International Journal of Accounting and Financial

Management Research (IJAFMR)

ISSN 2249-6882

Vol. 2 Issue 4 Dec 2012 1-8

© TJPRC Pvt. Ltd.,

COMPARATIVE STUDY OF FINANCIAL PERFORMANCE OF INDIAN STEEL

COMPANIES UNDER GLOBALIZATION

SHRABANTI PAL

Research Scholar, Department of Business Management, University of Calcutta, West Bengal,India

ABSTRACT

Indian steel industry is one of the fastest growing industries and contributes a significant amount to the country’s

GDP. India is the fourth largest steel producer in the world after China, Japan and USA. Indian steel industry is

contributing around 2 percent to Gross Domestic Product (GDP) and its weight in the Index of Industrial Production (IIP)

is 6.2 percent. The present paper is an endeavor to examine the financial performance of the Indian steel companies and

establish the linear relationship between liquidity, leverage, efficiency and profitability of the selected companies. Indian

steel companies are selected for the study on the basis of market share in 2008-09 for a period of twenty years ranging

from 1991-92 to 2010-2011. The public sector company Steel Authority of India is holding the highest market share

followed by Tata Steel Limited, JSW Steel Limited, Essar Steel Limited, JSW Ispat and Steel Limited, Rastriya Ispat

Nigam Limited, Jindal Steel and Power Limited, Bhushan Steel Limited, Llyods Steel Industries Limited and National

Steel and Agro Industries Limited. To estimate the impact of selected variables on the profitability multiple regression

analysis is carried on and the models are predicted for such purpose

KEY WORDS: Financial Performance of Indian Steel Companies, Multiple Regression Analysis, Compare the Financial

Performance of Indian Steel Companies

INTRODUCTION

Indian steel industry has played a significant role in development of Indian economy. It has acquired a place on

global steel map due to its phenomenal performance in steel production, consumption and foreign trade since last decade.

India is currently occupied fourth position of largest steel producing nation in the world with a production of 71.3 million

tonnes after China, Japan and U.S.A. At present the apparent steel consumption in India is about 55 kg per annum which is

very less compared to other economically developed countries. Therefore, there is an immense scope for the Indian steel

industry to grow further. The major contribution directs the attention that the steel is having a strong hold in the traditional

sectors like infrastructure and construction, automobile, transportation and industrial application etc. However, during

2001-02 to 2010-11 owing to boom in the infrastructure and automobile sector the industry experienced a turnaround and

records a sharp increase of 8.6 percent compound annual growth rate. Potential steel demand also derived by the consumer

durables and white goods industry. Hence, the present study is basically aims to compare the financial performance of

Indian steel companies under globalization and establish the linear relationship between liquidity, leverage, efficiency and

profitability of the selected companies.

LITERATURE REVIEW

Multiple Regression analysis is a very widely used statistical tool to determine the linear relationship between the

ratios and other performance indicators of the firms. DeVancy (1993) conducted a study to measure the changes of status

in the families of United States of America by using financial ratios selected from different categories for a period of four

years ranging from 1983 to 1986. This study used the financial ratios as indicators of progress to answer the question

2 Shrabanti Pal

whether the households were able to improve their financial status during the study period. The importance of ratios is

increasing for the purpose of measuring the financial performance of the company. Cleary (1999) applied regression

analysis to different financial ratios on 1317 U.S firms for a period of seven years started from 1987 to 1994 to show the

relationship between investment and financial status of the firm. Forsaith and Hall (2000) used regression technique to a

number of financial ratios of Australian manufacturing and wholesale sector firms to observe the relationship between

financial ratios and the firm size. Hence, the study reveals that there is no close relationship between the ratios and firm

size. Erhardt, Werbel and Shrader (2003) performed a study on 127 large U.S companies and applied regression method on

financial ratios and demographic diversity to check the relationship between demographic diversity on Board of Directors

and financial performance and indicate that board diversity is positively associated with these financial indicators of firm

performance.

