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Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
Review Article
ANALYSIS AND CLUSTERING OF NIFTY COMPANIES OF
SHARE MARKET USING DATA MINING TOOLS
D. Venugopal Setty1, Dr.T.M.Rangaswamy
2 and Dr.A.V.Suresh
3
Address for Correspondence
1Assistant Professor,
2Professor,
3Professor and HOD, Department of Industrial Engineering and
Management, R.V. College of Engineering, Bangalore – 560059, India
E-mail ID: [email protected]
ABSTRACT Data are any facts, numbers, or text that can be processed. Data analysis is to find relationships among the data
objects and then perform the remaining analysis like; clustering, classification, or anomaly analysis. A cluster is a
set of objects in which each object is closer to every other object, and an entire collection of clusters is referred as
clustering. On review of the papers and journals, it was found that the investors are finding difficulty in selecting
better performing company for investment. Hence the objective of the research work was set to develop the
clusters of NIFTY companies for better investment. Price per earnings ratios were calculated for all the 50
NIFTY companies during years 2008-2009 & 2009-2010. The specimen calculated Price per earning ratios for
Reliance power was 171.70 and clustering of companies under sector wise were made based on the financial ratio
analysis and clustering analysis. It was found that all 50 NIFTY companies were clustered and distributed as 11,
21 & 18 numbers for the P/E ratio <10, P/E ratio between 10-20 & P/E ratios >20 respectively for the year 2008-
09 and 03, 18 & 29 respectively for the year 2009-10. Based on results, an investor is suggested to select a
company and sector from the list for better investment. The recommended company for investment is reliance
power (power-generation and distribution sector), since this company performed well in the years 2008-09 and
2009-10.
KEY WORDS: Nifty, sector, share market
INTRODUCTION
Data Mining
Data are any facts, numbers, or text that can be
processed by a computer. One approach to data
analysis is to find relationships among the data
objects and then perform the remaining analysis
using these relationships rather than the data
objects themselves. Data Mining is an analytic
process designed to explore data (usually large
amounts of data, typically business or market
related) and in search of consistent patterns and
/or systematic relationships between variables,
and then to validate the findings by applying the
detected patterns to new subsets of data. It is
also called as data discovery or knowledge
discovery. Data Mining can be used to increase
revenue, cuts costs, or both.
Data Mining Tasks
Data mining tasks are generally divided into
two major categories, namely predictive task
and descriptive task. The objective of Predictive
Task is to predict the value of a particular
attribute based on the values of the other
attributes and that the objective of Descriptive
task is to derive patterns (correlations, trends,
clusters, trajectories and anomalies) that
summarize the underlying relationships in data.
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
Data mining does the further four important
tasks namely; predictive modeling, association
analysis, cluster analysis, and anomaly
detection.
Cluster
A cluster is a set of objects in which each object
is closer to every other object. The types of
clusters includes; well-separated clusters,
prototype-based clusters, graph-based clusters,
density-based clusters, and shared-property
(conceptual clusters). The important
characteristics of cluster include; data
distribution, shape, different size, different
density, poorly separation, relationships among
clusters, and subspace.
Clustering
Clustering is a class or group of objects that
share common characteristics and play an
important role in how people analyze and
describe the world. It is dividing the objects into
groups (clustering) and assigning particular
objects to these groups (classification).
Clustering aims to find useful groups of objects,
where usefulness is defined by the goals of the
data analysis. An entire collection of clusters is
commonly referred to as clustering. There are
three types of clustering namely; hierarchical
versus partitional, exclusive versus overlapping
versus fuzzy and complete versus partial. A
partitional clustering is simply a division of the
set of data objects into non-overlapping subsets
(clusters) such that each object is exactly in one
subset. Partitional algorithms typically
determine all clusters at once. The partitional
clustering can be obtained by taking any
member of that sequence.
Cluster Analysis
It groups data objects based only on information
found in the data that describes the objects and
their relationships. It is also a class or group of
objects that share common characteristics and
play an important role in how people analyze
and describe. The goal is that the objects within
a group be similar to one another and different
from the objects in the other groups. The greater
the similarity within a group and greater the
difference between groups, the better or more
distinct is the clustering. Cluster analysis is
sometimes referred to as unsupervised
classification. When the term classification is
used without any qualification within data
mining, it typically refers to supervised
classification.
