Leverage's Impact on BSRM STEEL's Financial Performance

Leverage Effect On The Financial Performance Of BSRM
STEEL LTD.
DISSERTATION
Submitted to the Center for Business Administration (CBA) of Chittagong
University for the completion of MBA
Supervised By
Dr. Harunur Rashid
Professor of Accounting and Information System
University of Chittagong
Submitted By
Hasan Ullah Chowdhury
ID: 1404023
Batch: 4th
(BG)
Major: Accounting
CU-CBA, University of Chittagong
Chittagong, Bangladesh
10th
August, 2016

ii
Date: 10/08/2016
To
Professor Dr. Harunur Rashid
Accounting and Information System
CU-CBA, University of Chittagong
Sub: Submission of Dissertation Report
Dear Sir,
I am submitting my Dissertation Report regarding “The leverage effect on the financial
performance of BSRM STEEL LTD” as a part of the requirement of the completion of MBA
program. Your guidelines have been followed in every aspect in preparing this report. I have
really enjoyed working on this report and I hope that my work would meet the level of your
expectation.
I would be highly encouraged if you are kind enough to receive my Report. If you have any
further enquiry concerning any additional information, I would be very pleased to clarify that.
Thanking you
Sincerely yours
_______________
Hasan Ullah Chowdhury
ID: 1404023
Major: Accounting
Batch: 4th
(BG)

iii
AL-Hamdu-Lillah, at first, I would like to thank to Almighty Allah who give me strength and
showered me with endless Rahma for completion of the study.
I would like to show heart-felt gratitude to my honorable supervisor and most respected teacher
Professor Dr. Harunur Rashid for his sincere help, constant encouragement and guidance from
the very inception to the completion of this research work. Without whose invaluable
suggestions, it would not have been possible to complete the study.
I am grateful to all my teachers who teach and train me from the beginning of my learning to
now.
I would like to thank my mother, brother, and friends who support and inspired me in
completing this study.
I would like to thank to all the concerned researchers, authors whom articles, books guide me
in the proper directions.
(Hasan Ullah Chowdhury)
10th August, 2016

iv
This report is the outcome of the study “Leverage effect on the financial performance of BSRM
STEEL LTD” during the period 2010 to 2015 with the objectives of determining the
relationship between Leverage and Financial Performance (GPM, OPM, NPM, ROE, EPS),
and determining the impact of it on those performances.
This paper studies the effect of leverage on the financial performance of BSRM STEEL LTD
that covers the six-year data from 2010 to 2015. Twelve null hypotheses are developed for the
study. Financial leverage (independent variable) and the financial performance indicators
(dependent variable) like GPM, OPM, NPM, ROE, ROA, EPS are used in this study as an
input. Descriptive Statistics, Correlation Analysis, and Regression Analysis are used to test the
hypotheses.
The study reveals that there is no statistically significant relationship of leverage with the
financial performance (GPM, OPM, NPM, ROE, EPS) and no statistically significant impact
of leverage on that financial performance.
Although no significant impact or relationship is found, it does not mean that there is no impact
or relationship at all. The study reveals that the leverage has negative relationship with GPM,
OPM, NPM, ROA, EPS but positive relationship with ROE. The study also reveals that the
company is a highly levered company since it uses highest level of debt against equity in its
capital structure. The major sources of capital of it is debt, specifically short term borrowings
that indicates the short term financial risks.
In addition, the study reveals that 2013 and 2015 are the successful year for the BSRM STEEL
LTD. In these years the company expand its sales and increases profits by managing costs and
debt well. In these year the company use the right mix of debt and equity. The success of
company in these years is due to expansion in plant capacity, employing more experts, great
marketing strategies, etc.
Finally, this report ends with certain recommendations, based on findings, in which it is
suggested to the management of the BSRM STEEL LTD (1) to use the right mix of debt and
equity after analyzing the cost and benefit of the capital structure and (2) to diversify the
business in order to minimize the risks.

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Chapter 1: Introduction
1.1 Introduction ....................................................................................................................................2
1.2 Statement of the problem...............................................................................................................2
1.3 Research Objectives........................................................................................................................2
1.3.1.General Objectives ............................................................................................................2
1.3.2.Specific Objective ..............................................................................................................3
1.4 Research Questions.........................................................................................................................3
1.5 Research Hypothesis.......................................................................................................................3
1.6 Significance of the study .................................................................................................................4
Chapter 2: Literature Review
2.1. Introduction ....................................................................................................................................6
2.2. Earlier studies regarding the effect of leverage on firm’s financial performance ...........................6
2.3. Earlier studies regarding the measures of leverage........................................................................7
2.4. Earlier Studies regarding the factors affecting firm’s performance ................................................7
Chapter 3: Research Design and Methodology
3.1. Introduction ....................................................................................................................................9
3.2. Research Design Plan ......................................................................................................................9
3.3. Selection of Variables......................................................................................................................9
3.4. Research Model ............................................................................................................................10
3.5. Sources of Data .............................................................................................................................11
3.6. Data Analysis Tools & Technique: .................................................................................................11
3.6.1.Techniques used for Hypothesis Testing.........................................................................11
3.6.2.Software used for data processing..................................................................................11
Chapter 4: Profile of BSRM STEEL LTD.
4.1. Introduction ..................................................................................................................................13
4.2. BSRM STEEL LTD from 1952 to 2015.............................................................................................13
Chapter 5: Data Analysis and Interpretations
5.1. Introduction ..................................................................................................................................16
5.2. BSRM’s Financial Performance & Financial Position over Six years...............................................16
5.3. BSRM’s Level of Leverage and Financial Performance..................................................................17
5.3.1.Capital Structure..............................................................................................................17

vi
5.3.2.Leverage Level.................................................................................................................18
5.3.2.1.Overall Leverage Level........................................................................................18
5.3.2.2.Specific Leverage Level.......................................................................................19
5.3.3.Level of Financial Performance Indicators.......................................................................21
5.3.4.Borrowings and Financial Performance Indicators..........................................................23
5.4. Hypothesis Testing and Interpretation..........................................................................................24
5.4.1.Summary of the Variables’ Data......................................................................................25
5.4.2.Descriptive Statistics and Interpretation.........................................................................25
5.4.3.Correlation Analysis and Interpretation ..........................................................................26
5.4.4.Regression Analysis and Interpretation...........................................................................27
5.5. Summary of Hypothesis testing ....................................................................................................30
Chapter 6: Findings, Recommendation, Limitations, and Conclusions
6.1. Introduction ..................................................................................................................................32
6.2. Research Findings..........................................................................................................................32
6.3. Recommendations ........................................................................................................................32
6.4. Limitations of the study.................................................................................................................33
6.5. Conclusions ...................................................................................................................................33
..........................................................................................................................................34
...................................................................................35

