Stock Market Performance and Fundamentals of top Infrastructure Companies in India

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NICMAR
PROJECT SEMINAR REPORT ON
AN ANALYSIS OF STOCK MARKET
PERFORMANCE AND FUNDAMENTALS OF
INFRASTRUCTURE COMPANIES IN INDIA
By
NITESH PATTNAIK (AH16076)
SHASHANK SRIVASTAVA (AH16107)
YASH SACHDEV (AH16124)
PGP ACM 30th Batch
(2016- 2018)
Post Graduate Programme in Advanced Construction
Management (PGP ACM) – VII Term
NATIONAL INSTITUTE OF CONSTRUCTION
MANAGEMENT AND RESEARCH, HYDERABAD

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ACKNOWLEDGEMENT
We express our sincere and heartfelt thanks to Dr. P.H. Rao, NICMAR, HYDERABAD for his
constructive support, constant encouragement, guidance and challenging efforts in the right
direction without which this thesis would not have attained the present form.
We express a deep sense of gratitude to Dr. Rajiv Gupta, Head ACM Hyderabad, for giving
the opportunity to undertake this subject for study.
At last, we would like to thank various staffs, key authors and other personals for helping us in
attaining the final objective of the study.
NITESH PATTNAIK (AH16076)

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DECLARATION
We declare that the project seminar report titled “An Analysis of Stock Market Performance
and Fundamentals of Infrastructure Companies in India” is bonafide work carried out by us,
under the guidance of Dr P.H. Rao. Further we declare that this has not previously formed the
basis of award of any degree, diploma, associate-ship or other similar degrees or diplomas, and
has not been submitted anywhere else.
Date: 12th
February, 2018 NITESH PATTNAIK (AH16076)
PGP ACM 30th (2016-2018)
NICMAR -Hyderabad

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CERTIFICATE
This is to certify that the project seminar on “An Analysis of Stock Market Performance and
Fundamentals of Infrastructure Companies in India” is bonafide work of Nitesh Pattnaik,
Shashank Srivastava and Yash Sachdev in part of the academic requirements for the Seventh
term of Post Graduate Programme in Advanced Construction Management (PGP ACM). This
work is carried out by him/them, under my guidance and supervision.
Date: 12th February, 2018 Name of the Guide & Signature
Dr. P.H. Rao
Name of the Head & Signature
Dr. Rajiv Gupta

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EXECUTIVE SUMMARY
Infrastructure Industry in India have been experiencing stupendous growth in its diversified
sectors with the development and growing urbanization and increasing involvement of foreign
investments in this field. The current scenario of Infrastructure industry in India is positively
concerned of developing and creating better Infrastructure to provide benefits of those to the
general public for their living standards, wellness and aims to know that Infrastructure
companies are better in growth and how customers know about to invest in better Infrastructure
company. Moreover, there is a downfall in some Infrastructure companies in terms of
profitability and stock value at the same time. This report aims at evaluating the financial
policies, reasons behind them, models and their impact on the stock market value of various
Infrastructure Organizations in India. This study also concerns with their comparison in order
to conclude the strongest and the safest organization to invest in.

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CONTENTS
S.No Title Page No
1. Introduction 8
1.1 Topic Definition 9
1.2 Objectives of the study 10
1.3 Scope of the study 10
2. Literature Review 11
3. Methodology 20
4. Experimental Analysis 27
4.1 Stock market performance 36
4.2 Fundamentals of Finance 44
5. Conclusion and future scope 51
6. References 52

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LIST OF TABLES
S.No Title Page No
1. Sectors attracting Highest FDI equity inflows in India 10
2. CDGR of companies with respect to Sensex 28
3. CAGR and CDGR 36
4. Coefficient of variation 36
5. Z test of Various Companies 37-41
6. ANOVA 42
7. Correlation 43
8. Various ANOVA tests for Fundamentals of Finance 44-50

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CHAPTER – 1
INTRODUCTION
Development of Indian economy is unattainable without sustainable inclusive economic
growth. Infrastructure is one of crucial pillars of productivity in any economy. Broad definition
of infrastructure includes Electricity, R&M of Power Stations, Non-Conventional Energy,
Water supply and Sanitation, Telecommunications, Roads & Bridges, Ports, Inland Waterways,
Airports, Railways, Irrigation, Storage & Gas Pipeline Networks. It not only attracts foreign
direct investment, but also affects economic growth and reduces poverty In India. At present,
the construction sector is the second most employing sector (after agriculture), contributing
about 35 million workforce and 8 percent of the GDP, majority of which comes from the
Infrastructure sector. This depends upon the quality of infrastructure, which is one of the crucial
drivers of productivity of an economy. Lack of quality Infrastructure is the most problematic
factor in India for doing business (The Global Competitiveness, 2014). It also acts an
imperative role for attracting foreign direct investment (Sharma, Nayagam & Chung,
2012). Most of the infrastructure development sectors moved forward, but not to the required
extent of increasing growth rate up to the tune of 8 to 10 per cent. The Organization for
Economic Co-operation and Development (OECD) estimated in 2009, that total new spending
for infrastructure over the period of twenty year, (2010-2030) would be US $ 71 Trillion or
about 3.5% of world GDP. The World Economic Forum’s Positive Infrastructure Report found
that India faces a global infrastructure deficit of US $ 2.7 trillion per year over the next 20
years. There was improved investment in physical infrastructure in GDP during the 12th
Five
Year plan. On the quality of infrastructure, India ranks 87 out of 144 countries (The Global
Competitiveness, 2014). The problem of public financing of infrastructure is a topic on top of
policymakers’ agendas worldwide. Budget constraints, past experiments of poor public
spending and inefficiencies in managing infrastructure on the public side have led to a
reconsideration of the need to shift the investment effort to the private sector and to the
development of Public Private Partnerships (PPPs). However, the gap to be filled is
remarkable.
Since the evolution of various policies, both from the government and organizations, a
substantial progress in terms of profitability has been achieved during the recent years. But a
major portion of organizations are incurring heavy losses, either due to the improper planning,
policy making or implementation. Stock prices have gone down to an alarming level, thereby

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a new level of efficiency in all the aspects is required. As per the concern of a normal
shareholder, it is difficult to assess that which organization to be considered as safe for
investment. As very meagre information is revealed about the ongoing projects and their
respective status on wealth generation, it is essential to evaluate the finances and stock market
performance, along with their policies. Table 1.1 shows the sectors attracting highest FDI
equity in India.
1.1 TOPIC DEFINITON
1.1.1 Stock Market Performance: Stock Market Performance is the
indicator of the stock market as a whole or of a specific stock. It gives
signal to the investors about their future moves. The movement in the
price of a stock and the indexes gives the idea of the near future trend of
the stock, sector or the economy as a whole. As financial domain is the
most important one of an economy, so the stock market performance
works as an indicator of the overall health of the economy.
1.1.2 Financial Performance: Financial performance is a subjective measure
of how well a firm can use assets from its primary mode of business and
generate revenues. This term is also used as a general measure of a firm's
overall financial health over a given period of time, and can be used to
compare similar firms across the same industry or to compare industries
or sectors in aggregation.
Table 1.1. Sectors attracting Highest FDI equity inflows in India

