Download the relationship betweeen financial leverage and

THE RELATIONSHIP BETWEEEN FINANCIAL LEVERAGE
AND PROFITABILITY OF FIRMS LISTED AT THE NAIROBI
SECURITIES EXCHANGE
LYDIAH KABARE KUNGA
A RESEARCH PROJECT SUBMITTED IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD
OF THE DEGREE OF MASTER OF SCIENCE IN FINANCE,
SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI
OCTOBER 2015
DECLARATION
This research project is my original work and has not been presented to any other
University or Institution for an award of a degree.
Signature ………………………………………
Date……………….…………
Lydia Kabare Kunga
D63/70982/2014
This research project has been submitted for examination with my approval as the
University of Nairobi supervisor
Signature ………………………………………
Dr. Kennedy Okiro
Lecturer
Department of Finance and Accounting
School of Business, University of Nairobi
ii
Date……………….…………
ACKNOWLEDGEMENT
Thanks to Almighty God for His grace and lighting my path daily.
I am fully indebted to my supervisor, Dr. Kennedy Okiro who made a monumental
task much lighter. Thank you for your advice, insightful criticisms and guidance.
My immeasurable appreciation to my family and friends for helping me survive the
stress from this year and encouraging me not to give up. Thank you.
My deepest gratitude goes to my colleague, Christopher Githuku who took on extra
duties while I worked on the project and Sally Cheptoo, my most trusted cheerleader.
iii
DEDICATION
This project is dedicated to my family. Thank you for your solid support and
encouragement during this entire period.
A special dedication goes to the memory of my sister Loise, her strong faith in what
she stood for and believed.
iv
TABLE OF CONTENTS
DECLARATION ..................................................................................................... ii
ACKNOWLEDGEMENT ...................................................................................... iii
DEDICATION ........................................................................................................ iv
LIST OF TABLES ................................................................................................ viii
LIST OF ABBREVIATIONS AND ACRONYMS................................................ ix
ABSTRACT ............................................................................................................. x
CHAPTER ONE: INTRODUCTION ..................................................................... 1
1.1 Background of the Study...................................................................................... 1
1.1.1 Financial Leverage ................................................................................ 2
1.1.2 Firm Profitability ................................................................................... 3
1.1.3 The Relationship Between Financial Leverage and Profitability ............ 4
1.1.3 Nairobi Securities Exchange .................................................................. 4
1.2 Research Problem ................................................................................................ 5
1.3 Research Objective .............................................................................................. 7
1.4 Value of the Study ............................................................................................... 8
CHAPTER TWO: LITERATURE REVIEW ........................................................ 9
2.1 Introduction ......................................................................................................... 9
2.2 Theoretical Framework ........................................................................................ 9
2.2.1 Modigliani-Miller Theorem ................................................................... 9
2.2.2 Pecking Order Theory ......................................................................... 10
2.2.3 Trade-Off Theory ................................................................................ 12
2.3 Determinants of Firm Profitability ..................................................................... 12
2.3.1 Profitability ......................................................................................... 13
2.3.2 Firm Size ............................................................................................. 13
v
2.3.3 Liquidity ............................................................................................. 14
2.4 Empirical Review .............................................................................................. 14
2.5 Summary of the Literature Review..................................................................... 18
CHAPTER THREE: RESEARCH METHODOLOGY ...................................... 20
3.1 Introduction ....................................................................................................... 20
3.2 Research Design ................................................................................................ 20
3.3 Population ......................................................................................................... 20
3.4 Data Collection .................................................................................................. 20
3.5 Data Analysis .................................................................................................... 21
3.5.1 Analytical Model................................................................................. 21
3.5.2 Tests of Significance ........................................................................... 22
CHAPTER FOUR: DATA ANALYSIS, RESULTS AND DISCUSSION........... 23
4.1 Introduction ....................................................................................................... 23
4.2 Response Rate ................................................................................................... 23
4.3 Descriptive Statistics.......................................................................................... 23
4.4 Pearson Product Moment Correlation Coefficient .............................................. 25
4.5 Regression Analysis and Hypothesis Testing ..................................................... 26
4.5.1 Model Summary .................................................................................. 26
4.5.2 Analysis of Variance ........................................................................... 27
4.5.3 Model Coefficients .............................................................................. 27
4.6 Discussion of Findings ....................................................................................... 29
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS
................................................................................................................................ 30
5.1 Introduction ....................................................................................................... 30
5.2 Summary of Findings ......................................................................................... 30
vi
5.3 Conclusion......................................................................................................... 32
5.3 Recommendations.............................................................................................. 32
5.4 Limitations ........................................................................................................ 33
5.5 Suggestions for Further Research ....................................................................... 33
REFERENCES ...................................................................................................... 34
APPENDIX I: LIST OF FIRMS LISTED AT NSE (2014) .................................. 38
APPENDIX II: SECONDARY DATA OF QUOTED FIRMS EXTRACTED
FROM AUDITED REPORTS .............................................................................. 41
vii
LIST OF TABLES
Table 4.1 Descriptive Statistics ................................................................................ 24
Table 4.2 Pearson’s Correlation Analysis ................................................................. 25
Table 4.3 Model Summary ...................................................................................... 26
Table 4.4 Analysis of Variance ................................................................................ 27
Table 4.5 Model Coefficients ................................................................................... 27
viii
LIST OF ABBREVIATIONS AND ACRONYMS
CMA
Capital Markets Authority
NSE
Nairobi Securities Exchange
ROA
Return on Assets
ROE
Return on Equity
SPSS
Statistical Packages for Social Sciences
ix
ABSTRACT
This study sought to establish the relationship between financial leverage and
profitability of firms listed at the Nairobi Securities Exchange. To achieve this
objective a descriptive research design was used. The study considered firms that
have been listed on the NSE for the past five years and utilized secondary data
obtained from the period 2010-2015. Data was collected from 47 listed firms which
represented a response rate of 73 percent. This was considered sufficient for making
generalization on the whole population. The study covered a period of five years from
2010-to-2014. Data was analyzed using descriptive statistics, correlation analysis and
regression analysis. The results indicated that liquidity and financial leverage depicted
a negative relationship with profitability. Size of the firm was found to have a positive
relationship with profitability of listed firms at the Nairobi Securities Exchange. The
limitation of this study is that it used only four variables only, namely; financial
leverage, firm size, profitability and liquidity. Profitability is affected by many factors
other than the ones discussed in this study and therefore it is important to consider
other factors that have bearing on profitability and establish whether the findings will
hold or not after which conclusive results can be drawn. The study recommends that
listed firms should look for alternative ways of financing their projects other than
using financial leverage. From the results obtained it is evident that financial leverage
does not contribute to profitability of the firm. This is because when a firm borrows
more from its creditors then the firm has to pay more amount of cost of debt to the
creditor which is the interest rate. This leads to less net income for the firm and hence
lower profitability.
x
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Businesses deploy a number of strategies to improve profitability, including
streamlining processes, outsourcing and integrating new technologies. Financial
leverage offers an alternative way to increase profits by financing a portion of the
business through loans or by issuing stock. Akhtar (2012) indicates that financial
leverage does not guarantee an improvement in profitability. All businesses must cope
with a degree of uncertainty regarding future sales, but businesses offering new or
untested products and services run much higher risks of failure. As a consequence,
securing financial leverage for such businesses may come at the cost of unfavorable
interest rates and higher dividend payments for stockholders, which makes it more
difficult to improve profitability. Businesses offering products or services with a
demonstrable track record with consumers can often secure financial leverage at more
favorable rates.
Cheng and Tzeng (2010) a firm that successfully uses leverage demonstrates by its
success that it can handle the risks associated with carrying debt. This can become an
important factor when additional financing is needed. Not only will loans more likely
be available, but they will be available at more attractive interest rates. Like
individuals, companies with solid financials, but little credit history, sometimes have
trouble convincing lenders that they are deserving of a good rate.
Leverage under financial strategy planning helps to increase the rate of return by
generating a greater return on borrowed money than the cost of using that money. If
firms return on assets is greater than the before tax interest rate paid on debt then we
can say that leverage is positive. Companies that dislike to borrow funds for the
1
financing of their assets have to rely completely on equity financing therefore they are
free from any fixed amount of charges to pay which means there is no financial
leverage associated with that company. It is obligatory that every individual
organization has to give especial focus towards the most important questions of
amount of financial leverage, associated cost of capital and their impact on the firm’s
profitability (Amalendu, 2012).
1.1.1 Financial Leverage
Abor (2005) defines financial leverage as the amount of debt that an entity uses to buy
more assets. Leverage is employed to avoid using too much equity to fund operations.
An excessive amount of financial leverage increases the risk of failure, since it
becomes more difficult to repay debt. The financial leverage formula is measured as
the ratio of total debt to total assets. As the proportion of debt to assets increases, so
too does the amount of financial leverage.
Financial leverage is favorable when the uses to which debt can be put generate
returns greater than the interest expense associated with the debt. Many companies
use financial leverage rather than acquiring more equity capital, which could reduce
the earnings per share of existing shareholders. Financial leverage is a risky approach
in a cyclical business, or one in which there are low barriers to entry, since sales and
profits are more likely to fluctuate considerably from year to year, increasing the risk
of bankruptcy over time (Amalendu, 2012).