Gallizo and Salvador (2003) also carried out a study on financial ratios of U.S manufacturing firms for a period of

eight years since 1993 to 2000 to understand the behavior and adjustment process of the same. A proper balance between

sales and assets generally specify that the assets are managed and utilized well towards the sales generation. The main aim

of the company is to maximize its profit and profitability ratios helps to measure overall performance and efficiency of the

firm. Raheman and Nasr (2007) carried on a research on profitability and working capital management of the Pakistani

firms for a period of six years (1999-2004) and applied regression analysis to explore the relationship between working

capital variables and profitability indicators and the result showed a negative relationship between working capital and

profitability due to liquidity-profitability tangle.

Gulsun and Umit (2010) applied Multiple Regression technique in their research paper on Turkish Insurance

Companies to develop a warning model to identify the companies that are experiencing deterioration in financial health.

Schneider and Matai (2010) carried on a study regarding business climate, political risk and FDI on developing and

transition countries covering a period from 1996 to 2008 to develop a model to specify the impact of business climate and

political risk on FDI. Kavita and Manivanna (2010) conducted a research on Indian software companies for a period of ten

years ranging from 1997 to 2007. They applied regression technique to quantify the strength of relationship between

operating profit and liquidity factors of the concerned firms and also to evaluate the overall financial performance and

operational efficiency of the companies.

A study has been conducted by Bhunia (2010) on private sector steel companies of India to test the short term

liquidity trend of the companies and its effect on the financial performance. The study reveals that the inventory and

receivable management require special attention and proper control over inventory. The investment in loans and advances

should be minimized to the extent possible. A balanced and proper amount of working capital should be maintained in the

business for smooth running of the same. The management of the companies should adopt a viable and proficient payment

policy. At the same time maximization of assets and minimization of liabilities should be preserved and help Indian steel

companies to grow further. A proper working capital management system ensures the hazard free business operations and

also enhances the profitability of the company. Ramaratnam and Jayaraman (2010) used financial ratios in terms of

liquidity, profitability, variability and sustainability to measure the financial performance of Indian steel industry for a

period of five years from 2005 to 2010. Their study reveals that the critical situation faced by the Indian steel industry is

due to over capacity and demand slowdown resulting in price cuts. The anti-dumping duties imposed by U.S and many

European countries contributed to this demand supply mismatch in the market. Moradi, Salehi and Erfanian (2010) carried

on a research on the corporations listed on Teheran Stock Exchange for a period of seven years since 2002 to 2008 and

applied multiple regression technique to find out the relationship between financial leverage and earning response

Comparative Study of Financial Performance of Indian Steel Companies Under Globalization 3

coefficient. Singapurwoko and Mustofa-El-Wahid (2011) conducted a study on 48 companies listed under Indonesian stock

exchange selected from different industries for a period of seven years to explore the relationship between debt and

profitability. As the direct comparison between debt and profitability is not possible so they applied regression model to

determine the relationship.

OBJECTIVES

1. To compare the financial performance of Indian steel companies under globalization.

2. To establish the linear relationship between liquidity, leverage, efficiency and profitability of the selected

companies.

DATA AND SOURCE OF DATA

The sample of the companies has been chosen on the basis of market share for the year 2009-10. Market share

of the companies are calculated by dividing their respective sales (` in crores) by industry’s total sales and then

multiplying it with 100. Data set of CMIE (2010) is used for the purpose of data collection. All effort have been made to

include a representative samples having more than 1 percent of the market share. With this ten Indian steel companies

(Steel Authority of India, Rastriya Ispat Nigam Limited (now named as Vizag Steel), Tata Steel limited, ESSAR Steel

limited, JSW Steel Limited, JSW Ispat Limited, Jindal Steel and Power Limited, Bhushan Steel Limited, Llyods Steel

Industries Limited and National Steel and Agro Limited) are selected which covered more than 79 percent of the industries

total market share for a period of twenty years since 1991-92 to 2010-11. The market shares of the selected companies are

given in the Table-I.