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1.2 OBJECTIVES OF THE STUDY
The objectives of the study are as follows:
 To analyse the stock market performance of Infrastructure companies in the present
scenario.
 To examine the fundamentals of Infrastructure companies in India
 To carry out the fundamental analysis on various aspects of Infrastructure companies
in India
 To carry out the technical analysis on Infrastructure companies in India
 To forecast the future share price and position of the Infrastructure companies in
India.
1.3 SCOPE OF THE STUDY
 This study is having a significant scope in estimating the future market condition of
the various infrastructure players across the country.
 It can be helpful for evaluating the operational efficiency of the organizations.
 It can be effectively utilized for calculating the short and long term financial position
of the organizations.
 It can be used to symbolize the trends of achievement
 It is possible to utilize this study for better understanding of the parameters required
to achieve profitability
 It can be effectively utilized by the potential investors for comparative evaluation of
Infrastructure sector.
 It can be useful for improving the financial model and key policies to attain and
maintain the profitability in the long run.

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CHAPTER – 2
LITERATURE REVIEW
Pankaj Soni (2015) in their study of “Fundamental Analysis of Cement Sector” stated that the
Fundamental analysis is based on Economic, Industry and Company (EIC) Analysis. The paper
also develops a Multi-Regression Model for finding values of Cement Company’s share prices
(Dependent Variable) through 4 parameters that is SENSEX, IIP, CPI and Realty Index
(Independent Variable). For this regression analysis was done on monthly share prices and
other variables from last 5 years and was tested. His motive is to find out which stock is good
for investment based on the fundamental analysis, to develop a statistical model of share prices
and index and its correlation, to test the model based on real time data available.
Data has been collected through secondary sources. Most of the data are historical in nature.
Previous five years data has been collected for this project. The data has been collected from
company financial report, historical data from NSE India, company’s websites and various
broking sites etc. The ratios of the companies have been calculated with help of balance sheets
and P&L account.
Data has been analysed with the help of ratios and percentages. For financial analysis
company’s financial statements have been studied and ratios are computed out of it. Statistical
tools like averages, standard deviation, and correlation and regression equation are also used.
Microsoft Excel has been used for data analysis tools. Data of four companies have been used
for study. The regression model is also developed using the stock price data of these three
companies. The three companies have been selected based on its Net Profit of 2012-13.
Following cement companies were selected:
a) Ultratech Cement
b) Ambuja Cement
c) ACC Cement
d) Shree Cement
The model worked. Then, it was applied in two scenarios- Boom and Recession to know the
future share prices of companies and which stock is best to invest.

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Ibn-Homaid N. T. & Tijani I. A. in their study of “Financial Analysis of a Construction
Company in Saudi Arabia” (2015) stated the role of financial management in determining the
financial status a construction company in Saudi Arabia, present a failure prediction model for
the company based on the previous business data available, method to recognize business
failure at the earliest stage in order to reduce the economic damages and estimate the
probability of failure conditional on a range of firm characteristics based on a certain
assumption concerning the probability distribution. This study uses financial ratio to analysis
the financial record of a construction company in Saudi Arabia to predict its financial health
status. The ratio is compare with industry’s standard average over a long period of time.
Financial records of the construction company were obtained from Saudi stock exchange
market which is analyzed for five consecutive years and they found out that Based on the
financial record obtained from Saudi stock exchange market, financial ratios were computed
and compared with proposed Peterson’s (2009) median and range for heavy and highway
construction industry. The analyses of financial ratios were grouped into four categories, which
is as follows: liquidity, profitability, leverage and efficiency.
These four ratios is efficiently in determining the failure or success of Construction Company
as it was shown in the analysis above. Its hope that construction firm in Saudi Arabia will adopt
this as a benchmark in predicting the financial status of their business
Ibn-Homaid N. T. & Tijani I. A. in their study of “Assessment of Financial Condition: A Case
Study Of Saudi Construction Companies” (2017) aimed to assess the financial condition of
some selected Saudi construction companies. The study adopts the published financial
statements of the construction companies listed on Saudi Stock Exchange Market. Traditional
financial ratios were employed as assessment tools, necessary financial data concerning the
ratios were extracted and saved in Microsoft Excel spreadsheet for the analysis of the financial
ratios, and these were compared to the industry’s typical median and range. Subsequently, a
null hypothesis test was conducted using SPSS 22, to statistically test that there is no
significance difference between the companies’ median and industry median. The analysis
reveals that two companies are financially satisfactory and the third company is in financial
distress. However, the companies’ financial condition can be enhanced if they are able to
manage the companies in such a way that there’s increase in their revenues, reduces general
overhead costs and adequate debt management. They have selected three construction
companies from the building and construction section of the Saudi Stock Exchange Market
(SSEM). In the context of this study, the companies were named A, B and C respectively. The
primary activities of these companies are development and construction services. Sixty

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financial statements were collected from the selected companies. Data were downloaded using
case study research protocols (Yin, 2003). This includes the use of multiple data sources, where
possible, to ensure the quality of the data collected. The financial data were based on quarterly
accounting report spanning from the first quarter of year (2011) to the last quarter of year 2015.
Some quarterly accounting report was published in Arabic language; these were translated to
English language accordingly. This study uses industry average published in Peterson (2009)
for the appraisal of the selected companies. Data regarding the aforementioned financial ratios
were extracted from the collected financial statements. Microsoft Excel Sheet were used for
computation of the financial ratios. Subsequently, in interpreting these ratios, companies’
financial ratios were compared with construction industry’s typical median and range published
in Peterson (2009).
Since construction industry is a project-oriented industry that is characterized with unique
financial conditions. This research suggests that the companies’ financial assessment should
be a dynamic process, so it is important to systematically perform and evaluate this process at
regular intervals. Further studies should be conducted to validate and improve the assessment
technique used in this study. To assess the financial condition of some selected Saudi
construction companies.
Bockova and N.Zizlavsky.O in their study of “Innovation And Financial Performance Of A
Company: A Study from Czech Manufacturing Industry” (2016) investigates the impact of
innovation on the financial performance of a company. Its aim is to explore the relationship
between innovation and performance of large companies in Czech manufacturing industry. The
data was obtained from the Amadeus Bureau Van Dijk Electronic Publishing database and the
Czech Statistical Office Database in the period of 2007 to 2014.They tested whether
companies, which invest into innovation, achieve stronger financial performance and are better
able to respond to an economic crisis. The results of a Mann-Whitney U test showed that the
long-term financial performance of investigated companies is closely linked to their investment
into innovation. Moreover, the authors of this article found that long-term innovations vary the
ability of the company to succeed in the post-crisis period. The median value of companies
with R&D expenditures proved an ability to regain the original value of profitability ratios
ROE and ROA earlier than companies without R&D expenditures. This paper is built on the
fourth approach – R&D Expenditures. The first step is to define the research sample. The
choice is related to the manufacturing industry in the Czech Republic due to the fact that the
manufacturing industry is considered to be the most significant industry for the development