CHAPTER 1: INTRODUCTION
1.1 Introduction
1.2 Statement of the problem
1.3 Research Objectives
1.3.1 General Objectives
1.3.2 Specific Objective
1.4 Research Questions
1.5 Research Hypothesis
1.6 Significance of the study

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Capital structure decision is a crucial decision of every listed companies in every country.
Capital structure indicates what type of sources a company will use to raise capital: Will the
company use debt (i.e. leverage) or equity, or mix of both?
Leverage is an ingredient of capital structure. It refers to the use of debt (loans, debenture, etc.)
to boost the earnings of shareholders. The company can get benefits by using it. One of the
most benefit is tax advantage and high returns. Because using leverage will increase returns
and reduce tax.
Although using leverage as a source of financing has some advantages, it can produce some
drawbacks. The ROI after using it must be greater than cost of debt. If not the company will
not be able to pay the periodic interest payment. Again high leverage means high risks. The
investors will not be interested in investing because of fear of losing investment.
So, it is seen that research on leverage effect is a crucial aspect for every company. In this paper
I tried to show the consequences of using leverage of BSRM STEEL LTD for gathering its
capital. I also tried to show the relations between leverage and some financial performance
indicators.
One of the most crucial sources of financing used by the companies both in Bangladesh and
abroad is debt. Leverage will increase the financial performance if it is handled efficiently and
effectively and if not the company has to face the severe consequences.
High leverage meaning high returns is not always true because of high risks. Use of leverage
increases the cost of debt (i.e. interest payment) and may lead to losing profits. The company
may face losing profits, reduce in EPS, losing investors, and bankruptcy, and many more
consequences.
Therefore, it is required to know the effect of using leverage on financial performance before
it is used. After knowing the effect, the company can take better decisions for its capital
structure.
But, a few researches are found regarding the effect of leverage on the financial performance.
Although some are found, they are not enough for knowing the effect and they are based on
foreign country. Uses of leverage depends on the economic condition of a country. Therefore,
due to the research gap, I have made an effort on studying the effect of leverage and tried to
determine the relationship and impact of leverage with and on financial performance.
The objective of the study is divided into two parts:
The main objective of this study is to assess the impact of leverage on the financial performance
of BSRM STEEL Ltd.

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To accomplish the general objective, the following specific objectives have covered:
 To determine the positive or negative relationship between leverage and GPM
 To determine the positive or negative relationship between leverage and OPM
 To determine the positive or negative relationship between leverage and NPM
 To determine the positive or negative relationship between leverage and ROE
 To determine the positive or negative relationship between leverage and ROA
 To determine the positive or negative relationship between leverage and EPS
 To determine the impact of leverage on GPM
 To determine the impact of leverage on OPM
 To determine the impact of leverage on NPM
 To determine the impact of leverage on ROE
 To determine the impact of leverage on ROA
 To determine the impact of leverage on EPS
The following questions are developed for the research:
 Is there any relationship between the leverage and performance indicators?
 Is the relationship positive or negative?
 Do performance indicators depend on leverage?
 On what other factors the performance indicators depend?
 Is the company a highly levered firm?
 To what extent the leverage was used by the company?
Hypothesis are tentative (i.e. not certain or fixed) statements or assumptions or guesses
developed based on the research objective to solve the research problems (i.e. to meet the
research objectives) or to provide indication for further research.
Therefore, the following null hypotheses have been developed and tested against the objectives
set forth above:
Hypothesis 1 (H0): There is no significant relationship between leverage and GPM
Hypothesis 2 (H0): There is no significant relationship between leverage and OPM
Hypothesis 3 (H0): There is no significant relationship between leverage and NPM
Hypothesis 4 (H0): There is no significant relationship between leverage and ROE
Hypothesis 5 (H0): There is no significant relationship between leverage and ROA

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Hypothesis 6 (H0): There is no significant relationship between leverage and EPS
Hypothesis 7 (H0): Leverage has no significant impact on GPM
Hypothesis 8 (H0): Leverage has no significant impact on OPM
Hypothesis 9 (H0): Leverage has no significant impact on NPM
Hypothesis 10 (H0): Leverage has no significant impact on ROE
Hypothesis 11 (H0): Leverage has no significant impact on ROA
Hypothesis 12(H0): Leverage has no significant impact on EPS
The choice of appropriate capital structure is a critical decision for corporate financiers because
of the likely impact of such financing decision in maximizing the wealth of its shareholders.
This study is especially significant to the “BSRM STEEL LTD” to know the effect of its
leverage on its profit so that it can take proper leverage and investment decisions. In addition,
this study will be of significant benefit to other individuals including:
 the investors to recognize the link between leverage and financial performance and
choosing appropriate measures to evaluate and analyze the BSRM STEEL LTD’s
financial status while committing their hard-earned funds for an expected return.
 the students and researchers who will want to develop a future research on this
subject.
The study of leverage is inevitable as debt is the main source of capital for the company. The
study can reveal the effects of leverage on the financial performance. By using the findings,
the BSRM STEEL LTD can make better decision regarding its capital structure management.

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Chapter 2: Literature Review
2.1. Introduction
2.2. Earlier studies regarding the effect of leverage on firm’s financial
performance
2.3. Earlier studies regarding the measures of leverage
2.4. Earlier Studies regarding the factors affecting firm’s performance