Agrawal and Nagarajan (1990) argue that financial leverage may be an acceptable
alternative when a company is located in an industry with steady revenue levels, large
cash reserves, and high barriers to entry, since operating conditions are sufficiently
steady to support a large amount of leverage with little downside. There is usually a
2
natural limitation on the amount of financial leverage, since lenders are less likely to
forward additional funds to a borrower who has already borrowed a large amount of
debt.
1.1.2 Firm Profitability
Penman (2007) defines profitability as the ability to make profit from all the business
activities of an organization, company, firm, or an enterprise. It measures
management efficiency in the use of organizational resources in adding value to the
business. Profitability may be regarded as a relative term measurable in terms of profit
and its relation with other elements that can directly influence the profit. Profitability
is ‘the ability of a given investment to earn a return from its use (Srivastava &
Srivastava, 2006). Profit maximization is said to be the main objective of all firms. In a
competitive marketplace, a business owner must learn to achieve a satisfactory level
of profitability. Increasing profitability involves determining which areas of a
financial strategy are working and which ones need improvement.
Maheshwari (2001) explains that profitability is the final measure of economic
success achieved by a company in relation to the capital invested. This economic
success is determined by the magnitude of the net profit. To achieve an appropriate
return over the amount of risk accepted by the shareholders is the main objective of
companies operating in capitalist economies. After all, profit is the propulsive element
of any investments in different projects. The assessment of profitability is usually
done through the Return on Assets (ROA) which equals to Net Income divided by
Total Assets and ROE (Return on Equity) that is equal to Net Income divided by
Equity, which is the ultimate measure of economic success.
3
1.1.3 The Relationship Between Financial Leverage and Profitability
Wald (2000) observes that highly profitable firms have lower levels of leverage than
less profitable firms because they first use their earnings before seeking outside
capital. In addition, stock prices reflect how the firm performs. Firms tend to issue
equity rather than use debt when their stock price increases, so that their leverage
levels stay lower than firms using debt. Similar findings were reported in Gu (1993),
Sheel (1994), Sunder and Myers (1999) and Wald (2000). According to Wald (1999),
profitability, which is the most significant determinant of firms’ financial leverage,
negatively affects the debt to asset ratios. Sheel (1994) also supported the negative
relationship between debt-to-asset ratio and non-debt tax shield and between a firm’s
leverage behavior and its past profitability.
According to previous studies, financial leverage affects cost of capital, ultimately
influencing firms’ profitability and stock prices. Several researchers have studied the
firms’ debt use and suggested the firms’ debt-equity decision is generally based on a
trade-off between interest tax shields and the costs of financial stress (Upneja &
Dalbor, 2001). According to the trade-off theory of capital structure, the optimal debt
level balances the benefits of debt against the costs of debt. The tax benefits of debt
dominate up to certain debt ratio, resulting in higher return on equity, but the benefit
would be less than the cost after the level of debt ratio. The more a company uses
debt, the less income tax the company pays, but the greater it’s financial risks.
1.1.3 Nairobi Securities Exchange
The Nairobi Securities Exchange (NSE) is a market that deals with exchange of
securities issued by public quoted companies and the government. The Nairobi
Securities Exchange is licensed and regulated by the Capital Markets Authority
4
(CMA). It has the mandate of providing a trading platform for listed securities and
overseeing its Member Firms. NSE (2014) there is 64 firms licensed under the NSE;
this is provided in Appendix I of this study. The stock exchange market helps in the
transfer of savings to investment in productive ventures rather than keeping the
savings idle. This helps to cultivate a culture of saving to local and foreign investors
who are interested in investing.
Kale (2014) noted that listed firms that use financial leverage to finance their assets
are likely to pay low taxes due to allowable interest deductions. Tax rules permit
interest payments as expense deductions against revenues to arrive at taxable income.
The lower the taxable income, the less tax a company pays. For instance dividends
paid to equity holders are not tax-deductible and must come from after-tax income.
Tax savings help further reduce a company’s debt financing cost, which is an
advantage that equity financing lacks that might significantly lead to improved
profitability.
Firms use financial leverage as a result of utilizing their finance assets. As a result, the
firms bear less risk, compared to firms that finance their assets using equity. Upon
liquidation of the firm, debt holders have more claiming rights to company assets; this
gives them security for their investments. Listed firms that finance their projects using
financial leverage might easily retain profits and financial performance within the
firm as compared to those using equity. Firms prefer financial leverage to finance
stable business operations in which they can more easily make ongoing interest
payments and retain the rest of the profits to themselves (Adongo, 2012).
1.2 Research Problem
5
Dittmar (2004) indicates that if firm use less amount of debt then it has to pay less
amount of fixed cost associated with that borrowed money. Such fixed cost associated
with the borrowed money is the cost of debt which is generally called interest amount.
Padron and Santana (2005) assert that if firm borrows more money from its creditors
then the firm has to pay more amount of cost of debt to the creditor which is called
interest rate this leads to less net income for the firm and hence lower profitability.
This is consistent with the findings by Eunju and SooCheong (2005) who concluded
that there was an inverse relationship between financial leverage and profitability of
firms.
In Kenya, listed firms consider four basic elements of debt financing, these are:
business risk, the need for financial flexibility, the degree of ownerships’ risk
aversion, and tax considerations. Nduati (2010) argues that listed firms adopt more
debt so that they can enjoy less income tax. However; the firm is more exposed to
financial risks. Kale (2014) in his study argued that debt is worthwhile if the firm
reach excessive profits which improve the return to shareholders. He further explains
that most local firms utilize debt for their future plans because fixed cost of debt is
usually pre decided and this enables the firm to plan since the cost is apparent.
Mahira (2011) investigated the effect of firm profitability and its financial leverage on
capital structure in automobile sector companies in Pakistan. The study found that the
profitability of the firm and its financial leverage have no significant impact on the
capital structure of the studied firms. Akhtar (2012) studied the impact of leverage on
corporate financial performance applied on oil and energy companies sector. The
results showed that financial leverage leads to improved performance. Subaii (2012)
study examines the relationship between financial leverage and return on assets at the
level of each sector of the three economic sectors of the Kuwaiti economy. The study
6
concluded that there is a positive relationship between financial leverage and return
on investment for all economy sectors.
Adongo (2012) studied the effect of financial leverage on profitability and risk of
firms listed at the Nairobi Securities Exchange. All the 58 firms listed at the NSE as at
2011 were not covered in this study. The results were based on a sample while 15
firms were excluded from the same sample. The study did not factor in firm size
which is an important consideration for a firm that finances its projects using financial
leverage. The results found that there was an insignificant relationship between
returns adjusted by risk and financial leverage on firms listed at the Nairobi Securities
Exchange. Nduati (2010) investigated on the relationship between leverage and
financial performance of listed firms. It was found that there was a positive
correlation between leverage and financial performance. Kale (2014) examined the
impact of financial leverage on firm performance: the case of non-financial firms in
Kenya. The findings revealed that there is a significant negative relationship between
leverage and return on assets in non-financial firms in Kenya.
The above studies show that little has been done in relation to financial leverage and
profitability of listed firms in the Nairobi Securities Exchange. Further, the studies
did not factor in liquidity which is important in establishing whether firms that utilize
financial leverage are able to meet their financial obligations.
This study therefore attempts to answer the question: What is the effect of financial
leverage on the profitability of firms listed at the Nairobi Securities Exchange?
1.3 Research Objective
To determine the relationship between financial leverage and profitability of listed
firms in the Nairobi Securities Exchange.
7
1.4 Value of the Study
This study is helpful to listed firms as it shows the impact of cost of financing and
financial leverage and in particular how it contributes to profitability. The findings
will be used to guide listed firms on financial decisions in the areas of management
and the use of funds to maximize the market value of the business which is a key
financial goal of most firms.
Firms in other sectors can learn the benefits of utilizing financial leverage and how it
impacts on profitability. The findings of this study might be used as a reference point
to firms seeking to finance their projects using financial leverage.
This study adds to the existing body of knowledge on the significance use of financial
leverage to the firm and how this contributes to profitability of the firm. Future
researchers and academicians interested in this area of study or other related topics
will use the findings of this study as a reference point. In addition, this study can be
used as a basis for further research.
8
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This section provides the theoretical framework of the study, the determinants of the
profitability, the empirical review and the summary of the literature review.
2.2 Theoretical Framework
This section covers the theories that support the relationship between financial
leverage and profitability of the firm. These theories include: Modigliani-Miller
theorem, Pecking Order Theory and Trade-off Theory.
2.2.1 Modigliani-Miller Theorem
Modigliani-Miller (1958) maintains that a firm’s market value is calculated by the risk
associated with the underlying assets of the firm and also on the earning capacity of
the firm. The theorem further states that the market value of the firm is not affected by
the choice of financing the investments or on the decisions of distributing the
dividends. The three ways that a firm can select to finance the investments are
borrowing outside capital, issuing the shares and reinvesting the profits. According to
the theory, under some market assumptions whether or not the firm investments are
financed with equity or debt makes no difference. The Modigliani-Miller theorem is
very often referred to as the capital structure irrelevance principle. This suggests that
the valuation of a firm is irrelevant to the capital structure of a company. Whether a
firm is highly leveraged or has lower debt component in the financing mix, it has no
bearing on the value of a firm (Modigliani & Miller, 1963).
9
Modigliani and Miller Approach further states that the market value of a firm is
affected by its future growth prospect apart from the risk involved in the investment.
The theory stated that value of the firm is not dependent on the choice of capital
structure or financing decision of the firm. If a company has high growth prospects,
its market value is higher and hence its stock prices would be high. If investors do not
see attractive growth prospects in a firm, the market value of that firm would not be
that great (Miller, 1977).