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of Czech economics since it is the largest sector of the Czech economy. This paper refers to
the applied research in the for-profit sector since this approach is closely related to the
innovation definition provided by the Oslo Manual (OECD, 2005) and manufacturing industry.
The research focuses on large companies (>250 employees) due to the fact that they are
considered to be innovation leaders, both in the Czech Republic (CZSO, 2014) and globally
(OECD, 2009). In addition, it is argued that large companies are in a better position to carry
out the R&D necessary for the innovation and may also be better placed to exploit the market
potential of each innovation (Love, Roper, 1999) as well as the possibility of employing
professional managers and technical experts, better protection of innovation.
This study analyzed the long-term structure of the relationship between R&D expenditures,
selected profitability ratios and ratios per employee in a small open economy, namely the Czech
Republic. The assumption stated at the beginning of our research that large companies with
R&D expenditures will have a higher economic performance (as measured by two profitability
ratios and two ratios per employee) than non-innovative companies, was confirmed over a long
period. The analyzed data from the research sample indicates that the average value of the ROE
and ROA for large companies in the long term is lower than the average value for the
manufacturing industry. It was found that over the long-term innovative activities alter the
ability of the company to succeed in the post-crisis period. The median value of the companies
performing innovations (measured by profitability ratios ROE and ROA) proved that these
companies reached original value earlier than the companies without innovative activities.
Furthermore, there is the need for qualitative research in investigated branches of
manufacturing industry. It is important to learn more about the motives for innovations and
how the impact on company’s economic performance depends on these motives.
Halim, Juosh, A. Dba and Amlus have made their study on “Determining the Financial
Performance Factors among Bumiputera Entrepreneurs in Malaysian Construction
Industry” (2014). They stated that to identify the financial factors determining the success or
failure of contracting firms in the Malaysian construction industry, researchers in the
construction industry have addressed three main factors that have caused the failure of
contracting firms in their operations, namely, shortage of funds, low profits, and debt. Previous
literature indicates that the rate of failure among construction firms is higher than that in other
sectors. The methodology employs the quantitative approach to achieve its objective.

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The study mailed 250 questionnaires to selected contracting firms. The results showed that the
negative reputation of failed contracting firms are influenced by ten factors, including
increased prices of raw materials during construction, low contract price, projects not
completed within the agreed time, small capital, delayed deposit from clients, relying on
creditors to fund projects, difficulty in acquiring loans, delay in receiving progress payments,
exorbitant financial costs, and small capital. These ten main factors are drawn from three main
categories, namely, small profit, shortage of capital, and debt burden.
A total of 20 probable causative factors related to finance are listed under three categories:
Lack of capital, small profit, debt burden. Questionnaires are distributed among respondents
with the intention of obtaining their opinions regarding the factors listed. Assessments are
based on the mean scores of the factors. The results show that “small profit” is the main cause
of failure in contractor firms, followed by “lack of capital” and “debt burden.”
They stated that to identify the financial factors determining the success or failure of
contracting firms in the Malaysian construction industry, researchers in the construction
industry have addressed three main factors that have caused the failure of contracting firms in
their operations, namely, shortage of funds, low profits, and debt. Previous literature indicates
that the rate of failure among construction firms is higher than that in other sectors. The
methodology employs the quantitative approach to achieve its objective. The study mailed 250
questionnaires to selected contracting firms. The results showed that the negative reputation
of failed contracting firms are influenced by ten factors, including increased prices of raw
materials during construction, low contract price, projects not completed within the agreed
time, small capital, delayed deposit from clients, relying on creditors to fund projects,
difficulty in acquiring loans, delay in receiving progress payments, exorbitant financial costs,
and small capital. These ten main factors are drawn from three main categories, namely, small
profit, shortage of capital, and debt burden.
A total of 20 probable causative factors related to finance are listed under three categories:
Lack of capital, small profit, debt burden. Questionnaires are distributed among respondents
with the intention of obtaining their opinions regarding the factors listed. Assessments are
based on the mean scores of the factors. The results show that “small profit” is the main cause
of failure in contractor firms, followed by “lack of capital” and “debt burden.”

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S. M. Tariq Zafar, D. S. Chaubey and Adeel Maqbul have analysed in their study of “A Study
on Fundamental Analysis of Infrastructure Industry in India” that the various factors of the
industry like cost structure & profitability, government policy, competition, labour & R&D and
economic factors like foreign exchange position, inflation, interest rate, deficit slowdown &
taxation whether it impact on the fundamentals of the company or not. The core objective of
this study is to evaluate the past performance and the expected future performance of
companies, to analyse the profitability position of the companies and to analyse the various
ratios of the past five years of sample companies based on market capitalization. The present
study adopts analytical and descriptive research design with convenience sampling based on
the secondary data collected from the annual reports and the balance sheet, published by the
companies’ respective websites. Five Infrastructure companies are chosen as sample size of the
study, on account of having lowest market capitalization. Survival of the companies largely
depends on satisfaction of their investor and consumers for whom they are in business.
Certified investor will take risk in future and would like to invest in companies from whom
they are in advantage. Companies with positive ratio have to develop more efficiency in their
approach and companies who are average and below average have to explore their effort with
optimum utilization of their available resources. Survival of the fittest is the ultimate universal
law.
M. Valliappan, (2015) in his study titled “Risk bearing ability of investors in Indian stock
market” stated that the ability to invest a substantial amount of money in India depends on
various approaches adopted by the Investors. His objectives were to know the investment
pattern of Indian equity investors in general and investment preference viz. risk-return
perception to a limited level, to find the part of savings that an investor is ready to invest in
stock market out of his income, to analyze the level of importance assumed by the retail equity
investors on various investment objectives based on the socio economic variables and selective
demographic profile of investors. For this evaluation, Descriptive research design was used to
collect primary data from 303 investors of Indian Equity Market through structured
questionnaire using convenience sampling method. The statistical tools used in analysis were
One Way ANOVA, Percentage Analysis, Kruskal-Wallis H test and weighted average. The
period of the study was from April 2014 to March 2015. A pilot survey was done with 30
investors for refinement of research process. He found out that Majority of the investors were
normal traders who are not ready to take more risk. Lack of knowledge about market is the
very big difficulty faced by investors in equity market. Few high end customers face high

