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- International Journal of Management (IJM)
Volume 9, Issue 4, July–August 2018, pp. 14–23, Article ID: IJM_09_04_003
Available online at
http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=9&IType=4
Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com
ISSN Print: 0976-6502 and ISSN Online: 0976-6510
© IAEME Publication
FINANCIAL PERFORMANCE OF SELECTED
AUTOMOBILE COMPANIES
Dr. G. Kanagavalli
Assistant Professor, Department of Commerce,
Alagappa University, Karaikudi, Tamilnadu, India
R. Saroja Devi
Ph.D Research Scholar, Department of Commerce,
Alagappa University, Karaikudi, Tamilnadu, India
ABSTRACT
The Indian auto industry became the fourth largest in the world with sales
increasing 9.5 per cent year-on-year to 4.02 million units (excluding two wheelers) in
2017. It was the 7th largest manufacturer of commercial vehicles in 2017. The Two
Wheelers segment dominates the market in terms of volume owing to a growing
middle class and a young population. Moreover, the growing interest of the companies
in exploring the rural markets further aided the growth of the sector. India is also a
prominent auto exporter and has strong export growth expectations for the near
future. Overall automobile exports from India grew at 6.86 per cent CAGR between
FY13-18. The present paper measures the financial performance of major selected
automobile companies for the period of 5 years from 2013-2017 by using ratio
analysis. The purpose of the study is to evaluate and compare the financial
performance of selected three companies to rate their financial performances. The aim
of the study is to analyze by comparing the risk of different companies, on their
strengths and weaknesses.
Key words: Financial performance, Automobile Industry, Ratios.
Cite this Article: Dr. G. Kanagavalli and R. Saroja Devi, Financial Performance of
Selected Automobile Companies. International Journal of Management, 9 (4), 2018,
pp. 14–23. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=9&IType=4
1. INTRODUCTION
The automobile sector today is one of the key sectors of the country contributing majorly to
the economy of India. It directly and indirectly provides employment to over 1.5 million
people in the country. A stable government framework, increased purchasing power, large
domestic market, and an ever increasing development in infrastructure have made India a
favorable destination for investment[1]. It is one of the largest sectors in the world, both in
terms of sales volume and production. The Indian automobile industry has a well established
name globally being the second largest two wheeler market in the world, fourth largest
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- Financial Performance of Selected Automobile Companies
commercial vehicle market in the world, and eleventh largest passenger car market in the
world and expected to become the third largest automobile market in the world only behind
USA and China.
The automobile sector facilitates the improvement in various infrastructures like power,
rail and road transport. Due to its deep forward and backward linkages with several key
segments of the economy, the automobile industry is having a strong multiplier effect on the
growth of a country and hence is capable of being the driver of economic growth. It plays a
major catalytic role in developing transport sector in one hand and help industrial sector on
the other to grow faster and thereby generate a significant employment opportunities. In India,
automobile is one of the largest industries showing impressive growth over the years and has
been significantly making increasing contribution to overall industrial development in the
country. The norms for foreign investment and import of technology have also been
liberalized over the years for manufacture of vehicles. At present, 100% foreign direct
investment is permissible under the automatic route in this sector, including passenger car
segment.
The Indian automobile industry proved to be in good shape in the last year even after the
economic downturn. This was majorly due to the fact of renewed interest shown by global
automobile players like Nissan Motors which consider India to be a potential market. The
industry accounts for 7.1 per cent of the country's Gross Domestic Product. The Two
Wheelers segment with 80 per cent market share is the leader of the Indian Automobile
market owing to a growing middle class and a young population. Moreover, the growing
interest of the companies in exploring the rural markets further aided the growth of the sector.
The overall Passenger Vehicle (PV) segment has 14 per cent market share.
2. REVIEW OF LITERATURE
Sheela Christina (2017)[2] carried out the study on Financial Performance of Wheels India
Limited-Chennai. The study deals with Analytical type of research design with the help of
secondary data collection method. For this purpose the researcher took past five years‟ data
and also checked out for the validity and reliability before conducting the study. The
researcher used the following financial tool namely ratio analysis, comparative balance sheet
and DuPont analysis and also statistical tools such as trend analysis and correlation.
Profitability ratios indicate there is a decrease in the profit level, utilization of fixed assets and
working capital in the last financial year. Thus the company can take necessary steps to
improve sales and profit. Finally, the study reveals that the financial performance is
satisfactory.