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This chapter presents empirical literature review on leverage and how it affects financial
performance of firms.
Al-Hasan,A., & Gupta,A. (2013) in their article “The Effect of Leverage on Shareholders’
Return: An Empirical Study on Some Selected Listed Companies in Bangladesh” uses two
variables EPS and leverage and reveals that leverage has statistically significant effect on the
shareholders’ return and proper management of leverage can maximize the value of EPS.1
Banafa, A. S, Muturi, W & Ngugi, K (2015) in their article “The impact of leverage on financial
performance of listed nonfinancial firm in kenya” shows that financial leverage has a negative
and significant effect on corporate financial performance (ROA).2
Achchuthan, S. (2012) in his article “Impact of Financial, Operating Leverage on the Financial
Performance: Special Reference to Lanka Orix Leasing Company Plc in Sri-Lanka” found that
only operating leverage has a significant impact on the financial performance. 3
Shaheen, Wasiq. (2015) in his article “Impact of Leverage on Financial Performance of the
Organization” found that leverage is negatively related to performance.4
Ahmed Ali, K. (2013) in his research project “The impact of financial leverage on firm
performance: the case of non-financial firms in Kenya” he found that there is a significant
negative relationship between leverage and ROA. He also found that profitable firms use
pecking order theory in its financing, the more profitable a firm is, the more likely they are
going to reduce its debts hence internal financing is preferred. 5
Richmond Senior, B., & Richmond Junior B. (2013) “The impact of leverage on firm’s
profitability; evidence from quoted banks on the Ghana stock exchange” found that leverage
has significant influence in operating profit, ROE, ROA of listed banks in Ghana.6
Tayyaba, Khushbakht. (2013) “Leverage – An Analysis and Its Impact On Profitability with
Reference to Selected Oil and Gas Companies” reveals that there is positive correlation
between DFL and EPS while there is negative correlation between DOL and EPS.7
Hasan, B., Ahsan, M., Rahaman, A., Alam, N. (2014) in their article “Influence of Capital
Structure on Firm Performance: Evidence from Bangladesh” found that there is significant
positive relations between EPS and short-term debt and significant negative relation between
EPS and long term debt. 8
Modigliani, F. and M. Miller. (1963) in their article “Corporate income taxes and the cost of
capital: A correction” shows that leverage matters and firms can really maximize value by
using more debt in their operations so as to take advantage of the tax shield benefits of
leverage.9

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Myers and Majluf (1984) in their article “Corporate financing and investment decisions when
firms have information that, investors do not have” contend that, firms would always prefer
internal sources of finance as opposed to external sources. These authors argue that, internal
funding which is specifically the use of retained earnings is cheaper as a source of finance
relative to external funding which is exclusively the use of debt and equity.10
Zivney, T. (2000). In his paper “Alternative Formulations of Degrees of Leverage”, categorizes
the measures into four types namely 11:
(a) elasticity based formula, 𝐷𝑂𝐿 =
% 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑛 𝐸𝐵𝐼𝑇
% 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑛 𝑆𝑎𝑙𝑒𝑠
& 𝐷𝐹𝐿 =
% 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑛 𝐸𝑃𝑆
% 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑛 𝐸𝐵𝐼𝑇
(b) textbook based formula, 𝐷𝑂𝐿 =
𝑆−𝑉𝐶
𝑆−𝑉𝐶−𝐹𝐶
& 𝐷𝐹𝐿 =
∆𝐸𝐵𝐼𝑇(1−𝑇)
(𝐸𝐵𝐼𝑇−𝐼𝑁𝑇)(1−𝑇)
×
𝐸𝐵𝐼𝑇
∆𝐸𝐵𝐼𝑇
(c) simplified formula, 𝐷𝑂𝐿 =
𝐸𝐵𝐼𝑇 + 𝐹𝐶
𝐸𝐵𝐼𝑇
& 𝐷𝐹𝐿 =
𝐸𝐵𝐼𝑇
𝐸𝐵𝐼𝑇−𝐼𝑁𝑇
(d) empirical use of simplified formula, 𝐷𝑂𝐿 = 1 +
𝐹𝐶
𝐸𝐵𝐼𝑇
& 𝐷𝐹𝐿 = 1 +
𝐼𝑁𝑇
𝐸𝐵𝐼𝑇−𝐼𝑁𝑇
.
IM Pandey, in his book “Financial Management” mention debt ratio, debt-equity ratio, interest
coverage ratio as a measure of financial leverage. According to him 12,
1. Debt Ratio =
𝐷𝑒𝑏𝑡
𝐷𝑒𝑏𝑡+𝐸𝑞𝑢𝑖𝑡𝑦
=
𝐷𝑒𝑏𝑡
𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑝𝑖𝑡𝑎𝑙
2. Debt-Equity Ratio =
𝐷𝑒𝑏𝑡
𝐸𝑞𝑢𝑖𝑡𝑦
3. Interest Coverage Ratio =
𝐸𝐵𝐼𝑇
𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡
Xu,M., & Banchuenvijit in their article “Factors affecting financial performance of firms listed
on shanghai stock exchange 50 (SSE 50)” reveals that asset utilization and leverage are factors
that affect financial performance of firms listed on SSE 50.13
Omondi, M., Muturi, W. (2013) in their article “Factors Affecting the Financial Performance
of Listed Companies at the Nairobi Securities Exchange in Kenya” reveals that leverage has a
significant negative impact and company size, liquidity, company age has positive impact on
firm’s performance.14

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Chapter 3: Research Design and Methodology
3.1 Introduction
3.2 Research Design Plan
3.3 Selection of Variables
3.4 Research Model
3.5 Sources of Data
3.6 Data Analysis Tools & Technique:
3.6.1 Techniques used for Hypothesis Testing
3.6.2 Software used for data processing

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This chapter shows the research design plan and methodology used to conduct the research.
I have designed my research by taking the following steps:
Step 1. Hypothesis Formulation based on Research Objective
Step 2. Selection of the variables
Step 3. Model Specification
Step 4. Collection of Data
Step 5. Hypothesis Testing
Step 6. Analysis and Interpretation
For determining the correlations and dependency two types of variables are selected:
Independent variables (also called exploratory variables) and dependent variables. These
variables are summarized below.
Independent Variables Dependent Variables
Financial Leverage:
Debt-Equity Ratio
Financial Performance Indicators:
1. Operating Profit Margin (OPM)
2. Gross Profit Margin (GPM)
3. Net Profit Margin (NPM)
4. Return on Equity (ROE)
5. Return on Assets (ROA)
6. Earnings Per Share (EPS)
The formula used for determining each variable above are summarized below:
A. Independent Variables Formula
Lev = Financial Leverage
= Debt-Equity Ratio
𝑇𝑜𝑡𝑎𝑙 𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠
𝑇𝑜𝑡𝑎𝑙 𝐸𝑞𝑢𝑖𝑡𝑦