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brokerage charges as a difficulty. The academic qualification influences the overall knowledge
of the investors. Overall knowledge of investment depends on Gender. Risk Capability of
investors does not depend upon their educational qualification. Majority of the investors in
stock market are teen agers between the age group of 18 – 28. As most of the investors are
teenagers who were investing in stock market their overall experience in stock market is also
not more than a year. The majority of investors make investment in stock market for the
purpose of future requirements. Investors mostly seek advice from the stock brokers before
making their investment. Investor’s perception towards stock market was that they were not
prepared to invest in stock market given their annual income. Most of the investors dealing in
equity were tax payers. Amongst the investors surveyed, 91.7% of them invest in equity market
directly. Investors in equity market were ready to invest only up to 10% of their annual income
in equity market. As the risk is high in equity market objective of most of the investors is to
save 11% to 20% of their investment. Banking sector is the most preferable sector by most of
the respondents to make equity investment.
Prof. Madhavi (2014), in her paper titled “An evaluating study of Indian stock market
scenario with reference to its growth and inception trend attempted by Indian investors:
relation with LPG” stated that the fluctuations are increased in the Indian stock market with
respect to risk and return relationship. Her objectives were to analyse the conditions of stock
market with relation to the financial factors impacting it, to know the trend of Indian stock
market, to study the volatile trends for securities on Indian stock market after globalization and
to analyze risk management measures adopted for securing safe return. For implementation,
Secondary data has been used in the form of reports of RBI Bulletin, Journals, websites of BSE
and NSE, various news channels. It was been studied that Fixed capital formation was having
the increasing trend since concept of globalization was introduced in the economy. India was
showing positive trend, beside than that china shows rise in their GDP growth rate that was
definitely due to their trade policies. It was studied that year by year number of registered
companies were increasing in SEBI, which was very high in the period of 1996 that is duration
of globalization. That is clear indication of positive results of LPG policies because of that
listed companies were doubled in short mean time. It was studied that year by year number of
registered companies were increasing in SEBI, Which was very high in the period of 1996 that
is duration of globalization. That is clear indication of positive results of LPG policies because
of that listed companies were doubled in short mean time. Measures adopted by Indian
government, RBI, SEBI time by time in order to stabilize the Indian capital market and
movement of funds resulted in very effective manner. She found out that stock market was very

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volatile and fluctuating with respect to risk and return relationship. In stock market incomplete
information leads to bad return whereas perfection and alertness leads to good and stable return.
It was found that higher the risk higher the return and vice versa. LPG and steps taken by the
government, RBI has surely given the direction as well as motivation to investor to invest more
and more in capital market which has definitely improved the growth of Indian economy. There
are a lot of risk management alternative available to the investors with which help risk can be
minimized and return can be increase. Future of stock market was found very bright in
upcoming years due to competitive strength.
Swarupa Panigrahi and Dhananjay Beura (2013), in their study titled “An Exploratory Study
on Infrastructure Financing in India” stated that resource constraint is the critical factor for
infrastructure deficit in India. Their objectives were to examine resource constraint is the
critical factor for infrastructure deficit in India, to identify stable exchange rate, mild inflation,
clarity of taxation rules, fiscal discipline & sustainability of economic policy create investment
climate in India. This case study stated that public private partnership model is the best model
as infrastructure is concerned but effectiveness of this depends upon maturity of domestic bond
market & infrastructure pricing policy. They found out that an essential criterion for any
country lies on its own financial market. Without of maturity of the financial market investment
in infrastructure is difficult to achieve. Future researchers may examine the “Role of
Infrastructure Pricing in Private Participation” & “Role of Financial Market in Infrastructure
Development”. “Make in India” will be dream if there is lack of proper infrastructure.
However, if we want to convert into reality, we must focus huge investment in infrastructure.
Pritesh Panchal (2015), in his study entitled “Liquidity Analysis of Selected Infrastructure
Companies: A Comparative Study” stated that liquidity position of the selected infrastructure
companies can be observed by making use of liquidity ratio such as current ratio and quick
ratio. His objectives were to analysis the liquidity position of the selected infrastructure
companies, to analysis the liquidity position of the selected infrastructure companies by making
use of liquidity ratio such as current ratio and quick ratio for the time spanning from 2011 to
2015, to Study the Liquidity positions of three selected infrastructure companies, i.e. Reliance
infrastructure ltd, IRB infrastructure ltd and Jaypee infrastructure ltd. For these purposes, he
calculated the current and quick ratio for the companies. He found out that through the present
study researcher conclude that the liquidity ratio of Jaypee Ltd and IRB Ltd is better but, when
we see in current ratio Jaypee Ltd is better. Like current ratio, in quick ratio there is IRB Ltd is
better than other two companies so, other companies need to improve their liquidity position

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for better performance. It can be concluded that liquidity is concerned to improve the
profitability.
Dr. Keyur M Nayak (2013), in his study titled “A study of random walk hypothesis of selected
scripts listed on NSE”, stated that Infrastructure sector is growing very fast now days in Indian
economy. The result of this study indicates that scrip prices of companies from this sector
cannot be predictable as the return series in infrastructure sector is not random. So the investor
cannot predict the price of this sector companies on the basis of its past prices as its follow
random walk. His objectives were to test the validity of RWH (Random walk hypothesis) in
the FMCG sector power sector, the infrastructure sector, banking sector and automobile sector.
For this purpose, he took the data from companies present in the respective sectors and analyzed
the same by using SPSS and Z test. He found out that in Infrastructure sector it is been found
that scripts of all companies rejected the null hypothesis that is the return series in Infrastructure
sector is not random. Scripts of this sector does not follow certain pattern in its prices therefore
investor cannot predict its prices and cannot get benefit of past pieces. It is been found that the
scrip prices of companies from this sector cannot be predictable as the return series in
infrastructure sector is not random. So the investor cannot predict the price of this sector
companies on the basis of its past prices as its follow random walk. The returns of all the scrips
which are examined in this study cannot be predicted by the investors by using the historical
information of the scrips. The reason being that scrips of these companies do not follow certain
pattern.

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CHAPTER – 3
METHODOLOGY
A sample of top 10 infrastructure companies in India based on market capitalization will be
studied. The share prices of Indian infrastructure companies for 52 weeks will be graphically
and statistically analysed. Various statistical tools like Mean, Standard Deviation, Coefficient
of Variation, etc. will be applied to the sample. Moreover, Regression models will be developed
for forecasting purposes. The sample of companies chosen are as follows:
 Larsen & Toubro (L&T)
 GMR Infrastructure
 Jaypee Infrastructure
 Reliance Infrastructure
 LANCO Infrastructure
 IRB Infrastructure
 IL&FS Infrastructure
 Hindustan Construction Company (HCC)
 NCC Ltd
 GVK Infrastructure
The key financial variables like EPS, DPS, P-E RATIO, ROI, ROCE, etc. will be examined for
the last 5 years with each of these companies to understand the fundamentals of the sample
companies
Technical analysis and fundamental analysis will be applied for each of these companies to
understand how the companies will be performing in the near future. In addition multiple
regression model will be used for forecasting the share prices in the sector.
Various important terms related to the study are as follows:
 Stock Market: The stock market refers to the collection of markets and exchanges
where the issuing and trading of equities (stocks of publicly held companies), bonds
and other sorts of securities takes place, either through formal exchanges or over-the-
counter markets. Also known as the equity market, the stock market is one of the most
vital components of a free-market economy, as it provides companies with access
to capital in exchange for giving investors a slice of ownership.