Going by the assumptions of this theory on no taxes, the capital structure does not
influence the valuation of a firm. In other words, leveraging the company does not
increase the market value of the company. It also suggests that debt holders in the
company and equity share holders have the same priority, that is, earnings are split
equally amongst them.
The proponents of this theory argue that financial leverage is in direct proportion to
the cost of equity. With increase in debt component, the equity shareholders perceive
a higher risk to the company. Hence, in return, the shareholders expect a higher
return, thereby increasing the cost of equity. The theory assumes that debt holders
have an upper-hand as far as claim on earnings is concerned. Thus, the cost of debt
reduces.
2.2.2 Pecking Order Theory
Pecking order theory was first suggested by Donaldson (1961), it was later modified
by Myers and Majluf in 1984. The theory states that firms prioritize their sources of
financing (from internal financing to equity) according to the cost of financing,
preferring to raise equity as a financing means of last resort. Hence, internal funds are
used first, and when that is depleted, debt is issued, and when it is not sensible to issue
10
any more debt, equity is issued. The pecking order theory states that there are three
sources of funding available to firms namely: retained earnings, debt, and equity
(Myers, 1994).
Retained earnings have no adverse selection problem. Equity is subject to serious
adverse selection problems while debt has only a minor adverse selection problem.
From the point of view of an outside investor, equity is strictly riskier than debt. Both
have an adverse selection risk premium, but that premium is larger on equity.
Therefore, an outside investor will demand a higher rate of return on equity than on
debt. From the perspective of those inside the firm, retained earnings are a better
source of funds than debt and debt is a better deal than equity financing. The firm will
fund all projects using retained earnings if possible (Harris & Raviv, 2003).
The pecking order theory makes predictions about the maturity and priority structure
of debt. Securities with the lowest information costs should be issued first, before the
firm issues securities with higher information costs. This suggests that short-term debt
should be exhausted before the firm issues long-term debt (Baskin, 2002).
The pecking order theory assumes that there is no target capital structure. Due to
adverse selection, firms prefer internal to external finance. When outside funds are
necessary, firms prefer debt to equity because of lower information costs associated
with debt issues. This theory maintains that businesses adhere to a hierarchy of
financing sources and prefer internal financing when available, and debt is preferred
over equity if external financing is required (equity would mean issuing shares which
means bringing external ownership into the company). Thus, the form of debt a firm
chooses can act as a signal of its need for external finance (Myers, 2001).
11
2.2.3 Trade-Off Theory
The trade-off theory of capital structure refers to the idea that a company chooses how
much debt finance and how much equity finance to use by balancing the costs and
benefits. Myers (1984) posits that trade-off theory of capital structure basically entails
offsetting the costs of debt against the benefits of debt. The Trade-off theory of capital
structure discusses the various corporate finance choices that a corporation
experiences.
The theory describes that the companies or firms are generally financed by both
equity and debt. Trade-off theory of capital structure primarily deals with the two
concepts, cost of financial distress and agency costs (Welch, 2004). An important
purpose of the trade-off theory of capital structure is to explain the fact that
corporations usually are financed partly with debt and partly with equity (Kraus &
Litzenberger, 1973).
Frank and Goyal (2011) explain that there is an advantage to financing with debt, the
tax benefits of debt, and there is a cost of financing with debt, the costs of financial
distress including bankruptcy costs of debt and non-bankruptcy costs for example,
suppliers demanding disadvantageous payment terms, bondholder and stockholder
infighting. The marginal benefit of further increases in debt declines as debt increases,
while the marginal cost increases, so that a firm that is optimizing its overall value
will focus on this trade-off when choosing how much debt and equity to use for
financing (Fama & French, 2002).
2.3 Determinants of Firm Profitability
There are a number of factors that affect profitability of the firm, this study has
discussed the following factors:
12
2.3.1 Profitability
According to the pecking order theory in the presence of asymmetric information, a
firm will prefer internal finance, but would issue debt if internal finance is exhausted.
The last alternative would be issue new equity. Myers (1984) prescribed a negative
relationship between profitability and debt. Daskalakis and Psillaki (2008) argue that
profitability may be regarded as a relative term measurable in terms of profit and its
relation with other elements that can directly influence the profit. Profitability is ‘the
ability of a given investment to earn a return from its use. Profit maximization is said to
be the main objective of all firms
Profitable firms are likely to have more retained earnings. Successful companies do
not depend as much on external finance. Empirical evidence from previous studies
like Al-Sakran, (2001); Kayo and Kimura (2010) appears to be consistent with the
pecking order theory. Most studies found a negative relationship between profitability
and debt financing (Daskalakis & Psillaki, 2008; Vasiliou et al., 2009).
2.3.2 Firm Size
Profit interacts with size: Large firms are less susceptible to bankruptcy because they
tend to be more diversified than smaller companies. Therefore, lower expected
bankruptcy costs enable large firms to take on more debts. The larger firms can
reduce the level of information asymmetries in the market and obtain financial
resources more easily. Large firms are more likely to access debt as compared to
small firms since they are more stable. (Padron et al., 2005). If two companies have
same profitability, larger company will get more external finance.
Size plays an important role in capital structure (Abor & Biekpe, 2009). Small firms
are often managed by very few managers whose main objective is to minimize the
13
intrusion in their business and that is why internal funds will lie in the first place of
their preference of finance. If internal funds are not enough, small firms will prefer
debt to new equity mainly because debt means lower level of intrusion and lower risk
of losing control. Hussain and Matlay (2007) assert that small firms strive for external
sources of finance only if the internal sources are exhausted. Small firms try to meet
their finance needs with a pecking order of personal and retained earnings, debt and
issuance of new equity.
2.3.3 Liquidity
According to Padron, Apolinario and Santana (2005), companies with more liquid
assets are likely to perform better as they are able to realize cash at any point of time
to meet its obligation and are less exposed to liquidity risks. By not having sufficient
cash or liquid assets, listed companies may be forced to sell investment securities at a
substantial loss in order to settle claims promptly. However, there are contrasting
views with regard to performance and liquidity in relation to the agency theory.
Kayo and Kimura (2010) argue that high liquidity could increase agency costs for
owners by providing managers with incentives to misuse excess cash-flows by
investing in projects with negative net present values and engaging in excessive
perquisite consumption. Liquidity measures the ability of managers to meet their
immediate commitments to shareholders and other creditors without having to
increase profit from investment activities and/or liquidate financial assets.
2.4 Empirical Review
This section discusses the empirical studies in relation to the two main variables of
this study which are financial leverage and profitability of listed firms. It consists of
both local and global studies as follows:
14
Abdussalam (2006) examined the relationship of firm structure and profitability. The
study considered major characteristics such as firm size, firm age, and debt ratio and
ownership structure of 48 Jordanian industrial companies listed in Amman Stock
Exchange for a period of one decade (1995 to 2004). The study employed two model
specifications in order to test the hypotheses, using the profitability measurement of
Rate of Return on Equity (ROE) and Rate of Return on Investment (ROI). The
empirical findings suggest that firm structure emerges as an important factor affecting
profitability. The results indicate that there was a positive relationship between firm
size and profitability.
Yuan and Kazuyuki (2011) carried out a study on the impact of the debt ratio on firm
investment. Using a sample of Chinese listed companies showed that total debt ratio
had a negative impact on fixed investment. A firm with a high debt ratio will channel
most of its income to debt repayments thereby forgoing investment using internal
funds. As more debt is employed in the capital structure of a firm, the business risk
also increases. Yuan and Kazuyuki argued that creditors will be reluctant to lend more
funds to a highly indebted firm which can result in underinvestment. Firm operations
will be affected if insufficient investment is undertaken.
Pouraghajan and Bagheri (2012) investigated on the impact of capital structure on the
financial performance of companies listed in the Tehran Stock Exchange. The study
tested a sample of 40 firms among the companies listed in the Tehran Stock
Exchange. Results suggest that there is a significant negative relationship between
debt ratio and financial performance of companies, and a significant positive
relationship between asset turnover, firm size, asset tangibility ratio, and growth
opportunities with financial performance measures.
15
Soumadi and Hayajneh (2012) studied the relationship between capital structure and
corporate performance on Jordanian shareholdings firms. The study used multiple
regression models by least squares (OLS) to establish the link between capital
structure and corporate performance of firms over a period of 5 years. The results
showed that capital structure was associated negatively and statistically with the
performance of the firms in the sample. Another finding from the study was that there
was no significant difference in the impact of financial leverage between high
financial leverage firms and low financial leverage firms in their performance. The
study also concluded that the relationship between capital structure and firm
performance was negative for both high growth firms and low growth firms.
Ahmad, Abdullar and Roslan (2012) carried a study in Malaysia which sought to
investigate the impact of capital structure on firm performance by analyzing
the relationship between return on assets (ROA), return on equity (ROE) and shortterm debt and total debt. The study established that short-term debt and long-term
debt had significant relationship with ROA. It was also established that ROE had
significant relationship with short-term debt, long-term debt and total debt.
Nduati (2010) examined the relationship between leverage and financial performance
of companies quoted at the Nairobi Securities Exchange. A descriptive research
design was adopted in the collection of data. Data was collected using interviews and
secondary sources such as annual financial reports of the targeted companies. Data
was analyzed using the Statistical Packages for Social Sciences (SPSS) and findings
presented in the form of pie charts, graphs and tables. The findings concluded that
leverage did not contribute to financial performance of firms quoted at the Nairobi
stock Exchange.
