? 2011 Institute of Interdisciplinary Business Research

SCCP as market leader vanished gradually and currently it owns only four plants, of
which two have been closed down on efficiency and profitability grounds. In view of the
higher demand during the period of de-regulation and liberalization, a number of new
units were set up and many others invested heavily to increase their existing production
capacity. As a result, the production capacity has reached 17.7 million tons per annum
during 2003.
There are 29 cement production units in the country. Up to May 2007, the total
installed cement production capacity is 36.841 million tones. By the end of June 2011, the
installed cement production capacity will touch to the level of 49.579 million tones. Due
to political instability and lack of allocation of funds for public sector development
program, cement industry of Pakistan was in the recession phase had registered an
average growth rate of 2.96% for the period from 1990 to 2002. For the period from 2003
to 2007 cement industry of Pakistan had registered an average growth rate of 20%. The
boost in cement sector is because of the rising construction activity in the country,
reconstruction activity in Afghanistan and increasing development expenditure by the
government. There are four foreign companies, three armed forces companies and 16
private companies listed in the stock exchanges. The industry is divided into two broad
regions, the northern region and the southern region. The northern region has over 87
percent share in total cement dispatches while the units based in the southern region
contributes 13 percent to the annual cement sales.
The cement industry of Pakistan entered the export markets a few years back, and
has established its reputation as a good quality product. The latest information is that
India will import more cement from Pakistan. So far 130,000 tones cement has been
exported to the neighboring country. During the financial year-07, cement sales registered
a growth of 31 percent to 17.53 million tones as against 13.5 million tones sold last year.
The cement sales during July-February-08 showed an increase, both in domestic and
regional markets to 18.17 million tones. The domestic sales registered an increase of 7.2
percent to 14.4 million tones in the current period as compared to 13.5 million tones last
year whereas exports stood at 3.7 million tones as against 1.8 million tones in the
corresponding period last year, showing an increase of 110 percent.
The government is considering allowing further concessions and additional
incentives for cement export, with a view to increase overall export volume. These
measures will immensely help in promoting and protecting high investments made in
cement sector in recent years. In the wake of its huge surplus production as a result of
massive capacity expansion undertaken it rather seems. Imperative for Pakistani cement
industry, on one hand, to sustain existing export markets and, on the other, explore new
markets.
In FY08 to-date, Pakistan cement industry brought in 5.84 million tons of new capacity of
cement production taking the total cement capacity to 36.1 million tons. This includes DG
Khan’s new Khairpur plant & Maple Leaf’s new production line of 2.1 million tons each
and some other additions of 1.8 million tons. Going forward, Lucky Cement with its 2
new lines of 1.26 million tons capacity each and Fauji Cement with its 2.1 million tons
new line are expected to come online. With these additions and other expansions, the total
industry installed capacity is expected to reach 49.1 million tons per annum by FY10.
Pakistan has already joined the world club of cement exporters, with 48th ranking
among a total of 116 exporting countries, having attained recently an export figure of
USD 33.24 million. Some of the big players from Pakistan who can possibly play a major
role in the export of cement to India are Lucky Cement, the largest cement producer in the
country, DG Khan Cement Co, Bestway Cement, Maple Leaf Cement, Attock Cement,
among others.


1.1. Significance of the study
Capital structure is one of the most important characteristics of a firm. Many theories
suggest that a change in the capital structure indicates a change or review of the firm
value, which should therefore have an impact on stock prices. Examining the relationship
between capital structure and stock price of Pakistan cement sector will clearly show that
capital structure has positive or negative relationship with stock price. The result will help
investors to invest in cement sector, because capital structure matters to firm value.
Changes in capital structure have an impact on stock price. Change in debt and equity
effect stock price. For example, if the dynamic pecking order theory holds, increase in
debt may result in a decrease in the stock price. On the other hand, according to trade-off
theory, a deviation from the optimal capital structure (either increase or decrease) would
result in a lower stock price.

1.2. Objectives of the study
The objectives of the study are followings:
¾ To Study the way firms structures their capital structure.
¾ To examine the relation between capital structure and stock prices.
¾ To provide guidance to the investor to invest in cement industry of Pakistan.
¾ To study impact of change in debt equity ratio and its impact on the stock
price of a particular cement firm and industry as a whole.