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 Stock Market performance: The study of stock market and its various trends to
predict various outcomes, generally by means of statistical analysis, is termed as stock
market performance.
 Growth rate: Growth rates refer to the percentage change of a specific variable within
a specific time period, given a certain context. For investors, growth rates typically
represent the compounded annualized rate of growth of a company's revenues,
earnings, dividends and even macro concepts such as GDP and the economy as a whole.
Expected forward-looking or trailing growth rates are two common kinds of growth
rates used for analysis.
 Compounded Annual Growth Rate: The compound annual growth rate (CAGR) is
the mean annual growth rate of an investment over a specified period of time longer
than one year. To calculate compound annual growth rate, divide the value of an
investment at the end of the period in question by its value at the beginning of that
period, raise the result to the power of one divided by the period length, and subtract
one from the subsequent result.
The compound annual growth rate isn't a true return rate, but rather a representational
figure. It is essentially a number that describes the rate at which an investment would
have grown if it had grown at a steady rate, which virtually never happens in reality.
CAGR can be interpreted as a way to smooth out an investment’s returns so that they
may be more easily understood.
 Statistical Analysis: Statistical analysis is a component of data analytics. In the context
of business intelligence (BI), statistical analysis involves collecting and scrutinizing
every data sample in a set of items from which samples can be drawn. A sample, in
statistics, is a representative selection drawn from a total population.
Statistical analysis can be broken down into five discrete steps, as follows:
o Describe the nature of the data to be analysed.
o Explore the relation of the data to the underlying population.
o Create a model to summarize understanding of how the data relates to the
underlying population.
o Prove (or disprove) the validity of the model.
o Employ predictive analytics to run scenarios that will help guide future actions.

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The goal of statistical analysis is to identify trends. A retail business, for example, might
use statistical analysis to find patterns in unstructured and semi-structured customer data
that can be used to create a more positive customer experience and increase sales.
 Current ratio: The current ratio measures the short-term solvency of the firm. It
establishes the relationship between current assets and current liabilities. It is calculated
by dividing current assets by current liabilities.
Current Ratio = Current Assets/Current Liabilities
Current assets include cash and bank balances, marketable securities, inventory, and debtors,
excluding provisions for bad debts and doubtful debtors, bills receivables and prepaid
expenses. Current liabilities includes sundry creditors, bills payable, short- term loans, income-
tax liability, accrued expenses and dividends payable.
Significance and interpretation
Current ratio is a useful test of the short-term-debt paying ability of any business. A ratio of
2:1 or higher is considered satisfactory for most of the companies but analyst should be very
careful while interpreting it. Simply computing the ratio does not disclose the true liquidity of
the business because a high current ratio may not always be a green signal. It requires a deep
analysis of the nature of individual current assets and current liabilities. A company with high
current ratio may not always be able to pay its current liabilities as they become due if a large
portion of its current assets consists of slow moving or obsolete inventories. On the other hand,
a company with low current ratio may be able to pay its current obligations as they become due
if a large portion of its current assets consists of highly liquid assets i.e., cash, bank balance,
marketable securities and fast moving inventories. Consider the following example to
understand how the composition and nature of individual current assets can differentiate the
liquidity position of two companies having same current ratio figure.
 Quick Ratio: It has been an important indicator of the firm’s liquidity position and is
used as a complementary ratio to the current ratio. It establishes the relationship
between quick assets and current liabilities. It is calculated by dividing quick assets by
the current liabilities.
Quick Ratio = Quick Assets/ Current liabilities

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Quick assets are those current assets, which can be converted into cash immediately or within
reasonable short time without a loss of value. These include cash and bank balances, sundry
debtors, bill’s receivables and short-term marketable securities.
While a quick ratio lower than 1 does not necessarily mean the company is going into default
or bankruptcy, it could mean that the company is relying heavily on inventory or other assets
to pay its short term liabilities. The higher the quick ratio, the better the company's liquidity
position. However, too high a quick ratio may indicate that the company has too much cash
sitting in its reserves. It may also mean that the company has a high accounts receivables,
indicating that the company may be having problems collecting on its account receivables.
 Earnings per Share: It measure the profit available to the equity shareholders on a per
share basis. It is computed by dividing earnings available to the equity shareholders by
the total number of equity share outstanding
Earnings per share = {Earnings after tax – Preferred dividends (if any)} / {Equity
shares outstanding}
Significance and Interpretation:
The shares are normally purchased to earn dividend or sell them at a higher price in future. EPS
figure is very important for actual and potential common stockholders because the payment of
dividend and increase in the value of stock in future largely depends on the earnings of the
company. EPS is the most widely quoted and relied figure by investors. In most of the
countries, the public companies are required to report EPS figure on the income statement. It
is usually reported below the net income figure.
There is no rule of thumb to interpret earnings per share. The higher the EPS figure, the better
it is. A higher EPS is the sign of higher earnings, strong financial position and, therefore, a
reliable company to invest money. For a meaningful analysis, the analyst should calculate the
EPS figure for a number of years and also compare it with the EPS figure of other companies
in the same industry. A consistent improvement in the EPS figure year after year is the
indication of continuous improvement in the earning power of the company.

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 Dividend per Share: The dividends paid to the shareholders on a per share basis in
dividend per share. Thus dividend per share is the earnings distributed to the ordinary
shareholders divided by the number of ordinary shares outstanding.
Dividend per share = Earnings paid to the ordinary shareholders/ Number of
ordinary shares outstanding
It is one of the important measurements to determine how much return on investment is earned
from each shares of a company. The history of DPS ratio of a company helps investors to
determine the stability of a company. A higher dividend per share ratio generally indicates that
the company is making more profit and provides more dividends on each shares of a company,
and a lower DPS ratio indicates that the company is less profitable and provides diminished
dividends on each shares of a company.
 Debt Equity Ratio: Debt equity ratio shows the relative claims of creditors (Outsiders)
and owners (Interest) against the assets of the firm. Thus this ratio indicates the relative
proportions of debt and equity in financing the firm’s assets. It can be calculated by
dividing outsider funds (Debt) by shareholder funds (Equity)
Debt equity ratio = Outsider Funds (Total Debts)/ Shareholder Funds or Equity
The outsider fund includes long-term debts as well as current liabilities. The shareholder funds
include equity share capital, preference share capital, reserves and surplus including
accumulated profits. However fictitious assets like accumulated deferred expenses etc. should
be deducted from the total of these items to shareholder funds. The shareholder funds so
calculated are known as net worth of the business.
A ratio of 1 (or 1: 1) means that creditors and stockholders equally contribute to the assets of
the business.
A less than 1 ratio indicates that the portion of assets provided by stockholders is greater than
the portion of assets provided by creditors and a greater than 1 ratio indicates that the portion
of assets provided by creditors is greater than the portion of assets provided by stockholders.