METHODOLOGY

Multiple regression analysis is conducted on fifteen financial ratios (variables) selected from different segment

like liquidity, solvency, activity and profitability such as current ratio, quick ratio, absolute quick ratio, interest coverage

ratio, debt-equity ratio, raw material turnover ratio, work in progress turnover ratio, finished goods turnover ratio, fixed

assets turnover ratio, sales to compensation ratio, sales to raw materials and stores expenses ratio, sales to selling and

distribution expenses ratio, sales to technical knowhow expenses and return on investment ratio selected from liquidity,

leverage, efficiency and profitability category to reveal the linear relationship between them and also to discover the

variable/variables which mostly influence the overall profitability of the company. The variables (ratios) are retained in the

regression model on the basis of high t value (|t|>2) and low p-value (p<0.05).

ANALYSIS OF DATA

The following table- shows the comparison between the sample companies. There are two companies SAIL and

RINL exists under public sector and TSL, ESL, JSWSL, JSWISL, JSPL, BSL, LSIL, NSAIL belongs to private sector.

After careful examination of the table- it is revealed that ICR is one of the important predictor variables for the regression

model of SAIL, RINL, TSL, JSWISL and LSIL indicates less payment for cost of borrowed capital out of the potential

profit helps to higher the profitability of the companies as the capital structure of the concerned companies contain

balanced amount of debt. The variable FATR provides positive impact on ROI of ESL and NSAIL but negative impact in

case of RINL. Positive impact of FATR means the companies (ESL and NSAIL) are using the fixed assets efficiently

towards sales generation but negative effect of the variable implies that the fixed assets are not being used by the company

(RINL) effectively and investment in the fixed assets for a given period of time fail to push up the sales of the company. So

it can be said that unnecessary investment in fixed assets cause for blockage of money which is ineffective in sales

creation. Therefore, additional investment is not effective to get additional return and profitability of the company is

4 Shrabanti Pal

affected in a negative way. The variable DTR provides positive impact on ROI of JSWISL implying that the company has

formulated a rational credit policy which collects the money from the debtors at the right time and invests it again in the

business. Reinvestment of the assets in the business confirms more returns and profitability of the company increases with

increasing DTR. Negative impact of the variable DTR on ROI in case of SAIL, LSIL and NSAIL indicates that the

company is not following a planned collection policy. Delay in collection from debtors at the right time hinders

reinvestment of the same in the business. Then the company has to retain the collection money in hand thus it is lowering

the profitability of the company. The other two liquidity indicator variables CR and QR are common predictor variables

for SAIL, JSWISL and LSIL. The variable QR gives negative effect on ROI of SAIL and positive impact for the rest of the

companies. Negative impact of QR or CR indicates that the corresponding company retains excess current or quick assets

in hand to pay off current liabilities which obstacle further investment of the same in the business and on the other hand

retaining of current or quick assets in hand increases the operating costs and idle funds and earns no profit thus lowering

the profitability of the company. The existence of positive relationship between liquidity and profitability ratios states that

the company has not yet placed in optimal level of maintaining working capital or it does not use optimal models for

maintaining assets. The variable RMTR is the predictor variables for ESL and JSPL and in case of ESL it provides

negative impact and for JSPL positive impact on ROI. In the recent time business houses manufacture the products on the

basis of market forecast and supply the same to the market according to the demand. Positive association of RMTR with

ROI (JSPL) implies that the supply of the product meets its potential demand for a given period of time generating

increased amount of sales which facilitate to earn more profit for the company. Hence, profitability of the company

increases. But in the case of ESL increased RMTR affects ROI negatively indicating that the production by the company is

not done according to market forecast and for that reason demand and supply mismatch each other and fails to generate

expected sales for the company. When expected sales are not being generated, company slowdowns its production process

which cause an accumulation of inventory in the warehouse. It increases the inventory carrying cost. Since in the modern

supply chain scenario, production plan is designed on market forecast only so the late or pre arrival of finished products in

the market may decrease the sales revenues and profitability of the company.