2. Literature Review
Many finance theories predict that the capital structure matters to firm value, which
implies that the changes in leverage have an impact on stock returns. We propose and test
several hypotheses to explain the observed relationship. We find the negative relation is
stronger for the firms with higher leverage level. This is consistent with a dynamic view
of the pecking-order model that increase in leverage reduces firms’ debt capacity and may
lead to future underinvestment. In addition, the long-term debt plays a more important
role in this relation than the short-term debt, and the leverage change has no impact on
future stock return, both of which are inconsistent with the default risk premium
hypothesis. Deviation from the target leverage ratio has no impact on contemporaneous
stock returns, which is inconsistent with the trade-off theory. Further tests on leverage
change and future operating performance do not support the view that increase in leverage
signals bad news for future performance of the firm in our sample. Overall, our evidence
favors the dynamic pecking-order theory over other capital structure theories. (Cai and
Zhang, 2005)
It is well known that firms are more likely to issue equity when their market
values are high, relative to book and past market values, and to repurchase equity when
their market values are low. We document that the resulting effects on capital structure
are very persistent. As a consequence, current capital structure is strongly related to past
market values. The results suggest the theory that capital structure is the cumulative
outcome of past attempts to time the equity market. (Baker and Wurgler, 2002)
This paper is an empirical study that tests the relationship between leverage and
stock returns. We investigate this relationship by undertaking a portfolio level analysis of
leverage and expected returns using the Fama-Macbeth (1973) methodology with
modifications. We find that returns increase in leverage which is consistent with the
findings of Miller-Modigliani (1958). We also undertake linearity tests. Results are robust
to other risk factors. (Sivaprasad and Muradoglu, 2007)
Leverage is an important risk factor which has been ignored in the asset pricing
literature. This paper attempts to broaden the focus of the current asset pricing literature


by forming portfolios mimicking the leverage factor. Returns are ranked according to
leverage and grouped into two groups of high and low to demonstrate the risk factor of
leverage in stocks. We argue that leverage is an important stock-market factor that
explains stock returns. We also undertake robustness checks with the Fama-French (1993)
factors of size, market-to-book and excess returns on market. Our results show that our
leverage mimicking portfolio capture the variations in stock returns better relative to the
other asset pricing models. (Sivaprasad and Muradoglu, 2008).
Using a panel of 425 European firms over the period from 1990 to 2005, we
revisit Welch’s (2004) finding that stock returns are the primary determinant of capital
structure changes and that the corporate motives for issuing activities remain largely
unexplained. We document that about half of the variation in leverage can be explained
by stock return-induced effects over both 1-year and 5-year horizons. In contrast to the
US evidence, corporate issuing activities are not as pronounced in our European sample,
but they seem nevertheless sufficient for firms to maintain a target debt ratio in the long
run. Therefore, our results are also consistent with recent evidence for dynamic
rebalancing of the capital structure within a target range in the presence of adjustment
costs. In a horse race with stock returns, traditional capital structure variables are inferior
in explaining corporate leverage ratios and readjustment in response to return-induced
changes in the short run, but they retain a significant role in the long run.
This is an empirical study that investigates the effect of firm’s leverage on stock
returns. We start with the explicit valuation model of Modigliani and Miller (1958) and
expand the model further to test the relation between stock returns and firms’ leverage.
Modigliani and Miller (1958) conduct their empirical tests exclusively in the utilities and
oil and gas industries. We conduct our tests in all risk classes. Modigliani and Miller
(1958) conduct their tests in the cross section for one year whereas we employ a rich
panel dataset. They use balance sheet definitions for return to equity while we use stock
returns. Our leverage definition takes into account the cash flows generated through debt
financing, following Schwartz (1959). We control for other risk factors. We first conduct
the analysis at the firm level and then at the portfolio level to include factor mimicking
portfolios for size, book-to market, market risk and momentum. We find that for utilities,
returns increase in leverage which is consistent with the findings of Modigliani and Miller
(1958) and Bhandari (1988). But for the other sectors, the relationship is negative which
is similar with the more recent work of Korteweg (2004), Dimitrov and Jain (2005) and
Penman (2007). Results are robust to other risk factors and level of analysis. We conclude
that the contradicting empirical results in literature are mainly due to the restrictions in the
samples used. The positive relationship between leverage and stock returns is unique to
utilities, a risk class that is highly regulated and has high concentration of leverage ratios.
(Muradoglu and Sivaprasad, 2008)
The value of a firm’s securities measures the value of the firm's productive assets.
If the assets include only capital goods and not a permanent monopoly franchise, the
value of the securities measures the value of the capital. Finally, if the price of the capital
can be measured or inferred, the quantity of capital is the value divided by the price. A
standard model of adjustment costs enables the inference of the price of installed capital.
Data from U.S. corporations over the past 50 years imply that corporations have formed
large amounts of intangible capital, especially in the past decade. (Hall, 2001)
This paper attempts to determine the capital structure of listed firms in the cement
industry of Pakistan. The study finds that a specific industry’s capital structure exhibits
unique attributes which are usually not apparent in the combined analysis of many sectors
as done by Shah & Hijazi (2005). The study took 16 of 22 firms in the cement sector,
listed at the Karachi Stock Exchange for the period 1997-2001 and analyzed the data by
using pooled regression in a panel data analysis. Following the model developed by Rajan