16
Adongo (2012) studied the effect of financial leverage on profitability and risk of
firms listed at the Nairobi securities exchange. A casual research design was adopted
for the study. Population consisted of fifty eight companies out of which thirty
companies were sampled. The sample excluded fifteen companies listed under banks
and insurance because these companies are regulated and are to meet certain liquidity
and leverage ratios. Six companies were suspended. The study covered a five year
period January 2007 to December 2011. Three companies were newly listed and
therefore not continuously listed over the period of study. Four companies had
information missing for some years required for the computation of the variables.
Secondary data was used and data was collected from thirty sampled firms. Source
data included NSE database, Capital Markets Authority (CMA) and Annual Audited
Financial Statements of sampled companies. Data was analyzed using Statistical
Packages for Social Sciences (SPSS) version 17. Cross-sectional time series fixed
model was used with the regression and correlation analysis to determine the nature
and the strength of the relationship between the independent and dependent variables.
The findings revealed an insignificant relationship between returns adjusted by risk
and financial leverage. This contradicted with the hypothesis of the study which had
predicted a positive relationship between financial leverage, profitability and risk of
listed firms.
Suhaila (2014) investigated the effect of liquidity and leverage on financial
performance of commercial state corporations in the tourism industry in Kenya. The
study adopted descriptive research design where data was retrieved from the Balance
Sheets, Income Statements and Notes of ten (10) Commercial State Corporations in
the tourism industry in Kenya during the study period 2008-2012. A regression
model was used to assess the impact of liquidity and leverage on financial
17
performance measured with profitability. A positive relationship was found to exist
between tourism industry liquidity and profitability of Commercial State Corporations
in the tourism sector in Kenya.
A study by Tale (2014) investigated on the relationship between capital structure and
financial performance of non-financial firms listed at the Nairobi securities exchange
in Kenya. The study used a descriptive survey. The population of the study consisted
of all the 40 nonfinancial firms listed and duly registered with capital market authority
of Kenya. Secondary data used was obtained mainly from the annual audited and
published books of accounts, financial statements and the NSE. Data analysis was
done by use of regression analysis model. However, the results showed that there was
a negative relationship between financial performance and the size and growth of the
firm.
Wainaina (2014) studied the relationship between leverage and financial performance
of top 100 small and medium enterprises in Kenya. The study used descriptive cross
sectional research design. The target population for the study was the top 100 SMEs
(2013) in Kenya. The study used a sample of 30 SMEs randomly selected from the
population of the study. The study collected secondary data for a period of five years
(2008-2012). The study made use of SPSS version 20, to aid in the analysis. The
study concluded that leverage had a significant influence on the financial
performance, and that there was a positive relationship between leverage (debt equity
ratio) and financial performance of small and medium enterprises in Kenya.
2.5 Summary of the Literature Review
From the above literature, studies have been carried out in relation to financial
leverage, capital structure, profitability and financial performance both in the local
18
and global setting. However, the empirical findings have found mixed results, for
example: Tale (2014) and Abdussalam (2006). The hypothesis for this study projects
a negative relationship between financial leverage and profitability of listed firms.
This is supported by the theories anchoring this study which are: Modigliani-Miller
theorem, Pecking Order Theory and Trade-off Theory. Most studies in the local
setting for example Adongo (2012) that have investigated the relationship between
financial leverage; profitability and financial performance in the context of listed
firms are inconclusive since they have relied on a sample to make generalization on
the findings. Secondly, most studies have tested the relationship between leverage
with financial performance and profitability which measures debt to equity ratio
unlike financial leverage which measures total debt. Thirdly, most studies have
ignored firm size as a key determinant of profitability which the current study has
factored in. This creates a need to investigate the relationship between financial
leverage and profitability of listed firms at the Nairobi Securities Exchange.
19
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Introduction
This chapter provides the research methodology that was used to achieve the objective
of the study. This chapter constitutes the research design, population, data collection,
analytical model, data analysis and the tests of significance.
3.2 Research Design
A descriptive research design was used. A descriptive research design is used to
establish the relationship between variables. According to Cooper and Schindler
(2006) a descriptive study is one that explains a phenomenon, to estimate a proportion
of a population with the same characteristics and to establish relationships that exist
between different variables. The study investigated the relationship between financial
leverage and profitability of listed firms at Nairobi securities exchange.
3.3 Population
Singh and Nath (2010) maintain that a population is the entire group of individuals,
events or objects having similar and observable characteristics. The population of this
study comprised of all the 64 firms listed at the Nairobi Securities Exchange.
Currently, there are 64 listed firms that are licensed to work and operate in Kenya
(NSE, 2014). The study considered firms that have been listed for the last five years
as the secondary data to be collected covered the period between years 2010-2014.
3.4 Data Collection
The study used secondary sources of data since the nature of data to be collected is
quantitative. The study covered a period of five years as from 2010-2014. This period
20
was considered sufficient for establishing the relationship that exists between the
variables. Secondary data was obtained from Nairobi Securities Exchange Handbook.
Secondary data was extracted from the financial statements of all the listed firms
based on the availability and accessibility of data in the period of study. Secondary
data selection and measurements was done based on the all variables under
investigation, namely; financial leverage, profitability, firm size and liquidity.
3.5 Data Analysis
Data was cleaned, sorted and then coded before being captured into the Statistical
Package for Social Sciences. Data was analyzed using descriptive statistics,
correlation analysis and regression analysis. The measurements that were analyzed
included: the financial leverage which is the independent variable. It was measured
using long-term liabilities divided by total assets. Profitability which is the dependent
variable was measured using Return on Assets (ROA). Control variables included the
firm size and liquidity which were measured using logarithm of total assets and
current assets divided by current liabilities.
3.5.1 Analytical Model
The study adopted a regression model to establish the relationship between financial
leverage and profitability of listed firms at Nairobi Securities Exchange. The study
projected a negative relationship between financial leverage and profitability of listed
firms at Nairobi Securities Exchange. The study sought to extend the model as
advanced by the previous works of Adongo (2012); the regression model was as
follows:
Y =β0 + β1X1 + β 2X2 + β 3X3 +e
b1 to bn are the regression coefficients
21
Y = profitability was measured using financial performance. This was measured
using return on assets (ROA) which is net income divided by total assets.
X1 is financial leverage (independent variable) which was measured using long-term
liabilities divided by total assets.
X2 is the size of the firm (control variable) which was measured using natural
logarithm of total assets.
X3 is Liquidity (control variable) which was measured using current assets divided by
current liabilities.
β0 = gradient or slope of the regression measuring the unit of change in y associated
with a unit change in X
ε is error term within a confidence interval of 5%
3.5.2 Tests of Significance
Model for coefficients was used to test the hypothesis of this study. The level of
significance was determined using probability values. If the p-value(s) is more than
5% then the null hypothesis is true since this means that there is no statistically
significant relationship between financial leverage and profitability of listed firms at
the Nairobi securities exchange. Similarly, if the p-value is less than 5% then the
alternative hypothesis was considered true since this means that there is a positive
relationship between variables. The coefficient of determination was used to
determine if the model is a satisfactory predictor or not using the R2. Correlation was
conducted to find out whether there is multi-colinearity between the variables. All the
tests were performed at 95% degree of confidence.
22
CHAPTER FOUR
DATA ANALYSIS, RESULTS AND DISCUSSION
4.1 Introduction
This section covers the analysis of data and findings of the study as set out in the
research objective and research methodology. The study findings are presented below
on the relationship between financial leverage and profitability of listed firms at the
Nairobi Securities Exchange. This study used secondary data that was extracted from
financial statements of listed firms.
4.2 Response Rate
Data was collected from 47 listed firms. This represents a response rate of 73% which
was considered sufficient for making generalization on the whole population. The
researcher managed to collect data from 47 listed firms although very few
measurements were missing on only specific variables. The study covered five years
(2010-2014). The findings have been presented in Appendix II.
4.3 Descriptive Statistics
Descriptive statistics have been used to show the summary of the relationship between
financial leverage and profitability of listed firms in the Nairobi Securities Exchange.
The findings show the mean, standard deviation, maximum and minimum values of
the variables under investigation as tabulated in table 4.1 below
23
Table 4.1 Descriptive Statistics
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Financial Leverage
235
.00
1.07
.4663
.20280
ROA
235
-.21
4.34
.1408
.38954
Liquidity
230
.00
18.76
1.7270
1.81492
Log ASSETS
235
.00
19.06
15.6151
1.99841
Valid N (listwise)
235
Source: Research Findings
From the findings in table 4.1 above, most listed firms utilized financial leverage in
the period of study. It was further observed that financial leverage increased rapidly
over the years from .00 to 1.07. The mean value for financial leverage is 0.4663 while
the standard deviation is .20280. This is an indication that most listed firms were
stable and thus were able to access financial leverage. The findings further revealed
that profitability was estimated at 1.4% which is a moderate performance. This is an
indication that financial leverage did not necessarily contribute to profitability of
listed firms. These findings are consistent with Padron and Santana (2005) who assert
that if a firm borrows more money from its creditors, then the firm has to pay more
amount of cost of debt to the creditor as interest. This leads to less net income for the
firm and hence lower profitability. This is consistent with the findings by Eunju and
SooCheong (2005) who concluded that there was an inverse relationship between
financial leverage and profitability of firms.