Neha Mittal (2018)[3] studies the determination of capital structure choice of the selected
Indian industries. The main objective is to investigate whether and to what extent the main
structure theories can explain the capital structure choice of Indian firms. It has applied
multiple regression models on the selected industries by taking data for the period 2009-2017.
It examines the relevance of capital structure in selected Indian industries based on a
regression analysis and data study. It concludes that the main variables determining capital
structure of industries in India are agency cost, assets structure, non-debt tax shield and size.
The coefficients of these variables are significant at one per cent and five per cent levels.
3. STATEMENT OF THE PROBLEM
Evaluating Performance is necessary to understand its strengths and weaknesses to know the
risks and rewards and to find out what changes to make, to achieve higher returns and if
possible with less risk. The purpose of measuring performance evaluation is not to know how
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- Dr. G. Kanagavalli and R. Saroja Devi
the business is performing but to enable it to perform better. As there is an increasing
competition from other global players, the management has to initiate appropriate steps to
lower the cost of production and generation of additional revenues through cost
competitiveness. For this purpose, certain production areas have been identified for cost
reduction. The management can aim at increasing the profit through the following methods:
Optimization of the product mix with a view to enhance the sales revenue and thus, the
profitability of the company.
Increased production of value added products.
Continuous reduction of inventory levels of spare and raw materials.
Implementation of expansion plans as per the fixed schedule with an eye on capturing the
expanding market.
Creating good reputation in customers by providing adequate sales network and enhancing
after sales services.
The purpose of Performance Evaluation is to examine the past and current financial data
so that a company‟s performance and financial position can be measured and evaluated and
future risks and potential can be estimated.
4. SCOPE OF THE STUDY
This present study is concerned with the financial performance of selected automobile
companies. Financial Performance measures whether the company‟s strategy and its
implementation and execution are effectively contributing towards Profitability, Liquidity,
Efficiency and Solvency so that the business can be carried out smoothly ensuring success,
growth and bottom line improvement.
5. OBJECTIVES OF THE STUDY
To study the profile and growth of selected automobile companies.
To analyze the liquidity and solvency performance of selected automobile companies
To measure turnover and profitability performance of selected automobile companies
6. HYPOTHESIS
The hypothesis of the research has been formulated as under:
H1: There is no significant difference between the values of current ratio among the selected
automobile companies.
H2: There is no significant difference between the values of Quick ratio among the selected
automobile companies.
H3: There is no significant difference between the values of Interest Coverage Ratio among
the selected automobile companies.
H4: There is no significant relationship between Net profit, Operating Profit, Fixed Assets and
Net Sales of selected automobile companies.
7. RESEARCH METHODOLOGY
The proposed study is entirely based on secondary data. The data has been compiled from
Annual Reports of the respective companies, Text Books, Reference Books, Journals,
Articles, Magazines and from the Internet. The necessary data has been collected from money
control.com, equity master and Society of Indian Automobile Manufactures (SIAM).
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- Financial Performance of Selected Automobile Companies
Sample Design
The Companies are selected on the basis of top two wheelers and three wheelers
Manufacturers. The researcher has selected three Automobile companies on the basis of
availability of data for the post five years. This sample has been selected for the proposed
research. The following companies have been selected for the study. a) Hero Motocorp
Limited, b).Bajaj Auto Limited, c).TVS Motor Company Limited. The period of study that
has been taken for the research five years i.e. from the financial year 2012-2013 to 2016-
2017.
Ratio Used for Analysis of Data
“Ratio analysis is a widely used tool of financial analysis. It is defined as the systematic use
of ratio to interpret the financial statements so that the strength and weaknesses of a firm as
well as its historical performance and current financial condition can be determined. The term
ratio refers to the numerical or quantitative relationship between two variables”.
Ratio Computed
S.No Ratio Computed Formula
1 Current Ratio Current assets /Current liabilities
2 Quick Ratio Current asset- inventories)/Current liabilities
3 Interest Coverage Ratio EBIT / Interest Expense
4 Proprietary Ratio Shareholders‟ funds / Total Assets
5 Sales to Total Assets Net Sales / Total Assets
Ratio
Liquidity Performance of Selected Automobile Companies
The following table-1 shows that the current ratio and quick ratio of selected automobile
industry.