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Creditors usually like a low debt to equity ratio because a low ratio (less than 1) is the indication
of greater protection to their money. But stockholders like to get benefit from the funds
provided by the creditors therefore they would like a high debt to equity ratio.
Debt equity ratio vary from industry to industry. Different norms have been developed for
different industries. A ratio that is ideal for one industry may be worrisome for another industry.
A ratio of 1: 1 is normally considered satisfactory for most of the companies.
 Return on Capital Employed: This ratio establishes the relationship between net
profit and the gross capital employed. The term gross capital employed refers to the
total investment made in business. The conventional approach is to divide Earnings
after Tax (EAT) by gross capital employed.
Return on gross capital employed = Earnings after Tax (EAT) X 100/ Gross capital
employed
Return on capital employed ratio measures the efficiency with which the investment made by
shareholders and creditors is used in the business. Managers use this ratio for various financial
decisions. It is a ratio of overall profitability and a higher ratio is, therefore, better.
To see whether the business has improved its profitability or not, the ratio can be calculated for
a number of years.
 Price Earnings Ratio: The price-earnings ratio (P/E ratio) is the ratio for valuing a
company that measures its current share price relative to its per-share earnings. The
price-earnings ratio is also sometimes known as the price multiple or the
earnings multiple.
The P/E ratio can be calculated as:
Market Value per Share / Earnings per Share
 Generally a high P/E ratio means that investors are anticipating higher growth in the
future.
 The average market P/E ratio is 20-25 times earnings.
 The P/E ratio can use estimated earnings to get the forward looking P/E ratio.

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 Companies that are losing money do not have a P/E ratio.
High P/E
Companies with a high Price Earnings Ratio are often considered to be growth stocks. This
indicates a positive future performance, and investors have higher expectations for future
earnings growth and are willing to pay more for them. The downside to this is that growth
stocks are often higher in volatility and this puts a lot of pressure on companies to do more to
justify their higher valuation. For this reason, investing in growth stocks will more likely to be
seen as risky investment. Stocks with high P/E ratios are also considered overvalued.
Low P/E
Companies with a low Price Earnings Ratio are often considered to be value stocks. It means
they are undervalued because their stock price trade lower relative to its fundamentals. This
mispricing will be a great bargain and will prompt investors to buy the stock before the market
corrects it. And when it does, investors make a profit as a result of a higher stock price.
 Return on Investment: The return on investment ratio (ROI), is a profitability measure
that evaluates the performance of a business or investment, or the potential return from
a business or investment, by dividing net profit by net worth, with the result expressed
as a ratio or percentage.
Return on investment, or ROI, is the most common term. There are several ways to
determine RO I, but the most frequently used method is to divide net profit by total assets.
Return on Investment = Net Income (Net Profit)/Total Assets
Generally, any positive ROI is considered a good return. This means that the total cost of the
investment was recouped in addition to some profits left over. A negative return on investment
means that the revenues weren’t even enough to cover the total costs. That being said, higher
return rates are always better than lower return rates.

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CHAPTER – 4
EXPERIMENTAL ANALYSIS
The procedure for carrying out the stock market performance of the infrastructure companies
is as follows:
 Initially, the equity share price of the companies in the sample were obtained. The
duration kept was 52 weeks (Source: BSE India, Money control and Morningstar).
 Based on the opening and closing prices of the recent and start day, the Compound
Annual growth rate(CAGR) for all the companies is to be obtained by using the
formula:
CAGR = {(ho / lo) 1/n
-1}
Where,
ho = Closing price of the recent date
lo = Opening price of the start date
n = Duration
The compound annual growth rate (CAGR) is the mean annual growth rate of an investment
over a specified period of time. The compound annual growth rate isn't a true return rate, but
rather a representational figure. It is essentially an imaginary number that describes the rate at
which an investment would have grown if it had grown at a steady rate, which virtually never
happens in reality. CAGR can be perceived as a way to smooth out an investment’s returns so
that they may be more easily understood.
 This data for various companies was computed for 365 days (14th
September, 2016 to
15th
September, 2017) and growth rate was computed on a daily basis.
 Once obtained, it was compared with the daily growth of the Sensex, to ascertain the
performance of the companies in the stock market on a daily basis.
 This analysis is done to obtain the effects of market fluctuations on the share price of
the companies.
 The more stable a company is, less is the fluctuation on its prices. However, this may
or may not be true in case of macro fluctuations.
 Also, statistical analysis can be performed on the values for better understanding of the
stability of the companies in stock market.

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Also, the CAGR for various companies and Sensex are as follows:
Entity CDGR SDGR
Sensex 0.0109 0.0083
L&T -0.0156 0.0184
GMR Infra 0.0183 0.0442
RIL -0.0127 0.0318
Jaypee Infra 0.0392 0.0616
Lanco -0.1226 0.0447
IRB Infra -0.0089 0.0316
IL&FS -0.0408 0.0492
HCC -0.0028 0.0415
NCC 0.0066 0.0345
GVK 0.0546 0.0532
From this preliminary analysis, we may conclude that GMR, Jaypee and GVK are performing
better with respect to the other companies. However, detailed statistical analysis is to be done
before jumping to a quick conclusion.
From the above table indicating Simple daily growth rate, initially the mean, standard deviation
and coefficient of variation (CV) were found out.
Analysis Chart
GMR GVK HCC IL&FS IRB Infra JP Infra L&T Lanco NCC RIL Sensex
Mean 15.3865254 7.2638136 39.74915 49.269068 223.580932 12.1380932 1470.9519 2.968326 86.28411 524.59047 29317.8058
Median 15.725 6.31 40.175 48.975 226.95 10.965 1469.65 3.565 85.8 518.075 29292.12
Mode 17.125 6.06 39.55 44.175 213.65 17.15 1746 0.87 85.225 510.125 #N/A
Std.
Dev 2.57355056 2.2537317 3.368287 6.6498439 19.5001533 4.27739346 196.31078 1.221072 5.5271815 44.215834 1948.42557
C.V. 16.7260021 31.026839 8.473858 13.496996 8.72174254 35.2394184 13.345833 41.1367 6.405793 8.4286385 6.64587788
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
GMR GVK HCC IL&FS IRB Infra JP Infra L&T Lanco NCC RIL Sensex
Coefficient of Variation