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B. Dependent Variables Formula
1. GPM = Gross Profit Margin
𝐺𝑟𝑜𝑠𝑠 𝑃𝑟𝑜𝑓𝑖𝑡
𝑁𝑒𝑡 𝑆𝑎𝑙𝑒𝑠 𝑅𝑒𝑣𝑒𝑛𝑢𝑒
2. OPM = Operating Profit
Margin
𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑃𝑟𝑜𝑓𝑖𝑡
3. NPM = Net Profit Margin
𝑁𝑒𝑡 𝑃𝑟𝑜𝑓𝑖𝑡 𝐴𝑓𝑡𝑒𝑟 𝑇𝑎𝑥
4. ROE = Return on Equity
𝑇𝑜𝑡𝑎𝑙 𝐸𝑞𝑢𝑖𝑡𝑦
5. ROA = Return on Total Asset
𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠
6. EPS = Earnings Per Share
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑆ℎ𝑎𝑟𝑒𝑠
Research model is designed to determine the impact of independent variable (Leverage) on the
dependent variable (Financial Performance Indicators). I used the following regression
equation for designing the research model:
𝑌 = 𝛼 + 𝛽1 𝑋1 + 𝜀
𝑊ℎ𝑒𝑟𝑒,
𝑌 = 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒
𝑋𝑖 = 𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒
𝛼 = 𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡 𝑡𝑒𝑟𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑚𝑜𝑑𝑒𝑙
𝛽 = 𝐶𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑚𝑜𝑑𝑒𝑙
𝜀 = 𝐸𝑟𝑟𝑜𝑟 𝑡𝑒𝑟𝑚
Based on the above regression equation, the following models are developed:
Model 1: The Impact of Leverage on GPM
GPM = 𝛼1 + 𝛽1 𝑙𝑒𝑣 + 𝜀1
Model 2: The Impact of Leverage on OPM
OPM = 𝛼2 + 𝛽2 𝑙𝑒𝑣 + 𝜀2

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Model 3: The Impact of Leverage on NPM
NPM = 𝛼3 + 𝛽3 𝑙𝑒𝑣 + 𝜀3
Model 4: The Impact of Leverage on ROE
ROE = 𝛼4 + 𝛽4 𝑙𝑒𝑣 + 𝜀4
Model 5: The Impact of Leverage on ROA
ROA = 𝛼5 + 𝛽5 𝑙𝑒𝑣 + 𝜀5
Model 6: The Impact of Leverage on EPS
EPS = 𝛼6 + 𝛽6 𝑙𝑒𝑣 + 𝜀6
In my study I used the secondary data as an input for analysis. All data is based on the annual
report of BSRM STEEL LTD. The data covers the year from 2010 to 2015.
For processing the data, I used the following techniques and software.
To test the hypothesis developed earlier I used following statistical tools:
1. Descriptive Statistics
2. Correlation Analysis
3. Regression Analysis
I processed the data by using the following software:
1. IBM SPSS Statistics 20
2. Microsoft Excel 2016

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Chapter 4: Profile of BSRM STEEL LTD.
4.1.Introduction
4.2.BSRM STEEL LTD from 1952 to 2015

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In this chapter I tried to provide the brief overview of BSRM STEEL LTD.
The Bangladesh Steel Re-Rolling Mills, commonly known as BSRM, is a one of the largest
and first steel manufacturing company in Bangladesh. It started its journey in 1952 by the hand
of two intrepid businessmen Taherali Africawala and Akberali Africawala.
Now BSRM LTD is a sister concern of BSRM Group. The BSRM Group business is divided
into four categories:
(a) Section and Bar Rolling
(b) Steel Making
(c) High Strength Rebar Rolling
(d) Ribbed Wire Production
Let’s look at the history of BSRM STEEL LTD:
1952 The BSRM saga began with the first steel re-rolling mills to emerge in the then East
Bengal.
1984 Introduced high strength cold twisted steel bars (TORSTEEL) to the construction
industry.
1987 Introduced High Strength Deformed reinforcing steel bars conforming to ASTM 615
Grade 60 for the construction industry.
1996 Commissioned the then largest billet making plant in the country - Meghna Engineering
Works Limited, now known as Steel Melting Works (SMW) unit of Bangladesh Steel
Re-Rolling Mills Ltd.
2006 Introduced micro reinforcement wires, below 8mm for low cost rural construction.
2008 BSRM Steels Limited commenced production of internationally recognized Grade 500
steel bars branded as “Xtreme500W” conforming to ISO 6935-2.
2009 Entrance in the Capital Market
Shares of BSRM Steels Limited, the flagship company of BSRM Group was listed with
the country’s premier bourses Dhaka Stock Exchange Ltd. (DSE) and Chittagong Stock
Exchange Ltd. (CSE) on 18 January 2009. Market Capitalization as on 31 December
2015 is Tk. 32,913 million. The public shareholding including institutional investors is
29.13%.
2010 BSRM Iron and Steel Co. Ltd. largest billet making plant in the country started
commercial production on June 01, 2010.
2012 Production capacity of BSRM Steels Limited enhanced to 600,000 MT per year.
2013 A syndicated term loan of US$ 40 million and BDT 5,908 million, raised by a
consortium of 25 banks and financial institutions, for BSRM Steel Mills Limited. It is
the largest ever syndicated loan facility arranged for a private company in Bangladesh.
The Plant will produce billets.

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2014 Oracle e-BS -12 went GO LIVE on 1st March 2014. Oracle Financials, Costing,
purchasing, Manufacturing, EAM, Inventory & Order Management are now integrated
on a single platform which ensure the accuracy, accountability and reliability of the
Group.
2015 1. Enhanced capacity of BSRM Steels Limited from 600,000 MT to 700,000 MT per
annum.
2. Announced a new product namely “BSRM Maxima”
3. Increased capacity of Bangladesh Steel Re-Rolling Mills from 120,000 MT to
450,000 MT per annum which will be the first and largest merchant mill in
Bangladesh.
4. Listing of Bangladesh Steel Re-Rolling Mills Limited with the stock exchanges
(DSE & CSE).
5. 5. Start of trial production of world’s largest induction furnace based billet casting
project –“BSRM Steel Mills Limited”.
In 2015, the corporate structure of BSRM LTD look like as follows:

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Chapter 5: Data Analysis and
Interpretations
5.1 Introduction
5.2 BSRM’s Financial Performance & Financial Position over Six years
5.3 BSRM’s Level of Leverage and Financial Performance
5.3.1. Capital Structure
5.3.2. Leverage Level
5.3.2.1. Overall Leverage Level
5.3.2.2. Specific Leverage Level
5.3.3. Level of Financial Performance Indicators
5.3.4. Borrowings and Financial Performance Indicators
5.4 Hypothesis Testing and Interpretation
5.4.1 Summary of the Variables’ Data
5.4.2 Descriptive Statistics and Interpretation
5.4.3 Correlation Analysis and Interpretation
5.4.4 Regression Analysis and Interpretation
5.5 Summary of Hypothesis testing