Financial Market
Financial market is a mechanism that allows
people to easily buy and sell financial securities,
commodities and other fungible items of value
at low transaction costs. Financial markets can
be domestic or international. The financial
markets can be divided into different types
namely; capital markets (stock markets, bond
markets and commodity markets), money
markets, derivatives markets, insurance
markets, foreign exchange markets. Financial
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
markets facilitates; raising of capital in the
capital markets, transfer of risk in the
derivatives markets, international trade in the
currency markets, and match those who want
capital to those who have it.
Stock Market
The stock market is one of the most important
source for companies to raise money, and is a
public market for the trading of company stock
and derivatives at an agreed price.The stock
market ma be primary , or secondary. In the
primary markets, securities are bought by way
of the public issue (IPO’s) directly from the
company, and where as in the secondary market
existing outstanding securities are bought and
sold.
Stock Exchange
A stock exchange is a corporation or mutual
organization which provides trading facilities
for stock brokers and traders. Stock exchanges
have multiple roles in the economy namely;
raising capital for businesses, mobilizing
savings for investment, facilitating company
growth, profit sharing, corporate governance,
creating investment opportunities for small
investors, government capital-raising for
development projects, etc. The Bombay Stock
Exchange Limited and the National Stock
Exchange limited are two largest exchanges in
India.
Standard and Poor CNX National Fifty (S&P
Cnx Nifty)
In 1996, the National Stock Exchange of India
launched S&P CNX Nifty and CNX Junior
Indices that make up 100 most liquid stocks in
India. The NSE's key index is the S&P CNX
Nifty, known as the Nifty. Nifty is a diversified
index of 50 stocks from 25 different economy
sectors weighted by market capitalization. S&P
CNX NIFTY tracks the behavior of a portfolio
of blue chip companies, the largest and most
liquid Indian securities. The index has been
trading since April 1996 and is well suited for
benchmarking. Selection of the index set is
based on criteria; impact cost, market
capitalization, shares outstanding, and domicile.
The index is reviewed every quarter and a six-
week notice is given to the market before
making any changes to the index constituents.
Stocks may be deleted due to mergers,
acquisitions or spin-offs.
Stock Market Basics (Shares And Stocks)
Stock market basics include shares and stocks.
A Share or stock is a document issued by a
company, which entitles its holder to be one of
the owners of the company. A share is directly
issued by a company through IPO or can be
purchased from the stock market. By owning a
share one can earn a portion of the company’s
profit called dividend. So, return is the dividend
plus the capital gain. A stock is nothing but a
collection or a group of shares. The stock may
be common stock or preferred stock.
Financial Ratio Analysis
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
Financial Ratio analysis uses a company’s
financial information to predict whether it will
meet its future projections of earnings, and it
assists the investor in the selection of stocks.
These are classified as; profitability ratios,
liquidity ratios, activity ratios, debt ratios
(leverage ratios), market ratios and coverage
ratios. Profitability ratios measure the firm's use
of its assets and control of its expenses to
generate an acceptable rate of return. These
because the profits of a company are important
to investors because these earnings are either
retained or paid out in dividends to
shareholders, both of which affect the stock
price.
Price/Earnings Ratio (P/E Ratio)
Price/Earning ratio gives you fair idea of how a
company's share price compares to its earnings.
If the price of the share is too much lower than
the earning of the company, the stock is under
valued and it has the potential to rise in the near
future. On the other hand, if the price is way too
much higher than the actual earning of the
company and then the stock is said to over
valued and the price can fall at any point. The
most commonly used guide to the relationship
between stock prices and earnings is the P/E
ratio. P/E ratio is volatile and may fluctuate
considerably. The P/E ratios (above 20, thumb
rule) are characteristic of growth companies,
although with the average market multiple
currently around 28, a P/E ratio of 20 almost
seems like a value stock. High P/E ratios
indicate high risk. If the future anticipated
growth of the high P/E ratio stocks is not
achieved, their stock prices will be punished
and they will fall very quickly. On the other
hand, if they live up to their promise, investors
will benefit substantially. Low P/E ratio stocks
(under 10) are characteristic of either mature
company with low growth potential or
companies that are undervalued or in financial
difficulty. By comparing the P/E ratio of a
company with the averages in the industries and
the markets, investors can get a feeling for the
relative value of the stock. P/E ratios fluctuate
considerably, differing among companies due to
many factors, from growth rates and popularity
to earnings and other financial characteristics. It
is calculated by, P/E ratio = Market price of the
stock / Earnings per share
Earnings per Share (EPS)
Earning per share is the profit that the company
made per share on the last quarter. It is
mandatory for every public company to publish
the quarterly report that states the earning per
share of the company. The earning per share
indicates the amount of earnings allocated to
each share of common stock outstanding. EPS
figures can be used to compare the growth or
lack of growth in earnings from year to year and
to project growth in earnings. Decreasing EPS
over a period of time generally has a negative
impact on stock price. EPS is calculated by,
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
• EPS = (Net income–Preferred
Dividends) / Number of common share
outstanding.