& Zingle (1995) it has chosen four independent variables i.e. firm size (measured by
natural log of sales), tangibility of assets, profitability and growth and further analyzed
the effects on leverage. The results, except for firm size, were found to be highly
*
significant. (Syed Tahir Hijazi Yasir Bin Tariq, 2006).
This paper provides a competitive equilibrium model of capital structure and
industry dynamics. In the model, firms make financing, investment, entry, and exit
decisions subject to idiosyncratic technology shocks. The capital structure choice reflects
the tradeoff between the tax benefits of debt and the associated bankruptcy and agency
costs. The interaction between financing and production decisions influences the
stationary distribution of firms and their survival probabilities. The analysis demonstrates
that the equilibrium output price has an important feedback effect. This effect has a
number of testable implications. For example, high growth industries have relatively
lower leverage and turnover rates. (Miao, 2005)
An ongoing argument in financial management has been how to craft a capital
structure which maximizes shareholder wealth. This question has gained prominence
within the strategic management field because of the apparent link between capital
structure and the ability of firms to literature, we are able to theorize that a firm’s capital
structure is influenced by environmental dynamism, and that the match between
environmental dynamism and capital structure is associated with superior economic
performance. Our large-scale empirical analyses provide supportive evidence for the
proposition that competitive environments moderate the relationship between capital
structure and economic performance. From a theoretical standpoint, these findings
provide another link between capital structure and corporate strategy. More importantly,
we are able to move the discussion beyond the limitations of financial risk and
incorporate the strategy concept of decision making under uncertainty. For practical
application, these findings offer informed advice for managers on how to craft a capital
structure. (Simerly and Mingfang, 2000)
This study examines the influence of institutions on the capital structure and debt
maturity choices in a cross-section of firms in 39 developed and developing countries.
Our evidence indicate that firms operating within legal systems that provide better
protection for financial claimants tend to have capital structures with less total debt, and
more long-term debt as a proportion of total debt. In addition, we find that firms that
choose to cross-list tend to use more equity and longer-term debt. We also find that taxes
and the characteristics of the financial institutions that supply capital have an influence on
how firms are financed. Finally, we find that the cross-sectional determinants of leverage
differ across countries. In particular, the relationship between profitability and leverage
tends to be stronger in countries with weaker shareholder protection. (Fan, Titman and
Twite, 2008)
Political institutions play a role in shaping factor mobility across sectors, space,
and borders. I provide an illustration of this accepted, though hardly researched, idea by
looking at the emergence of modem capital markets in the nineteenth century. The rise of
corporate finance threatened to redeploy financial resources away from land and
traditional sectors to heavy industry. I argue that mobilized and integrated markets
flourished in the absence of blocking coalitions that had an interest in keeping finance
local. I argue and show that the power of blocking coalitions was a reverse function of the
degree of centralization of state institutions. I start by providing a conceptual interface
between the abstract notion of capital used in trade models and the diversity of its actual
occurrences as cash, debt, equity, buildings, patent, machinery, and so forth. (Verdier,
spring 2001).
We study simultaneous investment and financing decisions made by incumbent
owners in the presence of capital market imperfections. We present a theory for how the