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From the above analysis, we can conclude that NCC Ltd is having the least CV, so it can be
considered as the safest company to invest in. However, there are other factors (various terms
like PE ratio, EPS, DPS etc.) which need to be analysed in order to ascertain the full proof
conclusion.
Moreover, to test the significance between growth rate of various companies with respect to
Sensex’s growth rate, Z test for significance of means is carried out.
 L&T and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of L&T and Sensex’s growth
rates.
Ha = There is a significant difference between means of L&T and Sensex’s growth
rates.
Carrying out the analysis part, we get:
z-Test: Two Sample for Means
Variable 1 Variable 2
Mean 0.008281 0.018355012
Known Variance 0.000022 0.000078
Observations 251 251
Hypothesized Mean Difference 0
z -15.961
P(Z<=z) one-tail 0
z Critical one-tail 1.644854
P(Z<=z) two-tail 0
z Critical two-tail 1.959964
From the above analysis, the null hypothesis is rejected and alternate hypothesis is accepted.
Hence, we can conclude that there is a significant difference between means of L&T and
Sensex’s growth rates. Also, the Sensex outperforms the company.
 GMR and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of GMR and Sensex’s growth
rates.
Ha = There is a significant difference between means of GMR and Sensex’s growth
rates.
Carrying out the analysis part, we obtain:

xxxviii | P a g e
Mean 0.008280543 0.044196108
z -19.09471072
P(Z<=z) one-tail 0
Hence, we can conclude that there is a significant difference between means of GMR and
Sensex’s growth rates.
 RIL and Sensex: Here, the null hypothesis and alternate hypothesis can be formulated
as:
H0 = There is no significant difference between means of RIL and Sensex’s growth
rates.
Ha = There is a significant difference between means of RIL and Sensex’s growth
rates.
Mean 0.008280543 0.03184219
z -18.25804705
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of RIL and
 Jaypee Infra and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of Jaypee Infra and Sensex’s
growth rates.
Ha = There is a significant difference between means of Jaypee Infra and Sensex’s
growth rates.
Carrying out the analysis part, we have:

xxxix | P a g e
Mean 0.008280543 0.061608
z -22.20246128
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of Jaypee Infra
and Sensex’s growth rates. Also, the Sensex outperforms the company.
 Lanco and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of Lanco and Sensex’s growth
rates.
Ha = There is a significant difference between means of Lanco and Sensex’s growth
rates.
Mean 0.008280543 0.044661133
z -18.07366074
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of Lanco and
 IRB Infra and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of IRB Infra and Sensex’s
growth rates.
Ha = There is a significant difference between means of IRB Infra and Sensex’s
growth rates.

xl | P a g e
Mean 0.008281 0.031628
z -19.4412
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of IRB Infra and
 IL&FS and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of IL&FS and Sensex’s growth
rates.
Ha = There is a significant difference between means of IL&FS and Sensex’s growth
rates.
Mean 0.008280543 0.049154
z -21.9541416
Hence, we can conclude that there is a significant difference between means of IL&FS and
 HCC and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of HCC and Sensex’s growth
rates.
Ha = There is a significant difference between means of HCC and Sensex’s growth
rates.

xli | P a g e
Mean 0.008281 0.041514
z -21.5671
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of HCC and
 NCC and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of NCC and Sensex’s growth
rates.
Ha = There is a significant difference between means of NCC and Sensex’s growth
rates.
Mean 0.008281 0.034529
z -20.9239
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of NCC and
 GVK and Sensex: Here, the null hypothesis and alternate hypothesis can be
formulated as:
H0 = There is no significant difference between means of GVK and Sensex’s growth
rates.
Ha = There is a significant difference between means of GVK and Sensex’s growth
rates.

xlii | P a g e
Mean 0.008280543 0.053205
z -19.94826518
P(Z<=z) one-tail 0
P(Z<=z) two-tail 0
Hence, we can conclude that there is a significant difference between means of GVK and
Now, for testing the significance in means of the companies, and for checking whether the
results are applicable for population data, ANOVA test is carried out. Here, the base hypothesis
can be written as:
Ho = There is no significant difference between the means.
Ha = There is a significant difference between the means.
ANOVA: Single Factor
SUMMARY
Groups Count Sum Average Variance
Sensex 251 2.07841 0.00828054 0.00002179096
L&T 251 4.60710 0.01835501 7.84358E-05
GMR 251 11.0932 0.04419610 0.000866282
RIL 251 7.99238 0.03184218 0.000396306
Jaypee 251 15.4635 0.06160771 0.001426189
Lanco 251 11.20994 0.044661133 0.000995365
IRB 251 7.93864 0.03162805 0.000340364
IL&FS 251 12.3376 0.04915379 0.000847582
HCC 251 10.4200 0.04151413 0.00057413
NCC 251 8.66677 0.03452900 0.000372754
GVK 251 13.3544 0.05320496 0.001250554

xliii | P a g e
ANOVA
Source
of
Variation
SS df MS F
P-
value
F crit
Between
Groups
0.59428959 10 0.0594289 91.17727775
5.9E-
163
2.32735
Within
Groups
1.79243822 2750 0.0006517
Total 2.38672781 2760
Hence, the null hypothesis is rejected. So, we can conclude that there is a significant difference
between the means.
At last, to understand the interrelation and interdependency between the variables, correlation
test is carried out.
GV
K
NC
C
HC
C
IL&F
S
IRB
Lanc
o
JP RIL GMR L&T
Sen
sex
GVK 1
NCC 0.52 1
HCC 0.33 0.28 1
IL&F
S
0.55 0.42 0.41 1
IRB 0.20 0.19 0.32 0.17 1
Lanco 0.23 0.22 0.28 0.16 0.27 1
JP 0.49 0.32 0.32 0.59 0.18 0.11 1
RIL 0.27 0.19 0.21 0.36 0.06 0.05 0.30 1
GMR 0.53 0.35 0.38 0.50 0.16 0.19 0.47 0.28 1
L&T 0.51 0.32 0.35 0.52 0.20 0.10 0.55 0.33 0.51 1
Sensex 0.19 0.14 0.46 0.24 0.16 0.18 0.13 0.18 0.24 0.16 1
It can be observed that HCC, IL&FS and GMR are correlated to a higher degree with respect
to Sensex. Hence, investment in these companies can be more risky as the market is highly
volatile in nature.

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Fundamentals of Finance
Here, the key terms adopted are:
 Current ratio
 Quick ratio
 Earnings per Share
 Dividend per Share
 Debt Equity Ratio
 Return on Capital Employed
 Return on Investment
 Profit Earnings Ratio
Values of these terms were obtained for the top 10 companies for a period of five years.
However, since the values for GVK were above extremes, hence it was excluded from the
fundamental analysis. Also, P-E ratio was only analysed few companies as many companies
haven’t shown their profit-earnings. Also, the industry average was obtained from secondary
sources and basic analysis. The data was compared with the industry average and top two and
bottom two companies were indicated by green and blue cell shades respectively.
Hence, from the above analysis, we can conclude that L&T and RIL are the two companies,
whereas Lanco and GMR are the bottommost two companies in terms of Internal Business
strength.
At last, for testing the significance between various means of various terms, ANOVA test is
applicable.
 Current Ratio: For current ratio, the assumption can be stated as : the null hypothesis
and alternate hypothesis can be formulated as:
H0 = There is no significant difference between means of companies
Ha = There is a significant difference between means of companies.
Anova: Single Factor
SUMMARY
1.45 4 5.58 1.395 0.002167
0.77 4 4.24 1.06 0.220067
1.15 4 5.38 1.345 0.000633
1.27 4 6.36 1.59 0.0828
0.61 4 3.74 0.935 0.0129
0.79 4 3.69 0.9225 0.061825
0.73 4 3.79 0.9475 0.015092
1.09 4 4.21 1.0525 0.034092
1.28 4 4.66 1.165 0.015033