Table 1 Liquidity Performance of Selected Automobile Companies
Year/ Current Ratio of selected automobile Quick Ratio of selected automobile
Company industry industry
Hero Bajaj Auto TVS Hero Motocorp Bajaj Auto TVS
Motocorp Motor Motor
2013 1.2 1.5 0.9 1.06 1.32 0.48
2014 1.3 1.2 0.9 1.10 1.05 0.52
2015 1.6 3.7 0.9 1.13 1.95 0.47
2016 1.8 1.7 0.8 1.27 1.32 0.45
2017 1.8 2.9 0.8 1.64 2.72 0.39
Mean 1.54 2.2 0.86 1.24 1.67 0.46
Median 1.6 1.7 0.9 1.13 1.32 0.47
S.D 0.27 1.05 0.05 0.23 0.67 0.04
CV 18.13 48.10 6.36 19.00 40.03 9.98
Skewness -0.340 0.791 -0.609 1.68 1.14 -0.067
Source: www.moneycontrol
In the above table current ratio of Hero Motocorp in 2013 was 1.2 , in 2014 was 1.3 and in
2017 was 1.8 follow the Bajaj Auto in 2013 was 1.5 in 2014 was 1.2 and 2017 was 2.9 and
TVS Motor in 2013 was 0.9 in 2014 was 0.9 and 2017 was 0.8. It can be interpreted that
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- Dr. G. Kanagavalli and R. Saroja Devi
current ratio of Hero Motocorp motors, Bajaj Auto is continuously rising and TVS Motor is
continuously declining.
In the above table quick ratio of Hero Motocorp in 2013 was 1.06, in 2014 was 1.10 and
in 2017 was 1.64 follow the Bajaj Auto in 2013 was 1.32 in 2014 was 1.05 and 2017 was
2.72. and TVS Motor in 2013 was 0.48 in 2014 was 0.52 and 2017 was 0.39. It can be
interpreted that quick ratio of Hero Motocorp motors, Bajaj Auto and TVS Motor is
continuously declining.
ANOVA Test of Current Ratio
Table 2 Analysis of Variance – Current Ratio of Selected Automobile Companies
Source of
Variation SS Df MS F P-value F crit
Between
Groups 1.966667 4 0.491667 0.671065 0.626819 3.47805
Within
Groups 7.326667 10 0.732667
Total 9.293333 14
Source: Computed
Table -2 gives the F-value (0.671) is less than the F-critical value (3.478) and P-value is
0.626. It is greater than the alpha level 0.05. Therefore, the null hypothesis is accepted. So
there is no significant difference between the values of Current Ratio among the selected
automobile companies.
ANOVA Test of Quick Ratio
Table 3 Analysis of Variance – Quick Ratio of Selected Automobile Companies
Source of
Variation SS Df MS F P-value F crit
Between
Groups 0.929373 4 0.232343
Within 0.477707 0.751759 3.47805
Groups 4.863719 10 0.486372
Total 5.793092 14
Source: Computed
Table -3 reveal that the F-value (0.477) is less than the F-critical value (3.478) and P-
value is 0.751. It is greater than the alpha level 0.05. Therefore, the null hypothesis is
accepted. So there is no significant difference between the values of Quick Ratio among the
selected automobile companies.
Solvency Performance of Selected Automobile Companies
The following table-4 shows that the Interest Coverage Ratio, Proprietary Ratio and Sales to
Total Assets Ratio of selected automobile industry.
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- Financial Performance of Selected Automobile Companies
Table 4 Solvency Performance of Selected Automobile Companies
Year/ Interest Coverage Ratio Proprietary Ratio of Sales to Total Assets
Company of Selected Automobile Selected Automobile Ratio of Selected
Companies Companies Automobile Companies
Hero Bajaj TVS Hero Baja TVS Hero Bajaj TVS
Motocorp Auto Moto Motocor j Moto Motocor Auto Moto
r p Auto r p r
2013 2.13 3.59 2.8 0.51 0.63 0.25 2.5 1.6 2.2
2014 2.43 5.67 4.6 0.55 0.66 0.03 2.5 1.3 2.3
2015 2.82 6.82 7.2 0.61 0.69 0.27 2.5 1.3 2.1
2016 2.98 5.41 9.2 0.62 0.79 0.31 2.2 1.3 2.2
2017 1.68 3.99 12 0.67 0.82 0.35 1.9 1 2
Mean 2.41 5.10 7.16 0.59 0.72 0.24 2.32 1.3 2.16
Median 2.43 5.41 7.2 0.61 0.69 0.27 2.5 1.3 2.2
S.D 0.52 1.31 3.64 0.06 0.08 0.12 0.268 0.212 0.114
CV 21.82 25.75 50.91 10.19 11.42 51.16 11.566 16.31 5.279
8
Skewness -0.42 0.10 0.19 -0.18 0.41 -1.73 -1.258 0.000 -0.405
Source: www.money control
In the above table Interest Coverage Ratio of Hero Motocorp in 2013 was 2.13 , in 2014
was 2.43 and in 2017 was 1.68 follow the Bajaj Auto in 2013was 3.59 in 2014 was 5.67 and
2017 was 3.99 and TVS Motor in 2013 was 0.51 in 2014 was 0.55 and 2017 was 12. It can be
interpreted that Interest Coverage Ratio of TVS Motor Hero continuously rising and
Motocorp motors, Bajaj Auto is continuously declining.