optimal combination of debt and equity financing depends on the firm's internal funds.
We identify complementarities between the two financial instruments. We test these
predictions empirically with panel data on 3,119 corporations in the COMPUSTAT
database. Our estimates using instrumental variable techniques support our theoretical
predictions regarding the link between internal funds and capital investments, as well as
the interaction effects between debt and new equity. We explore implications for
managers, financiers, and policy makers. (Stenbacka and Tombak, 2002)
This paper presents a continuous time model of a firm that can dynamically adjust
both its capital structure and its investment choices. The model extends the dynamic
capital structure literature by endogenizing the investment choice as well as firm value,
which are both determined by an exogenous price process that describes the firm’s
product market. Within the context of this model we explore interactions between
financial distress costs and debt holder/equity holder agency problems and examine how
the ability to dynamically adjust the capital structure choice affects both target debt ratios
and the extent to which actual debt ratios deviate from their targets. In particular, we
examine how financial distress and the firm’s objectives, i.e., whether it makes choices to
maximize total firm value versus equity value, influence the extent to which firms make
financing choices that move them towards their target debt ratios. (Titman and Tsyplakov,
2005)
We investigate the determinants of capital structure choice by analyzing the
financing decisions of public firms in the major industrialized countries. At an aggregate
level, firm leverage is fairly similar across the G-7 countries. We find that factors
identified by previous studies as correlated in the cross-section with firm leverage in the
U.S., are similarly correlated in other countries as well. However, a deeper examination of
the U.S. and foreign evidence suggests that the theoretical underpinnings of the observed
correlations are still largely unresolved. (Rajan and Zingales, 1991)
Firm size has been empirically found to be strongly positively related to capital
structure. A number of intuitive explanations can be put forward to account for this
stylized fact, but none have been considered theoretically. This paper starts bridging this
gap by investigating whether a dynamic capital structure model can explain the cross-
sectional size-leverage relationship. The driving forces that we consider is the presence of
fixed costs of external financing that lead to infrequent restructuring and create a wedge
between small and large firms. We find four firm size effects on leverage. Small firms
choose higher leverage at the moment of refinancing to compensate for less frequent
rebalancing. But longer waiting times between refinancing lead on average to lower levels
of leverage. Within one refinancing cycle the intertemporal relationship between leverage
and firm size is negative. Finally, there is a mass of firms opting for no leverage. The
analysis of dynamic economy demonstrates that in cross-section the relationship between
leverage and size is positive and thus fixed costs of financing contribute to the
explanation of the stylized size-leverage relationship. However, the relationship changes
the sign when we control for the presence of unlevered firms. (Kurshev and Strebulaev,
2006)
This paper examines the relative importance of many factors in the leverage
decisions of publicly traded American firms from 1950 to 2003. The most reliable factors
are median industry leverage (+ effect on leverage), market-to-book ratio (-), tangibility
(+), profits (-), log of assets (+), and expected inflation (+). Industry subsumes a number
of smaller effects. The empirical evidence seems reasonably consistent with some
versions of the tradeoff theory of capital structure. (Frank and Goyal, 2007)
This paper is a review of the central theoretical literature. The most important
arguments for what could determine capital structure is the pecking order theory and the
static trade off theory. These two theories are reviewed, but neither of them provides a


complete description of the situation and why some firms prefer equity and others debt
under different Circumstances. The paper is ended by a summary where the option price
paradigm is proposed as a comprehensible model that can augment most partial
arguments. The capital structure and corporate finance literature is filled with different
models, but few, if any give a complete picture. (Frydenberg, 2004)
Corporate governance theory predicts that leverage affects agency costs and
thereby influences firm performance. We propose a new approach to test this theory using
profit efficiency, or how close a firm’s profits are to the benchmark of a best-practice firm
facing the same exogenous conditions. We are also the first to employ a simultaneous-
equations model that accounts for reverse causality from performance to capital structure.
We also control for measures of ownership structure in the tests. We find that data on the
U.S. banking industry are consistent with the theory, and the results are statistically
significant, economically significant, and robust. (Berger and Patti, 2003).
Figure1 Frame work

Independent Dependent
Variables Variable

Debt to equity

Stock price
Debt to total
assets

Interest
coverage ratio

3. Hypotheses

Ho: There is negative relationship between capital structure and stock price.
H1: There is positive relationship between capital structure and stock price.