In case of BSL the positive impact of the variable STSADE implies that the company effectively and efficiently

utilizes selling and distribution expenses to promote sales to earn and generate target profit for the company. But the same

variable provides negative impact on ROI for JSPL indicates that the company is spending excess amount for selling and

distribution purpose but could not successfully achieve the expected sales which can earn more profits for the company.

Excess selling and distribution costs which are charged against the profits reduce the profitability of the company. Another

variable WIPTR is one of the important predictor variables for the company SAIL which is positively associated with ROI

implies that the production plan is efficiently designed based on market forecast and adequate supply meets with potential

demand successfully at a given point of time and eventually able to raise the profitability of the company.

In case of JSPL the other variable STRMASTE is sharing positive relationship with ROI of the concerned

company. It implies that as the company increases its spending on raw materials and stores the production increases

consequently which help to raise the sales volume of the company and facilitate to higher the profitability of the company.

Further production enhances the sales and subsequently the profitability of the company. In case of JSWSL the variable

CTR has positive impact on ROI implies that the company clears its dues to the creditors at the right time which enables it

to acquire more credit from them in future to carry on the production process smoothly and it also facilitates to reduce the

liabilities as a result it needs not to create provision for creditors out of the potential profit. Hence, the profitability of the

company increases. The variable STCR of LSIL has positive association with ROI emphasis that more expenditure towards

Comparative Study of Financial Performance of Indian Steel Companies Under Globalization 5

the employees of the company helps to increase the productivity of them and ensures production hike and profitability of

the concerned company. The R-Square value of each company is highly significant as given by the p-value corresponding

to F-statistic and also confirms the robustness of the models.

SUGGESTIONS

1. The private sector companies namely LSIL, NSAIL along with public sector steel giant SAIL should concentrate

in formulation of working capital management policy which needs a special care as it provides the negative

impact on the profitability of the companies. Too much holding of current or quick assets in hand ensures the

solvency of the company but affect the profitability of the concerned companies in a negative way.

2. The companies must pay a special attention to debtor management. Debtor turnover ratio of SAIL, LSIL, NSAIL

give the negative impact on profitability means either the concerned companies have the slow moving debtors or

the debtors are not paying at right time. Hence, the companies must strike a proper balance between liberal and

tight debtor management policy and should strengthen the collection policy.

3. The variable RMTR affects the overall profitability of the company in a negative way. The concerned company

must focus on the utilization of raw materials in the production process. A very high raw material turnover ratio

not always guarantees high production. But sometimes due to malfunction with the ending raw material inventory

raw material turnover becomes high. Therefore, the company should look after and check the raw materials

physically in store and in process and implement a proper material management policy to make sure the

appropriate use of raw materials towards profit creation.

4. The company JSPL under private sector experienced a negative impact of variable STSADE on the profitability of

the company. It means excess expenses on selling and distribution of the company fails to generate any additional

sales volume thus affect the profitability in a negative way. Hence, JSPL should impose control over the operating

expenses.

5. The other public sector company RINL must takes care in fixed assets management. Fixed assets must put in use

more effectively and efficiently to generate more sales for the company and hence increase the profitability. But

in this case the fixed assets are not intended to increase the sales and the profitability of the concerned company.

Therefore, RINL must pay attention towards their fixed assets management.

CONCLUSIONS

The present study shows that the performance of Indian steel companies is good. But only sales is not the main

determinant for the profit maximization. There are other factors which can influence the profitability of the concerned

company either in a positive or negative way. The present study reveals that the overall profitability depends on the other

financial indicators like liquidity, profitability, activity and financial leverage. So to enhance the profitability the company

the other aspects should be taken care of. Therefore, the companies should concentrate to improve the overall liquidity,

solvency and efficiency to enhance the profitability to the maximum otherwise the profitability of the companies will be

affected in other way.