The level of liquidity of listed firms was found to be 1.73. This means that most listed
firms were able to meet their short-term financial obligations as and when they fell
due. This ratio (current ratio) is consistent with the standard conventional rule of
current ratios which is 2:1. This is the stipulated range upon which firms that seek to
maintain an optimal level of liquidity should meet.
24
The findings further revealed that most firms were financially stable in terms of assets
to access financial leverage. The percentage mean of logarithm of assets is 15.6%
which is a strong indicator that most listed firms had a strong asset base.
4.4 Pearson Product Moment Correlation Coefficient
The Pearson’s correlation is a measure of the strength and direction of association that
exits between two variables on at least an interval scale. Below are the results of the
findings presented in table 4.2.
Table 4.2 Pearson’s Correlation Analysis
ROA
Financial
Liquidity
Log of assets
Leverage
ROA
1
Financial Leverage
-.107
1
Liquidity
.212
-.305
1
Log of Assets
-.547
.218
-.209
1
Source: Research Findings
The strength of the association between the variables was specified by Pearson
correlation scale where: values between 0.0 to 0.3 indicate that there is no correlation,
between 0.31 to 0.5 shows a weak correlation, between 0.51 to 0.7 a moderate
correlation and between 0.71 to 1.0 indicates that there is a strong correlation between
the variables (Pearson and University of London, 1985).
The findings in table 4.2 above reveal that there was no correlation between financial
leverage and profitability of listed firms. The correlation which is represented by R is
-.107. The results also revealed that there was no correlation between liquidity and
profitability of listed firms. This is represented by a correlation of .212. Further, the
findings also indicated that there was a moderate correlation between logarithm of
25
assets and profitability of listed firms. The correlation score is -.547. This can be
attributed to the ability of listed firms to be able to access debt due to their level of
financial stability in terms of assets.
4.5 Regression Analysis and Hypothesis Testing
This study sought to establish the relationship that exists between financial leverage
and profitability of listed firms at Nairobi Securities Exchange. Regression analysis
was used to establish the hypothesis for the study which was predicted to be negative.
The results were as shown in table 4.3 below:
4.5.1 Model Summary
The model summary depicts the summary of the model. It consists of the multiple
correlation, the coefficient of determination and the adjusted R square. Below are the
results of the findings:
Table 4.3 Model Summary
Model Summary
Model
R
R Square
Adjusted R
Std. Error of the Estimate
Square
1
a
.524
.274
.263
.17417
a. Predictors: (Constant), Log Assets, Financial leverage, Liquidity
From the above results in table 4.3 , R which represents multiple correlation show a
moderately strong correlation between the variables as follows R=.524. R2 which is
the coefficient of determination show the extent to which the variance in the
dependent variable which is profitability can be explained by the independent
variables. This is represented by 27.4% which shows the regression model is a
moderate predictor.
26
4.5.2 Analysis of Variance
Analysis of variance was carried out to test the ‘goodness of fit’ for the data. A
regression model was used for this purpose and the results are tabulated in table 4.4
below.
Table 4.4 Analysis of Variance
ANOVAa
Model
1
Sum of Squares
df
Mean Square
F
Regression
4.116
3
1.372
Residual
7.086
226
.031
11.201
229
Total
Sig.
43.756
.000b
a. Dependent Variable: ROA
b. Predictors: (Constant), Log Assets, Financial Leverage, Liquidity
From the above results in table 4.4, the findings show that the probability value is
below 5%, p=0.000 which is an indication that the regression model is statistically
significant in predicting the relationship between financial leverage and profitability
of listed firms in Nairobi Securities Exchange.
4.5.3 Model Coefficients
The study tested the model coefficients to determine the direction of the variables in
the regression model. The results are provided in table 4.5 below.
Table 4.5 Model Coefficients
a
Coefficients
Unstandardized Coefficients
Model
B
1
Std. Error
(Constant)
-.172
.104
Liquidity
-.024
.007
Financial
Leverage
-.021
.043
Log Assets
a. Dependent Variable: ROA
27
Standardized
Coefficients
t
Sig.
Beta
-1.657
.099
-.215
-3.466
.001
.032
-.040
-.656
.512
.006
.428
6.829
.000
From the above findings, the regression model is as follows;
ROA= -.172-.024X1+.-021X2 + ε
Logarithm of assets was excluded from the regression model because it was found to
have a positive relationship with the profitability of listed firms. These findings
contradicted with the hypothesis of this study which had predicted an inverse
relationship between financial leverage and profitability of listed firms. From the
regression model obtained above, holding all the other factors constant, a unit increase
in liquidity and financial leverage, results to a corresponding decrease in ROA by 0.024 and -0.021. The regression model obtained shows an inverse relationship
between financial leverage and profitability of listed firms in the Nairobi Securities
Exchange.
The above analysis was conducted at 5% significance level. The criteria for
comparing whether the predictor variables were significant in the model was done by
comparing the corresponding probability value obtained; α=0.05. If the probability
value was less than α, then the predictor variable was significant. From the model
coefficients logarithm of assets and liquidity were found to be statistically significant
in the model. This is because its p-value was less than 5%. The results were as follows
p=0.000 and p=0.001. On the other hand, financial leverage was found to be
statistically insignificant with a probability (p)-value of 0.512 which was above 5%.
These findings are consistent to the hypothesis of the study which predicted the
existence of a statistically insignificant relationship between financial leverage and
profitability of listed firms at Nairobi Securities Exchange.
28
4.6 Discussion of Findings
The descriptive results found that most listed firms utilized financial leverage because
most listed firms had a stable asset base. However, the findings concluded that
financial leverage did not contribute to profitability of listed firms; the financial
performance of listed firms was 14% which is a moderate score.
The results of the Pearson’s correlation concluded that there was no correlation
between financial leverage and profitability of listed firms. The correlation score was
found to be R is -.107. Similarly, it was discovered that there was no correlation
between liquidity and profitability of listed firms. The correlation score was found to
be -.212. There was a moderate correlation between logarithm of assets and
profitability of listed firms. The correlation score is -.547.
The regression results found that there was an inverse relationship between financial
leverage and profitability of listed firms in the Nairobi Securities Exchange. Results
suggest that there is a significant negative relationship between debt ratio and
financial performance of companies. The findings depict that the logarithm of assets
and liquidity were found to be statistically significant in the model. This is because its
p-value was less than 5%. The results were as follows p=0.000 and p=0.001. On the
other hand, financial leverage was found to be statistically insignificant because its pvalue was above 5%. The result was as follows p=0.512.
29
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction
This chapter summarizes the study and provides the results and discussions drawn
from the analysis presented in chapter four. It captures the summary of findings,
conclusions, limitations as well as recommendations for further research.
5.2 Summary of Findings
The study investigated three dimensions of a firm’s profitability, namely, financial
leverage, firm size and liquidity. The descriptive results indicated that most listed
firms utilized financial leverage as most listed firms had a stable asset base. However,
the findings concluded that financial leverage did not contribute to profitability of
listed firms. The financial performance of listed firms was 14%, which is a moderate
score. This was an indication that financial leverage did not contribute to profitability
of listed firms. These findings are however consistent with Padron and Santana (2005)
who assert that if a firm borrows more money from its creditors then the firm has to
pay more amount of cost of debt to the creditor in terms of interest and this leads to
less net income for the firm and hence lower profitability.
The findings of the Pearson’s correlation concluded that there was no correlation
between financial leverage and profitability of listed firms. The correlation score was
found to be R is -.107. Similarly, it was discovered that there was no correlation
between liquidity and profitability of listed firms. The correlation score was found to
be -.212. These findings are consistent to a study by Yuan and Kazuyuki (2011) who
found that there was an inverse relationship between total debt and profitability of
Chinese listed companies. It was also found that there was a moderate correlation
30
between logarithm of assets and profitability of listed firms. The correlation score is .547.
The regression results found that there was an inverse relationship between financial
leverage and profitability of listed firms in the Nairobi Securities Exchange. These
findings are consistent with a study by Pouraghajan and Bagheri (2012) who
investigated the impact of capital structure on the financial performance of companies
listed in the Tehran Stock Exchange. Results suggest that there is a significant
negative relationship between debt ratio and financial performance of companies. The
findings depict that the logarithm of assets and liquidity were found to be statistically
significant in the model. This is because its p-value was less than 5%. The results
were as follows p=0.000 and p=0.001. These findings are consistent with Pouraghajan
and Bagheri (2012) who found that there was a statistically significant relationship
between asset turnover and liquidity of companies listed in the Tehran Stock
Exchange. On the other hand, financial leverage was found to be statistically
insignificant because its p-value at 0.512 was above 5%. These findings are consistent
with a study conducted by Nduati (2010) that examined the relationship between
leverage and financial performance of companies quoted at the Nairobi Securities
Exchange. The findings concluded that leverage did not contribute to financial
performance of firms quoted at the NSE. These findings are also consistent with
Adongo (2012) who studied the effect of financial leverage on profitability and risk of
firms listed at the Nairobi Securities Exchange. The findings concluded that there was
an insignificant relationship between returns adjusted by risk and financial leverage.
31
5.3 Conclusion
The findings revealed that profitability was not correlated with financial leverage of
listed firms in Kenya. The study therefore concludes that firms should consider
alternative methods of financing their projects other than relying on financial
leverage. Financial leverage might lead to poor performance of firms due to excessive
costs of financing debt that might override the returns obtained from investing in
projects.