4. Research Methodology

Population All the cement companies which are listed on the Karachi Stock Exchange
have been selected as a population.
Sample
From the whole population a sample of eleven companies was selected which are listed
below:
1. Fauji Cement Company Ltd.
2. Cherat Cement Company Ltd.
3. Attock Cement Pakistan Ltd


4. Bestway Cement Ltd.
5. D.G. Khan Cement Company Ltd.
6. Dandot Cement Company Ltd.
7. Gharibwal Cement Ltd.
8. Kohat Cement Ltd.
9. Pioneer Cement Ltd.
10. Lucky Cement Ltd.
11. Maple Leaf Cement Factory Ltd.

These companies were chosen because of availability of data and also these are listed on
the Karachi Stock Exchange.
Sampling Techniques. The sampling technique will be convenient sampling.
Research Instruments. Three types of ratios are used to study the impact of capital
structure on stock price i.e. debt to equity ratio, debt to total asset and interest coverage
ratio.
Total Debt Ratio= Total Liabilities/ Total Assets
Debt to asset ratio = Total debt / assets
Coverage Ratio = Operating Profit / interest charges
Data Collection. Data for our research is collected from annual financial statements of
the companies i.e. balance sheets, profit and loss account. It also includes articles,
internet, books (financial management, accounting), and KSE published reports (monthly
opening and closing rates of cement companies).

5 .Analysis & Interpretation of Data

Ratios analysis on eleven selected companies has been conducted for five years 2004-
2008. All the tables below show the trend of these companies each year.

Table 1 FAUJI CEMENT

2008 2007 2006 2005 2004
Debt to equity ratio 0.34 0.71 0.89 1.54 2.05
Debt to total asset 0.3 0.4 0.5 0.6 0.7
Interest coverage ratio 4.1 4.8 7.7 4.3 3.5
stock price 9.8 15 19.05 19.475 13.47
5
Figure1
Fauji Cement

25 Debt to equity
20 ratio
15 Debt to total asset
10
5 Int eres t c
overage ratio
0
s toc k price
2008 2007 2006 2005
2004



Figure 1 shows that stock price of the company was maximum in 2005 where debt to
equity and debt to total assets decreased as compared to the previous year. It is obvious as
companies risk decreased that year which attracted the market. Next three years
contradicts this tradition trend. The reason for this unusual trend may be because of
political and economical instability of the country. Stock price in 2008 was minimum as
all the ratios were less then the ratios in 2005.

Table 2 CHEHRAT CEMENT

2008 2007 2006 2005 2004
Interest coverage ratio 0.3 4.3 9.9 21.1 31
stock price 25.555 40.35 64.625 81.25 62.6
Figure 2 5
Chehrat Cement

100 Debt to
80 equity ratio
60 Debt to total as set
40
20 Interes t
coverage ratio
0
s toc k pric e
2008 2007 2006 2005
2004

Stock price is maximum in 2005 and it is minimum in 2008. it is also observed that
interest coverage ratio is minimum in 2008 which shows positive relation between interest
and stock price of the company. Negative relation has been observed between debt and
stock price of the company.

Table 3 ATTOCK CEMENT

2008 2007 2006 2005 200
4
Interest coverage ratio 5.39 12.69 55.9 104 55.6
stock price 68.69 82.9 73.55 71.05 48.4


Figure 3
Attock Cement

120 Debt to
100 equity ratio
60
40
Interes t
20
coverage ratio
0
stoc k price
2008 2007 2006 2005
2004

Fluctuation has been observed in interest coverage ratio each year which lead to the
fluctuation in stock price of the company. Whereas debt to equity and debt to total assets
remained consistent through out five years showing no significant change. Stock price of
the company was maximum in 2007 i.e. 82.9 and minimum in 2004 i.e. 48.4.
Table 4 BESTWAY CEMENT