16 | P a g e
This chapter presents the analysis and interpretation of the research. This chapter is designed
in the following ways:
Summary of Data Input (by means of Balance sheet, Income Statement,
variables)
Processing and Interpretation (by means of descriptive statistics, correlation
analysis, and regression analysis)
I have modified the statement of financial position and the statement of financial performance
of BSRM STEEL LTD by keeping the value intact for showing actual effect of leverage on
performance. The modified financial statements from 2010 to 2015 are summarized below:
In Millions(Rounded)
2010 2011 2012 2013 2014 2015
Total Assets
Current Assets 7,366 16,553 14,894 15,346 18,601 15,054
Noncurrent Assets 4,868 5,058 7,523 8,559 8,540 9,676
TotalAssets 12,234 21,610 22,417 23,905 27,141 24,730
Total Liabilities & Equities
A. Total Liabilities:
a. Current Liabilities: 8,902 17,763 16,159 15,858 18,445 14,214
1. Borrowing Related: 7,489 14,598 15,347 13,492 17,256 12,859
i. Short termBorrowings 7,020 14,001 14,648 13,165 17,024 12,651
ii. Current Portion ofLong TermBorrowing 469 597 673 197 228 197
iii. Interest Payable 0 0 26 130 3 12
2. Others 1,413 3,165 811 2,366 1,189 1,355
b.Noncurrent Liabilities 1,198 873 718 1,132 1,200 1,436
1. Long TermBorrowings 1,198 873 219 425 432 548
2. Others 0 0 499 707 768 888
TotalLiabilities (a+b) 10,099 18,636 16,876 16,990 19,646 15,650
B. Total Equity:
a. Share Capital 2,713 3,255 3,255 3,418 3,418 3,418
b. Retained earnings (578) (281) 115 1,344 1,940 3,531
1. Net Profit After Tax 965 839 865 1,693 1,086 2,082
2. Others (1,543) (1,120) (751) (350) 854 1,449
c. Revaluation reserve 0 0 2,171 2,154 2,137 2,132
TotalEquity (a+b+c) 2,135 2,974 5,541 6,915 7,495 9,081
TotalLiabilities and Equities (A+B) 12,234 21,610 22,417 23,905 27,141 24,730
Statement of Financial Position
BSRM STEEL Ltd.
(Modified)

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The table 1 below shows the level of capital structure mix. It is clear from the table that the
major sources of capital of the company is debt. Total liability level (75% on an average) is
48% more than the equity (25% on average) over the 6 years. It indicates that the BSRM
STEEL LTD is a highly levered firm. But both debt and equity levels are fluctuating.
Table1: Capital Structure Mix
In Millions (Rounded)
2010 2011 2012 2013 2014 2015
Sales Revenue 22,008 31,235 38,253 36,229 38,536 32,316
Less: Cost of Goods Sold 20,078 29,320 36,365 32,979 35,729 27,947
Gross Profit 1,930 1,915 1,888 3,250 2,807 4,369
Less: Fixed Operating Cost 379 546 730 940 923 1,127
1,551 1,369 1,158 2,310 1,885 3,242
Add/(Less): Share of Profit/(Loss) of associate 0 0 0 497 (3) 75
Add: Finance Income 2 47 496 239 188 66
Add: Other Income 1 1 2 4 8 16
Less: WPP&WF 51 51 68 96 80 133
Profit Before Interest & Tax 1,502 1,366 1,588 2,955 1,998 3,267
Less: Interest 535 404 292 636 487 673
Profit before Tax 968 962 1,297 2,319 1,511 2,594
Less: Tax 3 123 431 625 424 512
Net Profit After Tax (NPAT) 965 839 865 1,693 1,086 2,082
Operating Profit Before Other Adjustment,
Interest, Tax
Statement of Financial Performance
BSRM Steels Limited
(Modified)
Total Asset
In Million Tk. % of Total Asset In Million Tk. % of Total Asset (In Million Tk.)
2010 2135 17.45% 10099 82.55% 12234
2011 2974 13.76% 18636 86.24% 21610
2012 5541 24.72% 16876 75.28% 22417
2013 6915 28.93% 16990 71.07% 23905
2014 7495 27.62% 19646 72.38% 27141
2015 9081 36.72% 15650 63.28% 24730
Total Equity
Year
Total Liability

18 | P a g e
The leverage or debt level is shown here from two viewpoints: (a) Overall or Total Leverage
Level and (b) Specific or Borrowing Leverage Level. These are discussed in the following
sections.
From the viewpoint of total liability leverage is measured by using two leverage measures:
Total Liability to Total Asset and Total Liability to Total Equity.
Table 2: level of leverage (Total Liability)
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
2010 2011 2012 2013 2014 2015
Capital Structure
Equity Level Liability Level
Year Liability to Asset% Liability to Equity%
2010 82.55% 473%
2011 86.24% 627%
2012 75.28% 305%
2013 71.07% 246%
2014 72.38% 262%
2015 63.28% 172%

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From the both measures it is observed that the leverage levels are fluctuating over the 6 years.
Total lability to asset shows the % as a total where in 2010 and 2011 the highest leverage is
used. Total liability to equity gives us the clear picture regarding leverage level against equity.
Both the measures show that the company is a highly levered firm.
From the viewpoint of specific source i.e. borrowing leverage is measured again by using the
two leverage measures as follows:
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
2010 2011 2012 2013 2014 2015
Liability to Asset
0%
100%
200%
300%
400%
500%
600%
700%
2010 2011 2012 2013 2014 2015
Liability to Equity

20 | P a g e
Table 3: Level of leverage (Borrowings)
In Million Tk. LTB to Asset LTB to Equity In Million Tk. STB to Asset STB to Equity
2010 1,198 9.79% 56.10% 7,020 57.38% 328.83%
2011 873 4.04% 29.34% 14,001 64.79% 470.77%
2012 219 0.98% 3.95% 14,648 65.34% 264.38%
2013 425 1.78% 6.15% 13,165 55.07% 190.38%
2014 432 1.59% 5.76% 17,024 62.73% 227.14%
2015 548 2.22% 6.04% 12,651 51.15% 139.32%
Long Term Borrowing Short Term Borrowing
Year
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
2010 2011 2012 2013 2014 2015
Borrowings to Asset
LTB to Asset STB to Asset
0.00%
50.00%
100.00%
150.00%
200.00%
250.00%
300.00%
350.00%
400.00%
450.00%
500.00%
2010 2011 2012 2013 2014 2015
Borrowings to Equity
LTB to Equity STB to Equity