• Where, Number of shares outstanding =
Number of shares issued – Shares
company has bought back.
RESEARCH GAP
• On review of the papers and journals,
despite the improving economic
environment in the country, the investors
are still finding difficult in selecting better
performing / appropriate company /sector
for investment.
• Stock analysis is a difficult task due to the
nature of the stock data, which is very noisy
and time varying.
OBJECTIVES OF THE RESEARCH
The current research work was carried out with
the following objectives:
1. To study and analyse the performance of
Share Market of NIFTY companies
2. To develop clusters of the NIFTY
Companies using Data Mining Tools
(Clustering analysis) and profitability ratio
(price per earnings ratio)
3. To help the investor in selection of better
performing company and sector for the
investment
METHODOLOGY ADOPTED
1. To study the stock market.
2. To collect the NIFTY companies for the
year 2008-2009 and 2009-2010.
3. To identify and grouping the Nifty
companies under various sectors.
4. To collect the number of outstanding shares,
EPS (earnings per share) and closing price
data / Market price of the stock of the 50
NIFTY companies for the year 2008-2009
and 2009-2010.
5. To calculate Price per Earnings ratio (P/E
ratio).
6. To group the Nifty companies as clusters.
7. To recommend best company / sector for
the investor to investment money.
DATA COLLECTION
Data to be collected was divided into two parts
such as; qualitative data and quantitative data.
The qualitative data collection was made using
judgmental sampling method. The quantitative
data collection was carried out by means of
secondary data, and this includes; list of NIFTY
companies, earnings per share (EPS) and
closing price data / Market price of the stocks of
the 50 NIFTY companies for the years 2008-09
and 2009-2010 from stock exchanges, internet,
magazines and trade journals. The companies
deleted under NIFTY in the year 2009 – 2010
are GRASIM and HCL TECH, while added is
TVS MOTORS and UCO BANK.
TOOLS AND TECHNIQUES USED
The tools and techniques used in the analysis
and clustering of the NIFTY companies of share
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
market includes: data mining tools - clustering
analysis, type of cluster - conceptual cluster
(shared-property clusters) , type of clustering -
partitional clustering , type of cluster analysis /
algorithm - agglomerative hierarchical
clustering algorithm , and type of financial ratio
- profitability ratio
DATA ANALYSIS
Price per earnings ratios are calculated for the
years 2008-09 & 2009-2010 and are tabulated
in Tble – 1 & Tble – 2 respectively.