REFERENCES

1. Bhunia, A. (2010). “A Study of Liquidity Trends on Private Sector Steel Companies in India”, Asian Journal of

Management Research, 1(1):618:628 http//: www.ipublishing.co.in/ajmrvol1no1/EIJMRS1056.pdf; Access on

April 23, 2012

6 Shrabanti Pal

2. Cleary, S. (1999), “The Relationship between Firm Investment and Financial Status”, Journal of Finance, 54(2):

673-692.

3. DeVancy, S.(1993)., “ Change in Household Financial Ratios Between 1983 and 1986: Were American

Household Improving Their Financial Status”, Financial Counseling and Planning, 43(1993),

http://www.6aa7f5e4a9901a1682793cd11f5a6b732d29.gripelements.com/pdf/vol-43.pdf Access on April 22,

2012

4. Eahardt, N.L, Werbel, J.D and Shrader, C.B (2003), “Board of Directors Diversity and Firm Financial

Performance”, Corporate Governance- an International review, 11(2), 102-111.

5. Foarsaith, D., Hall,J., (2000), “Financial Performance and the size of the business”, proceeding of 45th

ICSB

world conference. http://www.uca.edu/research/icsb/2000/04.pdf Access on April 25, 2012

6. Gallizo, Salvador (2003), “Understanding the behavior of financial ratios: The adjustment process”, Journal of

Economics and Business, 55(2003), pp- 267-283.

7. Gulsun, I, Umit, G (2010), “Early Warning Model with Statistical Analysis Procedures in Turkish Insurance

Companies”, African Journal of Business Management, 4(5):623-630.

8. Kavita, Dr. G., Manivanna, Dr. L., (2010), “An Analysis of the Profitability and Liquidity Position of the Selected

Software Companies in India”, JMACADEMY of IT and MANAGEMENT, 1(1): 70-80.

9. Moradi, M., Salehi, M and Erfanian, Z. “A Study on the Effect of Financial Leverage on Earning Response

Coefficient throughout Income Approach: Iranian Evidence”, International Review of Accounting, Banking and

Finance, 2(2): 104-116.

10. Pandey, I.M. (2010), Financial Management, , New Delhi: Vikas Publishing House Pvt. Ltd

11. Raheman, A., Nasr, M. (2007) “Working Capital Management and Profitability-Case of Pakistani Firms”,

International Review of Business Research Papers, 3(1):279-300.

12. Ramaratnam, M.S., Jayaraman, R., (2010), “A Study on Measuring the Financial Soundness of Selected Firms

with Special Reference to Indian Steel Industry-An Empirical View wit Z-Score”, Asian Journal of Management

Research, 1(1): 724-735.

13. Schneider, H.K., Matai, I. (2010), “Business Climate, Political Risk and FDI in Developing Countries”,

International Journal of Economics and Finance, 2(5): 54-65.

14. Singapurwoko, A., Mustofa El-Wahid, (2011), “The Impact of Financial Leverage to Profitability Study of Non-

Financial Companies Listed in Indonesian Stock Exchange”, European Journal of Economics, Finance and

Administrative Science, 32(2011): 136-148.

APPENDICES

Table 1: Market Share of the Selected Indian Steel Companies

Rank Companies Abbreviation Market

Share (in %)

1 Steel Authority of India SAIL 25.27

2 Tata Steel Limited TSL 14.39

3 JSW Steel Limited JSWSL 10.47

4 Essar Steel Limited ESL 6.55

5 JSW Ispat and Steel Limited JSWISL 6.37

6 Rastriya Ispat Nigam Limited RINL 6.12

7 Jindal Steel and Power Limited JSPL 4.40

8 Bhushan Steel Limited BSL 3.24

9 Lloyds Steel Industries Limited LSIL 1.76

10 National Steel and Agro

Industries Limited

NSAIL 1.33

TOTAL 79.90

Comparative Study of Financial Performance of Indian Steel Companies Under Globalization 7