2008 2007 2006 2005 2004
stock price 42.5 53 59.5 53.5 34.7
Figure 4 5

Bestw ay Cement

80 Debt to equity
ratio
60
Debt to total asset
40
20 Interes t c
overage ratio
0
s toc k price
2008 2007 2006 2005 2004

Company enjoyed highest stock price in 2006 where debt to equity ratio, debt to total
asset and interest coverage ratio were 2.72, 0.73 and 4.7 respectively. A consistent trend
has been observed through out regarding debt to equity and debt to total assets. This is the
reason of its consistency in stock price.
Table 5 D. G. KHAN CEMENT
2008 2007 2006 2005 2004
Interest coverage ratio 0.9 4.7 8.7 8 6
stock price 57.985 78.825 84.775 80.675 50.22
5


Figure 5
D.G Khan Cement

100 Debt to
80 equity ratio
60 Debt to total as set
40
20 Interes t
coverage ratio
0
s toc k pric e
2008 2007 2006 2005
2004

Interest coverage ratio is maximum in 2006 so as stock price of the company. Figure 5
shows positive relationship between stock price and interest of the company. Other ratios
are consistent each year, not showing big fluctuation. In 2006 debt to equity and debt to
total assets are on average of these five years.

Table 6 DANDOT CEMENT

2008 2007 2006 2005 2004
Interest coverage ratio -1.44 -1.55 1.7 0.1 -0.7
stock price 22.215 18.05 11.25 9.975 7.27
Figure6 5

Dandot Cement

25 Debt to equity
20 ratio
10
5 Interest
coverage ratio
0
stock price
-5 2008 2007 2006 2005 2004

Above table 6 shows positive relation between debt and stock price as debt to equity and
debt to total assets is maximum in 2008 which resulted maximum stock price of the
company in these five years.



Table 7 GHARIBWAL CEMENT

2008 2007 2006 2005 2004
Interest coverage ratio -1.2 -2 5.2 2.6 2.1
stock price 16.695 12.925 12.2 14.45 10.2
Figure 7 5
Gharibw al Cement

20 Debt to
15 equity ratio
Debt to total as set
10
5 Interes t
0 coverage ratio
2008 2007 2006 2005 2004 s toc k pric e
-5

Stock price of the company is maximum in 2008 as compared to any other year. Positive
relation has been observed between debt and stock price. Above table shows that debt to
equity and debt to total assets are maximum in 2008 which increased stock price of the
company i.e. 16.695.

Table 8 KOHAT CEMENT

2008 2007 2006 2005 2004
stock price 33.825 41.55 56.65 70.025 53.32
5

It is evident from the graph above table 8 that stock price of Kohat Cement was maximum
in 2005 where interest coverage ratio is maximum as compared to any other year. It is
minimum in 2008, which decreased the stock price of the company and lead it to the most
minimum level. This shows the positive impact between interest and stock price.
Similarly comparing debt to equity ratio and debt to total assets we observed that they are
maximum in 2008 where stock price decreased to minimum level comparing with other
years. It shows negative impact.



Figure 8
Kohat Cement

80 Debt to
equity ratio
60
Debt to total asset
40
20 Interes t
coverage ratio
0
stoc k price
2008 2007 2006 2005 2004

Table 9 PIONEER CEMENT

2008 2007 2006 2005 200
4
Interest coverage ratio -0.39 0.5 5.7 4.3 2.2
stock price 27.865 26.95 38.1 36.175 14.1
Figure 9

Pioneer Cement

50 Debt to equity
40 ratio
20
10 Interes t
coverage ratio
0
s toc k price
-10 2008 2007 2006 2005
2004

Debt to equity is observed consistent in last four years it was maximum in 2004 where the
stock price of the company was minimum. Interest gave a positive impact on stock price
as it was maximum in 2006 which lead to stock price to the maximum level. High level of
fluctuation is observed in interest coverage ratio in the past five years which fluctuated its
stock price.
Table 10 LUCKY CEMENT

2008 2007 2006 2005 2004


stock price 73.885 88.2 71.9 62.275 32.6
5



Lucky Cement

100 Debt to
80 equity ratio
40
20 Interes t
coverage ratio
0
stoc k price
2008 2007 2006 2005
2004

Unusual trend has been observed between interest and stock price of the company. It is
seen that interest coverage ratio is maximum in 2004 and stock price is minimum as
compared to 2007 where interest is minimum and stock price is maximum. Debt to equity
and debt to total asset gave a positive impact on stock price as in 2004 both are minimum
and in 2006 they are maximum which increased stock price.