In the above table Proprietary Ratio of Hero Motocorp in 2013 was 0.51, in 2014 was 0.55
and in 2017 was 0.67 follow the Bajaj Auto in 2013 was 0.63 in 2014 was 0.66 and 2017 was
0.82. and TVS Motor in 2013 was 0.25 in 2014 was 0.03 and 2017 was 0.35. It can be
interpreted that Proprietary Ratio of Hero Motocorp motors, Bajaj Auto continuously rising
and TVS Motor is continuously declining.
In the above table Sales to Total Assets Ratio of Hero Motocorp in 2013 was 2.5, in 2014
was 2.5 and in 2017 was 1.9 follow the Bajaj Auto in 2013 was 1.6 in 2014 was 1.3 and 2017
was 1 and TVS Motor in 2013 was 2.2 in 2014 was 2.3 and 2017 was 2. It can be interpreted
that Sales to Total Assets Ratio of Hero Motocorp motors, Bajaj Auto and TVS Motor is
continuously declining.
ANOVA Test of Interest Coverage Ratio
Table 5 Analysis of Variance – Interest Coverage Ratio of Selected Automobile Companies
Source of
Variation SS Df MS F P-value F crit
Between
Groups 21.29336 4 5.32334 0.550941 0.702988 3.47805
Within
Groups 96.62273 10 9.662273
Total 117.9161 14
Source: Computed
Table -5 gives that the F-value (0.550) is less than the F-critical value (3.478) and P-value
is 0.702. It is greater than the alpha level 0.05. Therefore, the null hypothesis is accepted. So
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- Dr. G. Kanagavalli and R. Saroja Devi
there is no significant difference between the values of Interest Coverage Ratio among the
selected automobile companies.
8. RELATIONSHIP OF PROFITABILITY AND ASSET ON NET SALES
Regression is a statistical technique to determine the linear relationship between two or more
variables. Regression is primarily used for prediction and causal inference. In its simplest
form, regression shows the relationship between one dependent variable (X) and a
independent variable (Y), Regression thus shows us how variation in one variable co-occurs
with variation in another, Regression with shoe size as an independent variable and foot size
as a dependent variable would show a very high regression coefficient and highly significant
parameter estimates, but we should not conclude that higher shoe size causes higher foot size.
It is important to recognize that regression analysis is fundamentally different from
ascertaining the correlations among different variables. Correlation determines the strength of
the relationship between variables, while regression attempts to describe that relationship
between the variables.
X is a Dependent variable, Y is an Independent variable.
X1- Net Profit, X2- Operating Profit, X3 - Fixed Assets and Y - Net Sales.
Table 6 Analysis of Variance of Hero Motocorp
Adjusted
Multiple R
Df SS MS F S R
R Square
Square
Regression 3 15281986 5093995
1.16287 0.577845
Residual 1 4380538 4380538 0.881597 0.777214 0.108855
Total 4 19662524
Constant variable: Net Sales
Table 6.1 Coefficients of Hero Motocorp
Coefficient Standard Lower Upper
s Error t Stat P-value 95% 95%
19470.6881 1.68449 0.34106 166338.61
NETSALES 3 11558.75647 7 1 -127397 4
-
7.98531779 0.83514 375.04033
NET PROFIT 1 30.14477262 -0.2649 6 -391.011 5
OPERATING 1.19738924 0.11943 0.79432 128.58330
PROFIT 1 10.02548898 4 4 -126.189 5
5.85450904 0.43223 0.74027 177.95752
FIXED ASSETS 5 13.54480119 3 1 -166.249 6
Constant variable: Net Sales
The multiple regression analysis indicated in Table No -6 performed based on the enter
method shows that Net Sales have significant impact on Profit and Assets. The overall
method was explained by Net Profit, Operating Profit, and Fixed Assets emerged as
significant variables in explaining the variance in Net Sales. Fixed Assets had a strongest
effect on Net Sales with a Coefficient of 5.85. Furthermore, Net Profit no longer significant
for the Net Sales. Since the significant value is 0.835146 (Coefficient= -7.98). The overall
method was explained by 88% of variance which was statically significant F (3, 1) = 1.1628,
Significant F=0.5778 it‟s greater than 0.05 to predict the Net Sales. Result of regression
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- Financial Performance of Selected Automobile Companies
analysis indicates adjusted R square of 0.1088 and the Significant F=0.5778 (P>0.005).