The results of the model coefficients estimates of the independent variables found an
inverse relationship with profitability of listed firms. The results indicated that
liquidity and financial leverage depicted a negative relationship with profitability
apart from the logarithm of assets that showed a positive relationship with
profitability of listed firms in the Nairobi Securities Exchange. These findings are
consistent with the hypothesis of this study which predicted a negative relationship
between financial leverage and profitability of listed firms. It can therefore be
concluded that financing firms using debt is costly and might expose the firm to
financial difficulties.
From the regression model, the coefficient of determination was 27.4% showing the
extent to which the variance of profitability was explained by the independent
variables. This is an indication that the model used was a moderate predictor in
explaining the relationship between financial leverage and profitability of listed firms
in the Nairobi Securities Exchange.
5.3 Recommendations
The study recommends that listed firms should look for alternative ways of financing
their projects other than using financial leverage. This is because from the results
32
obtained it is evident that financial leverage does not contribute to profitability of the
firm. There is a proportionate increase in the cost of debt represented by the interest
rate payable to a firm’s borrowing. This leads to less net income for the firm and
hence lower profitability.
5.4 Limitations
One of the limitations of this study is that it utilized secondary data sources and might
not necessarily reflect the exact needs of the study. This might negatively affect the
accuracy and reliability of the results and impact negatively on the findings drawn in
this study.
Another limitation of this study is that it was limited to four variables only; financial
leverage, firm size, profitability and liquidity. It is imperative to note that profitability
is affected by many factors other than the ones confounders discussed in this study
that have a bearing on profitability. Other factors considered, it would be important to
establish whether the findings will hold or not after which conclusive results can be
drawn.
5.5 Suggestions for Further Research
Although the study targeted to study 64 firms, only 58 firms were active in the NSE
for the period under study. Due to time and cost constraints, only 47 firms were
investigated in the study. The study recommends that future researchers interested in
this field of research might consider investigating all the firms and increase the period
of study to ten years. This will increase the scope of study and the findings obtained
will be more conclusive. The results obtained can be compared with the findings
obtained in this study then conclusions can then be drawn based on more concrete
facts.
33
REFERENCES
Abdussalam, M. A. (2006). An empirical study of firm structure and profitability
relationship: The Case of Jordan, Journal of Economic and Administrative
Sciences, 22, 11, 41 – 59
Abor, J. & Biekpe, N. (2009). How do we explain the capital structure of SMEs in
sub-Saharan Africa, Evidence from Ghana, Journal of Economic Studies,
36(1), 83-97
Abor, J. (2005). The effect of capital structure on profitability: empirical analysis of
listed firms in Ghana, Journal of Risk Finance, 6(5), 438-445.
Adongo, J. (2012). The effect of financial leverage on profitability and risk of firms
listed at the Nairobi securities exchange, Unpublished MBA Project,
University of Nairobi
Adongo, J. (2012). The effect of financial leverage on profitability and risk of firms
listed at the Nairobi securities exchange, Unpublished MBA Project, School of
Business, University of Nairobi
Agrawal, A. & Nagarajan, N. J. (1990). Corporate capital structure, agency costs and
ownership control: the case of all equity firms, Journal of Finance, 45, 13251331.
Ahmad, Z., Abdullah, M.H. & Roslan, S. (2012). Capital Structure Effect on Firms
Performance: focusing on consumers and industrials sectors on Malaysian
firms. International Review of Business Research Papers, 8 (5), 137 – 155
Akhtar, et al., (2012). Relationship between financial leverage and financial
performance: evidence from fuel & energy sector of Pakistan, European
Journal of Business and Management, 4, 11, 2222-2839.
Akhtar, S., & Oliver, B. (2009). Determinants of capital structure for japanese
multinational and domestic corporations, International Review of Finance, 9,
1-26.
Al-Najjar, B. (2011). The inter-relationship between capital structure and dividend
policy: empirical evidence from Jordanian data, International Review of
Applied Economics, 25 (2), 209-224.
Al-Najjar, B., & Taylor, P. (2008). The relationship between capital structure and
ownership structure: new evidence from Jordanian panel data, Managerial
Finance, 34 (12), 919-933.
Al-Sakran S.A. (2001). Leverage determinants in the absence of corporate tax system:
the case of non-financial publicly traded corporations in Saudi Arabia,
Managerial Finance, 27, 58-86.
34
Amalendu, B. (2012). Leverage impact on firms investment decision: a case study of
Indian pharmaceutical companies, International Journal of Contemporary
Business Studies, 3, 1, 35-45.
Baskin, J. (2002). An empirical investigation of the pecking order hypothesis,
Financial Management, 18, 26-34.
Cheng, C. & Tzeng, C. (2010). The Effect of leverage on firm value and how the firm
financial quality influences on this effect, National Chung Cheng University,
Taiwan.7.
Cooper, D. R., & Schindler, P. S. (2008). Business research methods. Boston:
McGraw-Hill Irwin.
Daskalakis, N, & Psillaki, M. (2008). Firm factors explain capital structure, Evidence
from SMEs in France and Greece, Applied Financial Economics, 18, 87-97
Dittmar, A. (2004). Capital structure in corporate spin‐offs, Journal of Business, 77 1,
9‐43.
Eunju, Y. & SooCheong, J. (2005). The effect of financial leverage on profitability
and risk of restaurant firms, The Journal of Hospitality Financial
Managements, 13,200-210
Fama, E. & French, K. (2002). Testing tradeoff and pecking order predictions about
dividends and debt, Review of Financial Studies, 15, 1-37,
Frank, M. Z., & Goyal, V. K. (2011). Trade-off and pecking order theories of debt,
handbook of empirical corporate finance: Empirical Corporate Finance.
Elsevier, 135–202
Gu, Z. (1993). Debt use and profitability: A reality check for the restaurant industry,
Journal of finance and accounting, 7, 135-147.
Harris, M. & Raviv, A. (2003). Capital structure and the informational role of debt,
Journal of Finance, 45 (2), 321-349.
Hussain J. & Matlay H. (2007). Financing preferences of ethnic minority owner and
managers in the UK, Journal of Small Business and Enterprise Development,
14(3), 487-500.
Kale, A. (2014). The impact of financial leverage on firm performance: the case of
non-financial firms in Kenya, Unpublished MBA Project, University of
Nairobi
Kayo, E.K. & Kimura, H. (2010). Hierarchical determinants of capital structure,
Journal of Banking & Finance, 35, 358-371.
35
Kraus, A. & Litzenberger, R.H. (1973). A state-preference model of optimal financial
leverage, Journal of Finance, 7, 911-922.
Mahira, R. (2011). Effect of profitability & financial leverage on capital structure: a
case of Pakistan’s automobile industry, Economics and Finance Review,
1(4)50 – 58,
Miller, M. H. (1977). Debt and taxes, Journal of Finance 32 (2), 261–275.
Modigliani, F. & Miller M.H. (1958). The cost of capital, corporation finance and the
theory of investment, American Economic, 48 (3), 261-297.
Modigliani, F. & Miller M.H. (1963). Corporate income taxes and the cost of capital:
a correction, American Economic Review, 53,433-443.
Myers S.C. (2001). Testing static tradeoff against pecking-order model of capital
structure, Journal of Financial Economic, 51 (2), 219-245.
Myers, S. C. & Majluf, N.S. (1984). Corporate financing and investment decisions
when firms have information that investors do not have, Journal of Financial
Economics, 13 (2), 187–221.
Myers, S.C. (1982). Determinants of capital borrowing, Journal of Finance
Economics, 5, 5147-5175.
Myers, S.C. (1984). The capital structure puzzle, The Journal of Finance, 39, 3,
Papers and Proceedings, Forty-Second Annual Meeting, American Finance
Association, 575-592
Myers, S.C. (1994). The capital structure puzzle, Journal of Finance, 39,575-592.
Nduati, M. (2010). The relationship between leverage and financial performance of
companies quoted at the Nairobi stock exchange, Unpublished MBA Project,
University of Nairobi
Padron, Y.G., Apolinario, M.C., & Santana, O. (2005). Determinant factors of
leverage: An empirical analysis of Spanish corporations, Journal of Risk
Management, 6, 60-68.
Pearson, K., & University of London. (1985). On further methods of determining
correlation. London: Cambridge University Press.
Pouraghajan, A., & Bagheri, M. (2012). The Relationship between capital structure
and firm performance evaluation measures: Evidence from the Tehran Stock
Exchange, International Journal of Business and Commerce, 1(9): 166-181.
Singh, Y. K., & Nath, R. (2010). Research methodology. New Delhi: Publishing
Corporation
36
Soumadi, M. & Hayajneh, S. (2012). Capital structure and corporate performance:
Empirical study on the public Jordanian shareholdings firms listed in the
Amman stock market, European Scientific Journal, 8(26), 173-189.
Subaii, B. (2012). The relationship between financial leverage and return on
investment in Kuwaiti public shareholding companies, Master Thesis, Middle
East University, Amman Jordan
Suhaila, A. M. (2014). The effect of liquidity and leverage on financial performance
of commercial state corporation sin the tourism industry in Kenya,
Unpublished MBA Project, School of Business, University of Nairobi
Tale, W. (2014). Relationship between capital structure and performance of nonfinancial firms listed at the Nairobi securities exchange, Unpublished MBA
Project, University of Nairobi
Upneja, A & Dalbor, M. C. (2001). An examination of capital structure in the service
industry, Journal of finance and Accounting, 13(2), 54-59.
Vasiliou, D., Eriotis, N. & Daskalakis, N. (2009). Testing the pecking order theory:
the importance of methodology, Qualitative Research in Financial, 1(2), 8596.