Table 2: Inter-Company Comparison

Sector Companies Predictor

Variables

Beta t-value sig VIF

ICR 1.106 9.899 0 6.346

SAIL R-Square=.974, Adjusted

R-Square=.967,

F=123.876,

Sig=.000,S.E=.0709

WIPTR 0.485 5.311 0 4.238

QR -0.426 -3.618 0.003 7.053

PUBLIC

DTR -0.192 -2.523 0.025 2.946

RINL ICR 1.511 10.466 0 3.577 R-Square=.936, Adjusted

R-Square=.924, F=80.343,

Sig=.000,S.E=.0272

FATR -0.736 -5.122 0 3.577

R-Square=.947, Adjusted

R-Square=.944,

F=318.495,

Sig=.000,S.E=.059 TSL ICR 0.973 17.846 0 1

RMTR -1.032 -6.881 0 1.891

ESL R-Square=.798, Adjusted

R-Square=.774, F=33.568,

Sig=.000,S.E=.0272

FATR 1.193 7.959 0 1.891

R-Square=.861, Adjusted

R-Square=.850, F=74.409,

Sig=.000,S.E=.258 JSWSL CTR 0.928 8.626 0 1

PRIVATE JSWISL QR 0.471 2.069 0.5 3.31

R-Square=.735, Adjusted

R-Square=.685, F=14.773,

Sig=.000,S.E=0.022

DTR 0.834 5.031 0 1.657

ICR 0.611 2.992 0.009 2.516

JSPL STSADE -0.244 -3.782 0.004 1.002

R-Square=.963, Adjusted

R-Square=.950, F=77.018,

Sig=.000,S.E=0.023

STRMASTE 0.929 12.852 0 1.253

RMTR 0.849 12.361 0 1.255

R-Square=.637, Adjusted

R-Square=.616, F=29.856,

Sig=.000,S.E=0.109 BSL STSADE 0.798 5.464 0 1

8 Shrabanti Pal

Sector Companies Predictor

Variables

Beta t-value sig VIF

LSIL ICR 0.351 2.988 0.009 2.184

R-Square=.950, Adjusted

R-Square=.880, F=35.918,

Sig=.000,S.E=0.023

STCR 0.661 6.721 0 1.533

CR 0.359 3.331 0.005 1.847

DTR -0.281 -2.693 0.017 1.73

NSAIL FATR 1.059 4.069 0.001 2.082 R-Square=.545, Adjusted

R-Square=.479, F=8.368,

Sig=.004,S.E=0.095

DTR -0.687 -2.638 0.019 2.082

Appendix-B: FORMULA OF RATIOS USED IN THE STUDY

Category of Ratios Name of Ratios Formula of Ratios

Profitability Return on Investment (ROI) Earnings before interest and tax /Average

Total Assets

Liquidity Current Ratio (CR) Current Assets/(Current Liabilities

Quick Ratio (QR) Quick Assets/ Quick Liabilities

Absolute Quick Ratio(AQR) (Cash and Bank)/Current Liabilities

Leverage and Coverage Debt- Equity Ratio(DER) Total Debt/Net Worth

Interest Coverage Ratio(ICR) Earnings before interest and tax/ Interest

Activity Debtors Turnover Ratio(DTR) Credit Sales/Debtors

Creditors Turnover Ratio(CTR) Credit Purchase/Creditors

Raw Material Turnover

Ratio(RMTR)

Sales/Closing stock of Raw Materials

Work-in-process Turnover

Ratio(WIPTR)

Sales/Closing stock of Work in Process

Finished Goods Turnover

Ratio(FGTR)

Sales/Closing stock of Finished Goods

Assets Management Fixed Assets Turnover

Ratio(FATR)

Sales/ Fixed Assets

Operating Expenses

Management

Sales to Compensation

Ratio(STCR)

Sales/Compensation to Employees

Sales to Raw material and Stores

Expenses Ratio(STRMASTE)

Sales/Raw Material and Stores Expenses

Sales to Selling and Distribution

Turnover Ratio(STSADE)

Sales/ Selling and Distribution Expenses

Sales to Technology Knowhow

Expenses Ratio(STTKE)

Sales/Technology and technical knowhow

Expenses