21 | P a g e
The both measures reveal that the major source of leverage is short term debt. The liability to
asset measure shows that the level of short term is 56% higher on an average than long term
leverage. The liability to equity measure shows that the level of short term is 219% on an
average higher than long term leverage.
The level of performance indicators is fluctuating over the 6 years. The six years’ performance
levels are given below.
Table 4: Level of financial performance
The most successful year for the company is 2013 and 2015 in which the company make the
highest profits than the other years. The GPM, OPM, NPM, ROE, ROA, EPS in 2013 is 8.97%,
6.38%, 4.67%, 24.49%, 7.08%, Tk. 4.95 respectively and in 2015 is 13.52%, 10.03%, 6.44%,
22.93%, 8.42%, Tk. 6.09 respectively.
Year GPM OPM NPM ROE ROA EPS
2010 8.77% 7.05% 4.38% 45.20% 7.89% 2.82
2011 6.13% 4.38% 2.69% 28.22% 3.88% 2.46
2012 4.94% 3.03% 2.26% 15.62% 3.86% 2.53
2013 8.97% 6.38% 4.67% 24.49% 7.08% 4.95
2014 7.28% 4.89% 2.82% 14.49% 4.00% 3.18
2015 13.52% 10.03% 6.44% 22.93% 8.42% 6.09
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
2010 2011 2012 2013 2014 2015
GPM

22 | P a g e
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
2010 2011 2012 2013 2014 2015
OPM
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
2010 2011 2012 2013 2014 2015
NPM
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
2010 2011 2012 2013 2014 2015
ROE

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This section shows the actual picture of using leverage that may be unclear using statistically.
Increase in borrowings level by 1.66% from 2010 to 2011 increases the sales by 115% but
reduce the NPBT by .62% due to the adjustment of loss and reduction in interest expense,
reduces the NPAT by 13%% due to increase in tax.
Decrease in borrowings level by 10.95% from 2014 to 2015 increases all the financial
performance indicators like GPM, OPM, NPM, ROE, ROA, EPS. So, 2015 is the efficient level
for the organization. In this year they managed the debt well.
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
2010 2011 2012 2013 2014 2015
ROA
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
2010 2011 2012 2013 2014 2015
EPS

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Here the following statistical tools are used to test the hypothesis developed earlier.
Statistical Tools Nature of Testing Is used for
1. Descriptive Statistics Testing the extent of leverage usage
and performance indicators, and the
risks and variability, maximum,
minimum of the variables.
Answering research
Question
2. Correlation Analysis Testing whether there is relationship
between dependent and independent
variables. If so, is the relationship
positive or negative.
Testing Hypothesis 1
to 6
3. Regression Analysis Testing the effect of leverage
(independent variable) on financial
performance indicators (dependent
variable)
Testing Hypothesis 7
to 12
Table5:Borrowings and NPAT
Sales CGS GP
Operating
Exp.
Operating
Profit
Adjust-
ment
NPBI&T
Interest
Exp.
NPBT Tax NPAT
(1) (2) (3)= (1)-(2) (4) (5)= (3)-(4) (6) (7)= (5)-(6) (8) (9)= (7)-(8) (10) (11)= (9)-(10)
2010 8218 22008 20078 1930 379 1551 -48 1502 535 968 3 965
2011 14874 31235 29320 1915 546 1369 -3 1366 404 962 123 839
2012 14867 38253 36365 1888 730 1158 430 1588 292 1297 431 865
2013 13590 36229 32979 3250 940 2310 644 2955 636 2319 625 1693
2014 17456 38536 35729 2807 923 1885 113 1998 487 1511 424 1086
2015 13199 32316 27947 4369 1127 3242 26 3267 673 2594 512 2082
In Millions(Rounded)
Year
Total
Borrowings

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The variables data used for testing hypothesis are calculated using Microsoft Excel. The
variables data are summarized in the following table:
Descriptive statistics is used to present the minimum, maximum, mean, standard deviation,
variance of the variables undertaken for analysis. It is used in my study to determine the average
level of leverage and the associated profits along with risks of that leverage level. The
calculation is done through SPSS software. The output of SPSS regarding descriptive statistics
is given below:
SPSS Output: Descriptive Statistics
The table shows the mean, standard deviation, variance, minimum, maximum, total observation
values for all the variables under study. The leverage, represented by ‘lev’, indicates that about
347% of leverage is used by the company against equity. It means total equity is not enough to
pay the debt. It also means that the company is a highly levered firm. The variability of leverage
is represented by standard deviation which is 170% on an average. It indicates the company
facing huge financial risks. The maximum level and minimum level of leverage against equity
used by the firm are 627% and 172% respectively.
The mean of GPM, OPM, NPM are 8%, 5%, 3% and the deviation (indicating variability) from
the mean of them are 2.9%, 2.4%, 1.5% respectively. It means the company is generating
profits by using debt. The maximum of GPM, OPM, NPM are 13%, 10%, 6%, and the
minimum of them are 4%, 3%, 2%.
Year Lev GPM OPM NPM ROE ROA EPS
2010 4.731 0.088 0.070 0.044 0.452 0.079 2.820
2011 6.266 0.061 0.044 0.027 0.282 0.039 2.460
2012 3.046 0.049 0.030 0.023 0.156 0.039 2.532
2013 2.457 0.090 0.064 0.047 0.245 0.071 4.955
2014 2.621 0.073 0.049 0.028 0.145 0.040 3.178
2015 1.723 0.135 0.100 0.064 0.229 0.084 6.091
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation Variance
Lev 6 1.7234 6.2661 3.474000 1.6961525 2.877
GPM 6 .0494 .1352 .082683 .0299837 .001
OPM 6 .0303 .1003 .059600 .0245583 .001
NPM 6 .0226 .0644 .038767 .0158693 .000
ROE 6 .1449 .4520 .251583 .1114673 .012
ROA 6 .0386 .0842 .058550 .0216992 .000
EPS 6 2.4600 6.0914 3.672717 1.4991957 2.248
Valid N (listwise) 6