Table 11 MAPLE LEAF CEMENT

2008 2007 2006 2005 200
4
Interest coverage ratio 0.25 0.6 5.8 6 1.8
stock price 11.65 18.3 28.575 35.325 31.1
Figure11

Maple Leaf Cement

40 Debt to
equity ratio
30
Debt to total asset
20
10 Interest
coverage ratio
0
stock price
2008 2007 2006 2005 2004


5. Results & Discussions

Table I Correlation Analysis
Correlations

DEBT DEBTASS INTREST STOCKPRICE
DEBT Pearson Correlation 1 . -.327* -.440**
Sig. (2-tailed) 830** .015 .001
N 55 .000 55 55
DEBTASS Pearson Correlation . 55
1 -.372* -.399**
Sig. (2-tailed) 830** * .003
N .000 55 .005 55
INTREST Pearson Correlation 55
-.327* -.372* 55
1 .383**
Sig. (2-tailed) .015 * .004
N 55 .005 55 55
STOCKPRICE Pearson Correlation -.440* 55
-.399* . 1
Sig. (2-tailed) * * 383**
N .001 .003 .004 55
55 55 55
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

we use regression analysis to investigate the relationships between dependent and
independent variables.

Table II Regression Analysis

Model Summary

Adjusted Std. Error of
Model R R Square R Square the
1 .508a .258 .214 Estimate
22.02437
a. Predictors: (Constant), DEBT, INTREST, DEBTASS

Table II above reveals that fifty percent change will be explained by these three
independent variables i.e. debt to equity ratio, debt to total assets and interest coverage
ratio.
It is evident from the table I that debt to equity ratio is showing very less negative
significance i.e. -0.440. Debt to total assets is -0.399 which is also very less negatively
significant. It is obvious as debt increases companies become more risky and which result
in decrease in stock price. So there is a weak negative relation between debt to equity,
debt to total asset and stock price.
Whereas above table also reveals that interest coverage ratio is very weak positive
significant i.e. 0.383. It shows positive relationship between interest coverage ratio and
stock price. As our hypothesis statement is about relationship between stock price and
capital structure so this result shows a weak negative relationship between capital
structure and stock price can affect stock price. Interest coverage ratio indicates the ability
of the company to meet its interest costs. So it can also affect stock price. But as our result


is showing negative relationship so there are some other factors which affects more sock
price. After getting results, Ho is accepted and H1 is rejected.
Now we will see the previous studies what they have been identified about impact
of capital structure on stock price. We will see the relationship between dependant and
independent variables whether they have positive relationship or negative.
Previous studies document a negative correlation between stock price and debt
ratios, which is usually interpreted in favor of the pecking order theory.
Capital structure is one of the central focuses in the corporate finance literature. Various
theoretical models, such as the tradeoff, pecking-order, and market timing models, have
been proposed to explain firms’ capital structure. These models also suggest that leverage
changes affect firm value and stock prices.
Jie Cai , Zhe Zhang (2005) focus on the effect of change in firms’ leverage on
stock returns. Using a sample of U.S. public firms, they show that firms with higher
leverage changes on average have lower returns. They test whether their results can be
explained by the pecking-order models, the default risk premium, the tradeoff models, or
the operational performance hypothesis. Their results are consistent with a dynamic
version of the pecking-order theory, which suggests that an increase in leverage reduces
safe debt capacity and leads to future underinvestment. This theory predicts a negative
effect of leverage change on stock returns.
Further, this effect should be stronger for firms that already have high leverage.
They find empirical supports for both predictions. In addition, they find a negative effect
of leverage change on future investment, suggesting that increasing leverage does lead to
future underinvestment. Their results provide little support for the default premium
hypothesis.
First, there is no evidence that firms with a higher leverage increase have higher future
returns. Second, there is a significant, negative effect of the change in long-term debt
leverage on stock returns, but a much weaker effect for the change in short-term debt
leverage. Both results are not consistent with the default risk premium hypothesis. Nor do
the results appear to be consistent with the tradeoff models. Tradeoff models imply an
optimal (target) capital structure. Deviation from the target should have a negative effect
on stock price. Yet, when they sort stocks into portfolios based on the deviation or change
in deviation from the target leverage, they do not find significant return patterns across
these Portfolios. Nor can our results be explained by the market-timing hypothesis, which
predicts that a firm will lower debt financing and increase equity financing if its equity is
overvalued. As a result, leverage decrease signals overvaluation of equity and has a
negative effect on stock price, which is opposite to our findings. Further tests also suggest
that the operational performance hypothesis proposed in Dimitrov and Jain (2003) is
unlikely to explain the results for their sample. Finally, we show that the leverage
innovation effect contains information about the cross-sectional stock returns that cannot
be explained by popular asset pricing factors. This result has important implication for the
construction of performance benchmarks and investors’ portfolio allocation decision.
Gulnur Muradoglu and Sheeja Sivaprasad (Nov 2008), they find leverage to have
a negative relation with stock returns. They find that returns have a negative relation with
leverage in the Consumer Goods, Consumer Services and Industrials sectors.
Some prior literature has examined capital structure ratios based not only on market
equity value but also on book equity value. Yet, the book value of equity is primarily a
“plug number” to balance the left-hand side and the right-hand side of the balance sheet
and it can even be negative.
Rajan and Zingales (1995) offer the definitive description of capital structures and
find a strong negative correlation between market-book ratios and leverage. Like Rajan