xlv | P a g e
ANOVA
Source of
Variation
SS df MS F P-value F crit
Between Groups 1.792139 8 0.224017 4.534679 0.001383 2.305313
Within Groups 1.333825 27 0.049401
Total 3.125964 35
Hence, from the above analysis the null hypothesis is rejected. So, there is a significant
difference between means of companies.
 Quick Ratio: For quick ratio, the assumption can be stated as : the null hypothesis
Carrying out the analysis, we have:
SUMMARY
1.41 4 5.38 1.345 0.002167
0.73 4 4.15 1.0375 0.229425
1.13 4 5.29 1.3225 0.000625
0.25 4 1.84 0.46 0.000333
0.47 4 3.09 0.7725 0.014758
0.79 4 3.69 0.9225 0.061825
0.37 4 1.97 0.4925 0.005892
1.05 4 1.17 0.2925 0.006692
0.99 4 3.55 0.8875 0.009825
ANOVA
Source of
Variation
Between Groups 4.421139 8 0.552642 15.00198 4.08E-
08
2.305313
Within Groups 0.994625 27 0.036838
Total 5.415764 35
 Earnings per Share: For earnings per share, the assumption can be stated as : the
null hypothesis and alternate hypothesis can be formulated as:

xlvi | P a g e
58.49 4 250.88 62.72 136.5642
-6.12 4 -2.94 -0.735 1.971633
48.99 4 270.23 67.5575 90.68609
-7.1 4 6.67 1.6675 11.24929
-3.25 4 -8.58 -2.145 3.082567
5.78 4 27.71 6.9275 5.900225
-0.05 4 -59.02 -14.755 90.40777
0.71 4 1.43 0.3575 3.077825
4.06 4 10.59 2.6475 1.015558
ANOVA
Source of
Variation
Between Groups 28253.76 8 3531.72 92.4117 1.35E-
17
2.305313
Within Groups 1031.865 27 38.21724
Total 29285.63 35
 Dividend per share: For dividend per share, the assumption can be stated as : the null
hypothesis and alternate hypothesis can be formulated as:
SUMMARY
21 4 67.25 16.8125 3.932292
0 4 0.2 0.05 0.003333
9 4 31.4 7.85 0.256667
0 4 1 0.25 0.25
0 4 0 0 0
5 4 16 4 0
0 4 1.5 0.375 0.5625
0 4 0.4 0.1 0.04
0.4 4 1.5 0.375 0.029167
ANOVA
Source of
Variation
Between Groups 1047.54 8 130.9425 232.261 7.59E-
23
2.305313
Within Groups 15.22188 27 0.563773
Total 1062.762 35

xlvii | P a g e
 Debt-Equity Ratio: For debt-equity ratio, the assumption can be stated as : the null
SUMMARY
0.21 4 1.18 0.295 0.0007
0.8 4 2.07 0.5175 0.004825
0.6 4 2.65 0.6625 0.008758
1.38 4 4.87 1.2175 0.023425
5.03 4 10.37 2.5925 1.457292
1.23 4 3.78 0.945 0.026567
19.74 4 219.81 54.9525 3687.657
1.48 4 13.26 3.315 0.4143
0.45 4 2.87 0.7175 0.032892
ANOVA
Source of
Variation
Between
Groups
10274.47 8 1284.308 3.132777 0.012241 2.305313
Within Groups 11068.88 27 409.9584
Total 21343.34 35
 Return on Capital Employed: For ROCE, the assumption can be stated as : the null

xlviii | P a g e
10.15 4 48.41 12.1025 2.426758
-31.39 4 -10.88 -2.72 27.8088
3.43 4 22.44 5.61 1.186333
-6.87 4 8.14 2.035 7.705767
-10.94 4 -18.11 -4.5275 12.71176
4.57 4 26.08 6.52 5.120867
0.1 4 -16.06 -4.015 41.1135
1.06 4 2.67 0.6675 6.015025
6.34 4 13.14 3.285 4.250967
ANOVA
Source of
Variation
Between Groups 959.6641 8 119.958 9.96515 2.42E-
06
2.305313
Within Groups 325.0193 27 12.03775
Total 1284.683 35
 Return on Investment: For ROI, the assumption can be stated as : the null hypothesis
SUMMARY
8.29 4 35.5 8.875 0.448367
-312.27 4 -219.52 -54.88 9161.094
14.68 4 62.42 15.605 8.388433
-91.08 4 32.47 8.1175 153.8929
-54.4 4 -107.46 -26.865 517.6211
5.95 4 41.04 10.26 7.028867
0.12 4 -12.55 -3.1375 30.31129
1.41 4 2.46 0.615 7.861433
2.85 4 5.76 1.44 0.751267
ANOVA
Source of
Variation
Between Groups 16247.08 8 2030.885 1.848612 0.111172 2.305313
Within Groups 29662.19 27 1098.6
Total 45909.27 35

xlix | P a g e
From the above analysis, the null hypothesis is accepted. So, there is no significant difference
between mean of companies.

l | P a g e
CONCLUSION AND FUTURE SCOPE
From the above tests and analysis carried out, we can conclude that L&T, RIL and NCC are
the safest and most profitable companies to invest in, while Lanco, GVK and GMR are the
most risky companies to invest in. This is, however, subjected to change, as the infrastructure
and share market is continuously evolving, as new initiatives are being introduced by the
government of India. Also, various PPP models are being evolved, in order to stabilize the
position and internal strength of Infrastructure companies. Hybrid Annuity Model (HAM) is
one such initiative.
However, the future scope of this study is way beyond the current statistical model assessment.
Various other models are being proposed by analysts across the globe. Some of them are:
 Statistical model integrated with Artificial Neural Network (ANN)
 Financial time sequencing model
 Data envelopment analysis (DEA) model
 Market value added (MVA) model etc.
When compared to traditional method, these models provide way better results. However,
ample time is required for understanding the way of assessment by these models, as they are
still being used by Big Shots of International market. By means of this study, we have tried to
assess a preliminary way of undergoing the assessment of Infrastructure companies in terms of
key ratios and stock prices, which may help investors in long term decision making.
Also, various provisions provide in the recent Union budget are relaxation of the rating
threshold (from AA to A), encouraging more participation from domestic insurance companies
and pension funds in the infrastructure sector, the total capital outlay for the infrastructure
sector has been budgeted to increase by 20.8% to Rs 5.97 lakh crore in FY18-19, the capital
outlay under PMAY (Urban) has been increased sharply, including assistance for construction
of 37 lakh houses in urban areas etc. Hence, the road to development of Infrastructure
companies is being paved, thereby making a way for the economic boost to be induced in the
national economy in the upcoming years. An extension to this study can be done by observing
the impact on Infrastructure sector from the various schemes of Niti Aayog and the upcoming
budgetary provisions.

li | P a g e
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