26 | P a g e
The mean of ROA and ROE is 8%, 25% and the deviation from the mean is 2%, 11%
respectively. The maximum of ROA and ROE is 8% and 45% and the minimum of them is 3%,
14% respectively.
The mean of EPS, measured in Tk./share, Tk. 3.67 and the deviation, maximum, minimum of
it are Tk. 1.5, Tk. 6.09, Tk. 2.46.
In this section, null hypothesis is tested using correlation analysis where Pearson Correlation
is used to determine the relationship (positive, negative, or zero relationship) between the
dependent variable (leverage) and one by one of the independent variables (GPM, OPM, NPM,
ROE, ROA, EPS). Bivariate correlation of SPSS is used to calculate the relationships between
the variables. Arranged Output of SPSS of correlation between variables are given below:
Arranged Output of SPSS: Correlations
Test of Hypothesis 1 (H0): There is no significant relationship between leverage and GPM
The correlation between Leverage and GPM is -.510 indicating negative correlations between
them. The calculated significance value (P value), .301, is greater than 0.05. Therefore, null
hypothesis is accepted and it can be concluded that there is no significant relationship between
leverage and GPM.
Test of Hypothesis 2 (H0): There is no significant relationship between leverage and OPM
Leverage and OPM have also negative correlation which is -.405. The significance value of the
correlation is .426 which is greater than .05 and therefore null hypothesis is accepted. So, it can
be concluded that there is no significant relationship between leverage and OPM.
Test of Hypothesis 3 (H0): There is no significant relationship between leverage and NPM
Leverage and NPM have also negative correlation which is -.474. The significance value of the
be concluded that there is no significant relationship between leverage and NPM.
GPM OPM NPM ROE ROA EPS
Pearson
Correlation
-.510 -.405 -.474 .545 -.340 -.715
Sig. (2-tailed) .301 .426 .342 .264 .510 .111
N 6 6 6 6 6 6
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Lev

27 | P a g e
Test of Hypothesis 4 (H0): There is no significant relationship between leverage and ROE
Leverage and ROE have positive correlation which is .545. The significance value of the
be concluded that there is no significant relationship between leverage and ROE.
Test of Hypothesis 5 (H0): There is no significant relationship between leverage and ROA
Leverage and ROE have negative correlation which is -.340. The significance value of the
be concluded that there is no significant relationship between leverage and ROA.
Test of Hypothesis 6 (H0): There is no significant relationship between leverage and EPS
Leverage and ROE have negative correlation which is -.715. The significance value of the
be concluded that there is no significant relationship between leverage and EPS.
Test of Hypothesis 7 (H0): Leverage has no significant impact on GPM
SPSS Output: Model 1: Lev & GPM
Using this output the following model is calculated:
𝐺𝑃𝑀 = .114 − .009 𝑙𝑒𝑣
This model shows that GPM is a function of leverage. Increase in leverage by 1% will reduce
GPM by 1%. i.e. the negative relationship between leverage and GPM exists as it is explained
earlier. But the significant value .301 of the correlation is greater than .05 therefore, null
hypotheses is accepted. So we can conclude that leverage has no significant impact on GPM.
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .114 .029 3.945 .017
Lev -.009 .008 -.510 -1.187 .301
a. Dependent Variable: GPM

28 | P a g e
Test of Hypothesis 8 (H0): Leverage has no significant impact on OPM
SPSS Output: Model 1: Lev & OPM
Based on this output the following model is calculated:
𝑂𝑃𝑀 = .080 − .006 𝑙𝑒𝑣
The model reveals that OPM is a function of leverage. Increase in leverage by 1% will reduce
OPM by 1%. i.e. the negative relationship between leverage and OPM exists as it is explained
earlier. But the significant value .426 of the correlation is greater than .05, therefore null
hypotheses is accepted. So we can conclude that leverage has no significant impact on OPM.
Test of Hypothesis 9 (H0): Leverage has no significant impact on NPM
SPSS Output: Model 1: Lev & NPM
On the basis of this output the following model is calculated:
𝑁𝑃𝑀 = .054 − .004 𝑙𝑒𝑣
It is observed from the model that NPM is a function of leverage. Increase in leverage by 1%
will reduce NPM by 1%. i.e. the negative relationship between leverage and NPM exists as it
is explained earlier. But the significant value .342 of the correlation is greater than .05,
therefore null hypotheses is accepted. So we can conclude that leverage has no significant
impact on NPM.
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .080 .025 3.175 .034
Lev -.006 .007 -.405 -.885 .426
a. Dependent Variable: OPM
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .054 .016 3.459 .026
Lev -.004 .004 -.474 -1.077 .342
a. Dependent Variable: NPM

29 | P a g e
Test of Hypothesis 10 (H0): Leverage has no significant impact on ROE
SPSS Output: Model 1: Lev & ROE
Using this output the following model is calculated:
𝑅𝑂𝐸 = .127 − .036 𝑙𝑒𝑣
This model shows that ROE is a function of leverage. Increase in leverage by 1% will reduce
ROE by 1%. i.e. the negative relationship between leverage and ROE exists as it is explained
hypotheses is accepted. So we can conclude that leverage has no significant impact on ROE.
Test of Hypothesis 11 (H0): Leverage has no significant impact on ROA
SPSS Output: Model 1: Lev & ROA
On the basis of this output the following model is calculated:
𝑅𝑂𝐴 = .074 − .004 𝑙𝑒𝑣
This model shows that ROA is a function of leverage. Increase in leverage by 1% will reduce
ROA by 1%. i.e. the negative relationship between leverage and ROA exists as it is explained
hypotheses is accepted. So we can conclude that leverage has no significant impact on ROA.
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .127 .105 1.214 .292
Lev .036 .028 .545 1.299 .264
a. Dependent Variable: ROE
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .074 .023 3.220 .032
Lev -.004 .006 -.340 -.723 .510
a. Dependent Variable: ROA

30 | P a g e
Test of Hypothesis 12 (H0): Leverage has no significant impact on EPS
SPSS Output: Model 1: Lev & EPS
Based on this output the following model is calculated:
𝐸𝑃𝑆 = 5.867 − .632 𝑙𝑒𝑣
The model indicates that EPS is a function of leverage. Increase in leverage by 1% will reduce
EPS by 1%. i.e. the negative relationship between leverage and EPS exists as it is explained
hypotheses is accepted. So we can conclude that leverage has no significant impact on EPS.
Name of Hypothesis
Accepted or
Rejected
Hypothesis 1 (H0): There is no significant relationship between leverage and GPM Accepted
Hypothesis 2 (H0): There is no significant relationship between leverage and OPM Accepted
Hypothesis 3 (H0): There is no significant relationship between leverage and NPM Accepted
Hypothesis 4 (H0): There is no significant relationship between leverage and ROE Accepted
Hypothesis 5 (H0): There is no significant relationship between leverage and ROA Accepted
Hypothesis 6 (H0): There is no significant relationship between leverage and EPS Accepted
Hypothesis 7 (H0): Leverage has no significant impact on GPM Accepted
Hypothesis 8 (H0): Leverage has no significant impact on OPM Accepted
Hypothesis 9 (H0): Leverage has no significant impact on NPM Accepted
Hypothesis 10 (H0): Leverage has no significant impact on ROE Accepted
Hypothesis 11 (H0): Leverage has no significant impact on ROA Accepted
Hypothesis 12(H0): Leverage has no significant impact on EPS Accepted
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 5.867 1.176 4.990 .008
Lev -.632 .309 -.715 -2.043 .111
a. Dependent Variable: EPS