and Zingales, Barclay, Smith, and Watts (1995) find that debt ratios are negatively related
to market-book ratios.
Muradoglu and Sivaprasad, Nov 2008, this is an empirical study that investigates
the effect of firm’s leverage on stock returns. They conclude that the contradicting
empirical results in literature are mainly due to the restrictions in the samples used. The
positive relationship between leverage and stock returns is unique to utilities, a risk class
that is highly regulated and has high concentration of leverage ratios.
After looking some previous studies we found that capital structure has negative
relationship to stock price. Our result is showing negative relationship between capital
structure and stock price, so may be there are some other factors which affects stock price
more than capital structure. According to our results capital structure is affecting 25% to
stock price other factors are affecting 75%.

5. Conclusion
According to our result, there is negative relationship between capital structure and stock
price. In previous studies we also find that they have given results that there is negative
relationship between capital structure and stock price. So result proves hypothesis Ho and
rejects H1. We found that capital structure is affecting 25% to stock price, it shows that
capital structure does not affect too much to stock price. There are some other factors
which affects stock price 75%. We are focusing only micro factor so at the end we can
conclude that macro factors like demand and supply, political instability, inflation, etc
.these factors have some relationship to stock price.

6. Recommendation
We will recommend only that those who will conduct research on this topic impact of
capital structure on stock price, they must see macro factors because according to result
capital structure affects 25% to stock price so 75% affects other factors.



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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
2004 VOL 3, NO 3
Appendix 13.475
stock Debt to equity Debt to total Ints coverage
years price ratio 2.05 asset ratio
0.7
3.5
2005
19.475
0.34
0.6
4.3
2006
19.05
0.71
0.5
7.7
2007
15
0.89
0.4
4.8
2008
9.8
1.54
0.3
4.1
2004
53.325
0.83
0.45
17.2
2005
70.025
0.53
0.35
25.2
2006
56.65
0.35
0.26
20.2
2007
41.55
1.51
0.6
1.2
2008
33.825
2.27
0.7
0.7
2004
32.65
0.63
0.39
90.6
2005
62.275
1.88
0.65
56.8
2006
71.9
2.34
0.7
31.8
2007
88.2
1.75
0.64
4.1
2008
73.885
0.84
0.5
19.2
2004
14.1
6.84
0.87
2.2
2005
36.175
2.86
0.67
4.3
2006
38.1
2.36
0.65
5.7
2007
26.95
2.83
0.69
0.5

2005 71.05 0.61 0.38 104
2006 73.55 0.65 0.39 55.9
2007 82.9 0.7 0.41 12.69
2008 68.69 0.66 0.4 5.39


Impact of Capital Structure

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