Hence, the Null hypothesis is accepted at 5% level. So there is no significant relationship
between Net profit, Operating Profit, Fixed Assets and Net Sales.
Relationship of Profitability and Asset on Net Sales in Bajaj Auto Ltd
Ho: There is no significant relationship between Net profit, Operating Profit, Fixed Assets
and Net Sales of Bajaj Auto ltd
H1: There is a significant relationship between Net profit, Operating Profit, Fixed Assets and
Net Sales of Bajaj Auto ltd
Table 7 Analysis of Variance of Bajaj Auto ltd
D Adjusted R
Multiple R R Square
f SS MS F S Square
Regressio 156447 0.95768311 0.91715694
n 3 4693425.86 5 4 7
423938.049 3.69033 0.36134 0.66862778
Residual 1 4 423938 9 5 8
5117363.90
Total 4 9
Constant variable: Net Sales
Table 7-1 Coefficients of Bajaj Auto ltd
Coefficient Standard Lower Upper
s Error T Stat P-value 95% 95%
57016.7689 1.61099 0.35365 506717.29
NET SALES 5 35392.19868 8 8 -392684 1
-
3.34692974 - 0.39110 26.651987
NET PROFIT 6 2.360965961 1.41761 7 -33.3458 1
OPERATING 2.90605 0.21098 19.574152
PROFIT 3.64352136 1.253767857 7 7 -12.2871 4
-
19.0314219 - 0.41828 167.50010
FIXED ASSETS 8 14.6803499 1.29639 5 -205.563 9
Constant variable: Net Sales
The multiple regression analysis indicated in Table No 6.1.8 performed based on the enter
method shows that Net Sales have significant impact on Profit and Assets. The overall
method was explained by Net Profit, Operating Profit, and Fixed Assets emerged as
significant variables in explaining the variance in Net Sales. Operating Profit had a strongest
effect on Net Sales with a Coefficient of 3.64. Since the significant value is 0.418285
(Coefficient= -19.031). The overall method was explained by 95% of variance which was
statically significant F (3, 1) = 3.690339, Significant F=0.361345 it‟s greater than 0.05 to
predict the Net Sales. Result of regression analysis indicates adjusted R square of 0.66862 and
the Significant F=0.5778 (P>0.005). Hence, the Null hypothesis is accepted at 5% level. So
there is no significant relationship between Net profit, Operating Profit, Fixed Assets and Net
Sales.
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- Dr. G. Kanagavalli and R. Saroja Devi
9. CONCLUSION
Ratio analysis helps to compare the financial statements of the firms and comparison of
financial performance also investigated over a period of time. Firms have made use of more
borrowed funds. The study found that there is the positive strong relationship of liquidity
ratio. It evolves the effective inventory management and conversion period leads to higher
liquidity power to the companies. Therefore, the study proves that there are some significant
changes to meet their liabilities. The Solvency Ratios of selected automobile companies have
some fluctuation. This means they face a little risk to meet their long term obligations. The
Efficiency or Turnover Ratios of Hero Motocorp is high rank among other Automobile
companies. This shows that Hero Motocorp effectively manages its resources and assets. The
Profitability Ratios of Hero Motocorp is higher than other automobile companies. It shows
Hero Motocorp earned high profit and it is good for the company. After analyzing all the
aspects, concern with this research, we can say that Bajaj Auto and TVS Motors are
satisfactory but Hero Motocorp sustains a good position in the market. Hence share holders
can invest their share daringly. They can get wholesome return and their shares will be safe
and secured.
KEY NOTES
1. www.ibef.com
2. Sheela Christina (2017) the study on Financial Performance of Wheels India Limited-
Chennai.
3. Neha Mittal (2018), “Determinants of capital structure of Indian industries”, Journal of
Accounting and Finance, Volume 25, No: 1, PP.32-40.
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http://www.iaeme.com/IJM/index.asp 23 editor@iaeme.com
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