31 | P a g e
Chapter 6: Findings, Recommendation,
Limitations, and Conclusions
6.1 Introduction
6.2 Research Findings
6.3 Recommendations
6.4 Limitations of the study
6.5 Conclusions

32 | P a g e
This chapter presents the research findings, recommendations, limitation, and conclusions of
the research.
The descriptive statistics shows that the BSRM STEEL LTD is a highly levered company. The
major sources of its capital is debt which is 347% against total equity on an average of six
years. The standard deviation from the mean of leverage is 170% indicating the fluctuation and
risks of using debt.
The correlation analysis shows the negative correlation between leverage and GPM, OPM,
NPM, ROE, EPS. It means increasing leverage level will decrease the profit level. It is due to
huge amount of contributions to WPP&WF and increases of interest payments. In addition, it
shows positive Correlation between leverage and ROE that indicates increase in leverage will
increase in ROE. It is because of the reduction in total equity which is due to loss from 2010
to 2013. However, this correlation is not statistically significant according to the standard p
value (.05).
The regression analysis shows the dependency of GPM, OPM, NPM, ROE, ROA, EPS on
Leverage. Leverage has negative impact on GPM, OPM, NPM, ROE, ROA, EPS. However,
the impact is also statistically not significant according to the standard p value (.05).
In aggregate, my study reveals that statistically leverage has no significant relationship with or
impact on the financial performance of BSRM STEEL LTD.
Based on the findings I suggest the followings to management of BSRM STEEL LTD.
 The company should investigate the reasons of not efficient utilization of debt and
should investigate why the relationship is not statistically significant.
 The company should use right mix of debt and equity that will maximize the EPS
 Too much dependent on debt is not good. Therefore, the company should increase
raising capital through equity.
 The company should diversify its business. Diversification will spread the risks. Risk
in one business will be offset by the profits of others.
 The company is too much dependent on short term borrowings. Therefore, interest is
so high. It means the company use the financing for short term investment or for
fulfilling working capital needs. It also means that the company is facing too much
short term financing risks. For this reason, the company should do the cost benefit
analysis before taking borrowings. It should take the optimal decisions.

33 | P a g e
My research is not without the limitations. It has the following limitations:
 Time constraint: this research is for the completion of my MBA program. So, I don’t
have enough time in doing the research deeply. So, a lot of mistake may be found here.
 Few Sample Size: It is known that the greater the sample size the greater the correction
of research. But the sample size used in my research is very low. Due to this, the actual
picture of the company may be unclear.
 Different Measures: lots of measures are available for measuring leverage. In this
paper, I use only total liabilities to total equity for measuring financial leverage.
 Ignoring the effect of Operating and Combined Leverage: This paper covers only
the effect of financial leverage on financial performance. The effect of Operating
leverage and combined leverage having significant impact on the performance is not
covered in this paper.
 Only one independent variable is used: Only one factor affecting profit of the
company was used in this study. But there are lots of other factors like Firm Size, Sales
Growth, Firm Age, Liquidity, etc. that may affect financial performance were not used
in this study.
The study reveals that leverage has no significant impact or relationship on or with financial
performance. It doesn’t mean that there is no relationship or impact at all. It is found from the
study that GPM, OPM, NPM, ROA, EPS have negative relationship with leverage. It is also
found that ROE and Leverage have positive relationship. Although the relationship and impact
is statistically insignificant, my study reveals the existence of relationship or impact of leverage
with or on financial performance of BSRM STEEL LTD.

34 | P a g e
1. Al-Hasan, A., & Gupta, A. (2013) The Effect of Leverage on Shareholders’ Return: An
Empirical Study on Some Selected Listed Companies in Bangladesh. European Journal of
Business and Management. 5(3)
2. Banafa, A. S, Muturi, W & Ngugi, K (2015). The impact of leverage on financial
performance of listed non-financial firm in Kenya. International Journal of Finance and
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35 | P a g e
Model 1: Lev & GPM
Variables Entered/Removeda
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
b. All requested variables entered.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .510a
.261 .076 .0288269
a. Predictors: (Constant), Lev
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression .001 1 .001 1.409 .301b
Residual .003 4 .001
Total .004 5
b. Predictors: (Constant), Lev
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .114 .029 3.945 .017
Lev -.009 .008 -.510 -1.187 .301

36 | P a g e
Model 2: Lev & OPM
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
Model Summary
Square
Std. Error of the
Estimate
1 .405a
.164 -.045 .0251092
ANOVAa
1
Regression .000 1 .000 .783 .426b
Total .003 5
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .080 .025 3.175 .034
Lev -.006 .007 -.405 -.885 .426

37 | P a g e
Model 3: Lev & NPM
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
Model Summary
Square
Std. Error of the
Estimate
1 .474a
.225 .031 .0156209
ANOVAa
1
Regression .000 1 .000 1.160 .342b
Total .001 5
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .054 .016 3.459 .026
Lev -.004 .004 -.474 -1.077 .342

38 | P a g e
Model 4: Lev & ROE
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
. Dependent Variable: ROE
Model Summary
Square
Std. Error of the
Estimate
1 .545a
.297 .121 .1045103
ANOVAa
1
Regression .018 1 .018 1.688 .264b
Total .062 5
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .127 .105 1.214 .292
Lev .036 .028 .545 1.299 .264

39 | P a g e
Model 5: Lev & ROA
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
Model Summary
Square
Std. Error of the
Estimate
1 .340a
.116 -.105 .0228149
ANOVAa
1
Regression .000 1 .000 .523 .510b
Total .002 5
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .074 .023 3.220 .032
Lev -.004 .006 -.340 -.723 .510

40 | P a g e
Model 6: Lev & EPS
Model Variables
Entered
Variables
Removed
Method
1 Levb
. Enter
Model Summary
Square
Std. Error of the
Estimate
1 .715a
.511 .388 1.1725363
ANOVAa
1
Regression 5.739 1 5.739 4.174 .111b
Residual 5.499 4 1.375
Total 11.238 5
Coefficientsa
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 5.867 1.176 4.990 .008
Lev -.632 .309 -.715 -2.043 .111

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