Wainaina, J. N. (2014). The relationship between leverage and financial performance
of top 100 small and medium enterprises in Kenya, Unpublished MBA Project,
School of Business, University of Nairobi
Wald, J. K. (1999). How firm characteristics affect capital structure: an international
comparison, Journal of Financial research, 22(2), 161-188
Wald, J. K. (2000). How firm characteristics affect capital structure: an international
comparison, Journal of Financial research, 24(2), 217-218
Welch, I. (2004). Capital structure and stock returns, Journal of Political Economy
112 (1): 106–132.
Yuan, K. & Kazuyuki, H. (2011). Impact of the Debt Ratio on Firm Investment: A
case study of listed companies in China, RIETI Discussion Paper Series, 08-E011.
37
APPENDIX I: LIST OF FIRMS LISTED AT NSE (2014)
AGRICULTURAL
Eaagads Ltd
Kakuzi Ltd
Kapchorua Tea Co. Ltd
The Limuru Tea Co. Ltd
Rea Vipingo Plantations Ltd
Sasini Ltd
Williamson Tea Kenya Ltd
AUTOMOBILES & ACCESSORIES
Car & General (K) Ltd
Marshalls (E.A.) Ltd
Sameer Africa Ltd
BANKING
Barclays Bank of Kenya Ltd
CFC Stanbic of Kenya Holdings Ltd
Diamond Trust Bank Kenya Ltd
Equity Bank Ltd
Housing Finance Co.Kenya Ltd
I&M Holdings Ltd
Kenya Commercial Bank Ltd
National Bank of Kenya Ltd
NIC Bank Ltd
Standard Chartered Bank Kenya Ltd
The Co-operative Bank of Kenya Ltd
COMMERCIAL AND SERVICES
Express Kenya Ltd
Hutchings Biemer Ltd
Kenya Airways Ltd
Longhorn Kenya Ltd
38
Nation Media Group Ltd
Scangroup Ltd
Standard Group Ltd
TPS Eastern Africa Ltd
Uchumi Supermarket Ltd
CONSTRUCTION & ALLIED
ARM Cement Ltd
Bamburi Cement Ltd
Crown Paints Kenya Ltd
E.A.Cables Ltd
E.A.Portland Cement Co. Ltd
ENERGY & PETROLEUM
KenGen Co. Ltd
KenolKobil Ltd
Kenya Power & Lighting Co Ltd
Kenya Power & Lighting Ltd 4% Pref 20.00
Kenya Power & Lighting Ltd 7% Pref 20.00
Total Kenya Ltd
Umeme Ltd
INSURANCE
British-American Investments Co.(Kenya) Ltd
CIC Insurance Group Ltd
Jubilee Holdings Ltd
Kenya Re Insurance Corporation Ltd
Liberty Kenya Holdings Ltd
Pan Africa Insurance Holdings Ltd
INVESTMENT
Centum Investment Co Ltd
Olympia Capital Holdings Ltd
39
Trans-Century Ltd
INVESTMENT SERVICES
Nairobi Securities Exchange Ltd Ord 4.00
MANUFACTURING & ALLIED
A.Baumann & Co Ltd
B.O.C Kenya Ltd
British American Tobacco Kenya Ltd
Carbacid Investments Ltd
East African Breweries Ltd
Eveready East Africa Ltd
Kenya Orchards Ltd
Mumias Sugar Co. Ltd
Unga Group Ltd
TELECOMMUNICATION & TECHNOLOGY
Safaricom Ltd
GROWTH ENTERPRISE MARKET SEGMENT (GEMS)
Flame Tree Group Holdings Ltd Ord 0.825
Home Afrika Ltd
40
APPENDIX II: SECONDARY DATA OF LISTED FIRMS
EXTRACTED FROM AUDITED REPORTS
KAKUZI - 1
Financial Leverage
effect(TL/TA)
2010
2011
2012
2013
2014
0.34
0.31
0.28
0.22
0.22
Liquidity
1.02
0.89
1.19
0.851
0.82
0.12766003
0.0412346
0.33035058
0.15361
0.361367
14.87
14.98
15.16
15.09
15.13
EAAGADS - 02
Financial Leverage
effect(TL/TA)
0.25
0.3
0.25
0.16
0.2
Liquidity
2.73
1.81
1.21
1.15
1.12
0.13931136
0.1376066
0.05629291
0.013908
0.038333
12.47
12.53
12.78
13.26
13.12
KAPCHORUA TEA - 03
Financial Leverage
effect(TL/TA)
0.41
0.45
0.38
0.42
0.38
Liquidity
1.68
1.64
2.1
1.65
2.12
1.01068056
4.340312
0.16021744
0.318189
0.038333
13.97
14.22
14.27
14.49
14.55
LIMURU TEA-04
Financial Leverage
effect(TL/TA)
0.34
0.25
0.22
0.24
0.16
Liquidity
2.34
2.34
6.7
5.94
18.76
0.07376946
0.1052401
0.14861985
0.038031
0.171714
11.35
11.97
12.16
12.68
13.26
REA VIPINGO - 05
Financial Leverage
effect(TL/TA)
0.31
0.42
0.36
0.28
0.25
Liquidity
2.24
1.34
2.1
3.41
4.71
0.06411035
0.2417681
0.0511335
0.039721
0.011016
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
14.16
14.35
14.64
14.68
14.84
SASINI - 06
Financial Leverage
effect(TL/TA)
Firm size effect(LNTA)
0.29
0.28
0.29
0.28
0.3
Liquidity
2.56
2.37
2.13
1.89
1.77
0.03506332
0.1418446
0.22574588
0.117973
0.106374
15.89
16.02
16.06
16
16.02
0.33
0.35
0.29
0.32
0.27
ROA(NI/TA)
Firm size effect(LNTA)
WILLIAMSON - 07
Financial Leverage
effect(TL/TA)
Liquidity
ROA(NI/TA)
Firm size effect(LNTA)
2.74
2.03
3.38
2.41
3.63
0.06520726
0.0085179
0.04709468
0.202253
0.054975
15.18
15.49
15.61
15.8
15.9
41
CAR&GENERAL - 08
Financial Leverage
effect(TL/TA)
0.59
0.6
0.65
0.62
0.64
1.3
1.31
1.12
1.16
1.11
0.07583452
0.0897654
0.045673
0.08605
0.038333
Firm size effect(LNTA)
14.98
15.17
15.53
15.56
15.75
CMC HOLDINGS - 09
Financial Leverage
effect(TL/TA)
0.6
0.63
0.65
0.56
0.53
0.93
1.03
1.53
1.05
0.95
0.10877572
0.0918055
0.05885937
0.081555
0.036607
Firm size effect(LNTA)
16.4
16.5
16.5
16.38
16.32
MARSHALLS E.A. - 10
Financial Leverage
effect(TL/TA)
0.67
0.88
0.63
0.31
0.45
Liquidity
1.83
2.78
2.91
1.94
0.82
0.10877572
0.0918055
0.05885937
0.081555
0.036607
14.18
13.93
13.89
13.25
13.15
0.24
0.28
0.32
0.27
Liquidity
ROA(NI/TA)
Liquidity
ROA(NI/TA)
ROA(NI/TA)
Firm size effect(LNTA)
SAMEER GROUP - 11
Financial Leverage
effect(TL/TA)
Liquidity
1.4
0.92
0.94
0.84
0.0980098
0.10425597
0.066812
0.095582
14.92
14.86
14.95
15.04
15.12
EXPRESS KENYA LTD - 12
Financial Leverage
effect(TL/TA)
0.68
0.71
0.46
0.6
0.59
Liquidity
0.83
0.93
0.86
1.27
1.25
0.07717125
0.093799
0.54786
-0.10948
-0.20948
14.08
14.11
13.55
13.11
13.08
KQ - 13
Financial Leverage
effect(TL/TA)
0.77
0.73
0.71
0.7
0.75
Liquidity
1.49
2.01
1.42
1.24
1.33
0.07526565
0.0424968
0.05473956
0.052365
0.038333
18.13
18.11
18.18
18.16
18.63
LONGHORN - 14
Financial Leverage
effect(TL/TA)
0.34
0.43
0.43
0.6
0.44
Liquidity
1.91
1.54
1.98
0.89
0.93
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
0.07965084
0.0535708
0.28445326
0.021438
0.038333
Firm size effect(LNTA)
12.97
13.17
13.47
13.4
13.44
NATION MEDIA - 15
Financial Leverage
effect(TL/TA)
0.28
0.32
0.31
0.31
0.28
Liquidity
1.01
1.05
0.92
0.91
0.81
0.19058894
0.2679858
0.17894718
0.036336
0.061016
15.7
15.89
15.99
16.18
16.25
ROA(NI/TA)
Firm size effect(LNTA)
42
SCAN GROUP - 16
Financial Leverage
effect(TL/TA)
0.4
0.55
0.49
0.43
0.36
0.92
2.02
1.84
0.84
1.03
0.05381389
0.0281204
0.02403531
0.045591
0.069792
15.18
15.9
15.95
15.94
16.36
STANDARD GROUP - 17
Financial Leverage
effect(TL/TA)
0.58
0.54
0.53
0.47
0.51
Liquidity
1.05
1.22
1.19
2.01
1.17
0.08092432
0.0617275
0.22112635
0.235104
0.047772
14.92
15.01
15.07
15.07
15.24
TPS SERENA GROUP - 18
Financial Leverage
effect(TL/TA)
0.42
0.37
0.39
0.39
0.32
Liquidity
1.28
1.23
2.01
1.24
0.98
0.08092432
0.0617275
0.22112635
0.235104
0.047772
15.76
16.29
16.39
16.42
16.6
1.07
0.51
0.43
0.46
0.48
Liquidity
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
UCHUMI - 19
Financial Leverage
effect(TL/TE)
Liquidity
1.34
0.92
0.85
0.92
0.74
0.07526565
0.0424968
0.05473956
0.052365
0.038333
14.71
14.96
15.2
15.41
15.53
ATHI RIVER MINING - 20
Financial Leverage
effect(TL/TA)
0.66
0.7
0.7
0.74
0.72
Liquidity
1.38
1.51
1.49
1.49
1.08
ROA(NI/TA)
0.151
-0.02
0
-0.07
0.15
Firm size effect(LNTA)
16.31
16.62
16.84
17.11
17.21
BAMBURI - 21
Financial Leverage
effect(TL/TA)
0.35
0.35
0.28
0.28
0.27
Liquidity
1.19
1.13
2.01
0.92
0.83
0
0.222218008
0.113434639
0.085387
0.095216
Firm size effect(LNTA)
17.28
17.32
17.33
17.58
17.58
CROWN PAINTS - 22
Financial Leverage
effect(TL/TA)
0.55
0.54
0.52
0.48
0.54
Liquidity
0.75
0.78
0.94
0.92
0.61
0.046440801
0.046349584
0.058230927
0.059135
0.072602
14.44
14.49
14.61
14.63
14.9
EAST AFRICAN CABLES - 23
Financial Leverage
effect(TL/TA)
0.53
0.5
0.54
0.53
0.55
Liquidity
1.25
1.79
1.83
1.63
1.85
0.083545301
0.040688777
0.063033844
0.083548
0.091756
15.08
15.32
15.42
15.65
15.73
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
43
EAST AFRICAN PORTLAND - 24
Financial Leverage
effect(TL/TA)
0.49
0.53
0.58
0.67
0.56
Liquidity
1.37
2.01
1.43
2.01
1.35
0.15238116
0.032655358
0.017843436
0
0.065922
Firm size effect(LNTA)
16.3
16.3
16.41
16.45
16.6
KENGEN - 25
Financial Leverage
effect(TL/TA)
0.41
0.53
0.57
0.57
0.61
Liquidity
1.56
1.49
1.05
1.48
1.51
0.018335553
0.021827426
0.01292055
0.017301
0.027827
18.54
18.83
18.9
18.91
19.06
KENOL/KOBIL - 26
Financial Leverage
effect(TL/TA)
0.67
0.63
0.75
0.8
0.76
Liquidity
1.81
1.62
0.98
1.03
2.01
0.09680441
0.0264158
-0.0291893
0.060904
0.016998
Firm size effect(LNTA)
17.2
17.23
17.64
17.3
17.15
KPLC - 27
Financial Leverage
effect(TL/TA)
0.62
0.64
0.67
0.68
0.73
ROA(NI/TA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Liquidity
1.37
1.41
1.42
1.44
0.51
0.018335553
0.021827426
0.01292055
0.017301
0.027827
18.09
18.2
18.6
18.71
18.99
TOTAL KENYA - 28
Financial Leverage
effect(TL/TA)
0.72
0.68
0.74
0.57
0.62
Liquidity
1.12
1.17
1.1
1.29
1
ROA(NI/TA)
0.02
0.03
0
-0.01
0.03
17.27
17.23
17.38
17.31
17.5
CENTUM - 29
Financial Leverage
effect(TL/TA)
0.04
0.05
0.22
0.13
0.28
Liquidity
1.25
0.09
0.23
0.33
0.2
0.11968666
0.1654789
0.1406176
0.046215
0.222479
Firm size effect(LNTA)
15.7
15.93
16.33
16.26
16.76
OLYMPIA - 30
Financial Leverage
effect(TL/TA)
0.29
0.39
0.4
0.43
0.43
Liquidity
1.14
1.48
1.16
2.27
2.79
ROA(NI/TA)
Firm size effect(LNTA)
Firm size effect(LNTA)
ROA(NI/TA)
ROA(NI/TA)
1.09034822
1.7388818
2.79678248
0.117786
0.038333
Firm size effect(LNTA)
13.58
13.79
13.89
14.44
14.46
TRANSCENTURY- 31
Financial Leverage
effect(TL/TA)
0.6
0.53
0.7
0.66
0.66
Liquidity
1.8
1.59
1.22
1.28
1.49
0.14606199
0.2729494
0.23476437
0.099206
0.103232
15.98
16.23
16.93
16.9
16.99
ROA(NI/TA)
Firm size effect(LNTA)
44
NSE-32
Financial Leverage
effect(TL/TA)
0.13
0.15
0.1
0.44
0.36
Liquidity
1.92
0.854
2.05
1.99
1.46
0.20033039
0.1667232
0.16333995
0.03455
0.124608
12.62
12.91
13.07
13.69
13.95
BOC KENYA-33
Financial Leverage
effect(TL/TA)
0.24
0.26
0.27
0.27
0.21
Liquidity
2.64
2.48
1.94
2.08
2.23
0.077402395
0.039279437
0.082895063
0.099206
0.076957
14.44
14.46
14.41
14.51
14.78
BAT-34
Financial Leverage
effect(TL/TA)
0.56
0.54
0.53
0.53
0.55
Liquidity
0.98
1.17
1.31
1.18
1.26
0.140093067
0.158901794
0.225282343
0.24616
0.219222
16.17
16.22
16.44
16.54
16.65
0.15
0.14
0.16
0.18
0.13
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
CARBACID-35
Financial Leverage
effect(TL/TA)
Liquidity
10.63
5.79
8.84
4.26
10.09
0.186269054
0.20327927
0.173676785
0.193404
0.215724
14.13
14.23
14.37
14.52
14.61
EABL-36
Financial Leverage
effect(TL/TA)
0.35
0.38
0.46
0.84
0.86
Liquidity
1.69
1.49
1.05
0.81
0.7
0.02682845
0.0143603
0.15530312
0.409461
0.026276
17.39
17.46
17.72
17.82
17.89
0.6
0.66
0.73
0.7
0.58
1.02
1.01
1
1
0.96
0.5
0.5
0.5
0.6
0.7
ROA(NI/TA)
Firm size effect(LNTA)
ROA(NI/TA)
Firm size effect(LNTA)
EVEREADY-37
Financial Leverage
effect(TL/TA)
Liquidity
ROA(NI/TA)
Firm size effect(LNTA)
KENYA ORCHARDS-38
Financial Leverage
effect(TL/TA)
Liquidity
ROA(NI/TA)
-0.02
-0.01
0
0
0.04
Firm size effect(LNTA)
18.18
18.13
18.07
18.05
18.07
0.38
0.43
0.51
2
1.25
0.84
0.02166631
0.083548
0.048276
16.95
17.13
17.12
MUMIAS-39
Financial Leverage
effect(TL/TA)
Liquidity
ROA(NI/TA)
Firm size effect(LNTA)
45
UNGA LTD-40
Financial Leverage
effect(TL/TA)
0.43
0.34
0.34
0.38
0.47
Liquidity
1.84
2.36
2.52
2.54
1.84
0.14964667
0.0823855
0.22545921
0.348471
-0.08312
15.53
15.44
15.56
15.67
15.91
0.44
0.4
0.41
0.41
0.38
0.911
0.69
0.69
0.91
0.6
0.10685473
0.0934247
0.08246009
0.026287
0.190102
18.33
18.46
18.55
18.62
18.67
0.82
0.51
0.82
0.83
0.84
1.117
1
1
1
1
0.036943139
0.06147377
0.048572404
0.047293
0.036873
24
26
26
26
26
Total Debt
0.86
0.87
0.88
0.85
0.84
Liquidity
1.16
1.15
1.14
1.17
1.19
0.026816531
0.029674936
0.031881268
0.038507
0.039393
18.52
18.85
18.94
19.12
19.26
Total Debt
0.88
0.88
0.89
0.86
0.86
Liquidity
1.14
1.14
1.14
1.16
1.166
0.020312743
0.029690966
0.027807955
0.030031
0.031412
18.01
18.24
18.49
18.72
18.93
Total Debt
0.77
0.82
0.83
0.82
0.81
Liquidity
2.29
1.23
1.21
1.21
1.22
0.041998953
0.049863089
0.0526005
0.049678
0.047808
25.33
25.69
26
26.21
26
0.85
0.85
0.87
0.87
1.17
1.14
1.14
ROA(NI/TA)
Firm size effect(LNTA)
SAFARICOM-41
Financial Leverage
effect(TL/TA)
Liquidity
ROA(NI/TA)
Firm size effect(LNTA)
Barclays Bank-42
Total Debt
Liquidity
ROA
Size
Cooperative Bank-43
ROA
Size
Diamond Trust Bank-44
ROA
Size
Equity-45
ROA
Size
HFCK-46
Total Debt
0.78
Liquidity
1.29
ROA
1,17
0.012839048
0.012962834
0.019524949
0.018149
0.021
23
24
24
24
24
KENYA REINSURANCE CORPORATION-47
Total Debt
0.61
0.61
0.61
0.38
0.64
Liquidity
1.64
1.63
1.65
2.61
1.57
0.088589862
0.089403013
0.100258682
0.117786
0.106313
23
23
23
23
24
Size
ROA
Size
46
Source: (NSE, 2015)
47