TABLE 1 : PRICE PER EARNING RATIOS FOR THE YEAR 2008-09
Company Sector P/E ratio =MV/EPS A B B Electric equipment 19.2
ACC Cement 9.9
AMBUJA CEM. Cement 10.6
AXIS BANK Bank 10.3
B H E L Engineering heavy 25.7
B P C L Refineries -
BHARTI AIRTEL Communication 17
CAIRN INDIA Oil drilling & exloration 50
CIPLA Pharmaceuticals 25.4
DLF Construction & contracting 18.5
GAIL (INDIA) Oil drilling & exploration 11.3
GRASIM INDS Diversified 8.4
H D F C Bank 22.1
HCL TECHNOLOGIES Computer software 10.6
HDFC BANK Bank 22.4
HERO HONDA MOTOR Automobiles 19.3
HIND. UNILEVER Personal care 24.2
HINDALCO INDS. Aluminium 3.4
ICICI BANK Bank 11.2
IDEA CELLULAR Communication 18.1
INFOSYS TECH. Computer software 14.9
ITC Cigarettes 22.2
LARSEN & TOUBRO Engineering heavy 20
M & M Automobiles 22.9
MARUTI SUZUKI Automobiles 19.1
NATL. ALUMINIUM Aluminum 9.9
NTPC Power-generation &
distribution 21.3
O N G C Oil drilling & exploration 11.6
POWER GRID CORPN Power-generation &
distribution 27
PUNJAB NATL BANK Bank 5.2
RANBAXY LABS. Pharmaceuticals -
RELIANCE CAPITAL Finance 11
RELIANCE COMM Communication 43.9
RELIANCE INDS 17.7
RELIANCE INFRA Power-generation &
distribution 14.9
RELIANCE PETRO Refineries -
RELIANCE POWER Power-generation &
distribution 171.73
S A I L Steel 6.9
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SIEMENS Telecommunication equipment 13.3
ST BK OF INDIA Bank 9.4
STERLITE INDS. Metals 7.2
SUN PHARMA. Pharmaceuticals 22.1
SUZLON ENERGY Engineering heavy 8.1
TATA COMM Communication 70.8
TATA MOTORS Automobiles 9.5
TATA POWER CO. Power-generation &
distribution 33.7
TATA STEEL Steel 3.7
TCS Computer software 12.4
UNITECH Construction & contracting 7.6
WIPRO Computer software 13.6
TABLE – 2 : PRICE PER EARNING RATIOS FOR THE YEARS 2009-2010
Company Sector P/E ratio =MV/EPS
ABB Electric equipment 50.57
ACC-CEMENT Cement 10.91
AMBUJA CEMENT Cement 14.81
AXIS BANK Bank 22.57
BHARTI AIRTEL Telecommunication service 14.92
BHEL Engineering heavy 38.88
BPCL Refineries 24.52
CAIRN INDIA Oil drilling & exploration 10.46
CIPLA Pharmaceuticals 33.4
DLF Construction & contracting 36.19
GAIL Oil drilling & exploration 18.53
HERO HONDA Automobiles 29.91
HINDALCO Aluminum 14.29
HUL Personal care 19.77
ICICI BANK Banks-private sector 27.3
IDEA CELLULAR Telecommunication service 20.71
IDFC Finance 28.35
INFOSYS Computer software 27.56
ITC Cigarettes 31.14
JAIPRAKASH ASSOCIATION Construction & contracting 23.12
KOTAK MAHINDRA Bank 90.75
L&T Engineering heavy 26.43
MAH & MAH Automobiles 32.75
MARUTI SUZUKI Automobiles 32.03
NTPC Power-generation/distribution 20.87
ONGC Oil drilling & exploration 13.68
PNB-BANK Bank 10.15
POWER GRID CORP Power-generation/distribution 26.84
RANBAXY LABS Pharmaceuticals 33.09
RELIANCE CAPITAL Finance 19.1
RELIANCE REFINERIES Refineries 10.9
RELIANCE-
COMMUNICATION Telecommunication service 14.8
RELIANCE
INFRASTRUCTURE Power-generation/distribution 23.66
RELIANCE POWER Power-generation/distribution 150.89
SAIL Steel 15.24
SBI-BANK Bank 14.25
SUN PHARMA Pharmaceuticals 29.48
Journal of Engineering Research and Studies
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TATA MOTORS Automobile 40.28
TATA POWERS Power-generation/distribution 31.989
TATA STEEL Steel 9.76
TCS Computer software 16.98
UNITECH Construction & contracting 17.76
WIPRO Computer software 35.58
TVS Automobiles 59.72
STERLITE INDUSTRIES Metals 26.86
UCO BANK Bank 6.02
Specimen Calculation for Price per Earning
Ratio
Price per earning ratio, P/E ratio = Market value
/Earnings per share
• For Reliance power (power-generation &
distribution), MV = Rs.51.519, EPS =
Rs.0.3 per share, and P/E ratio = 51.519/0.3
= 171.7
• For Amubja cement, MV = Rs.118.48, EPS
= Rs. 8 per share and P/E ratio = 118.48/8
=14.81
• For UCO bank, MV = Rs. 61.103, EPS =
RS.10.15 per share, and P/E ratio
=61.103/10.15 = 6.02
• For L&T (Heavy engineering), MV=
Rs.1570.9992, EPS = Rs.59.44 per share,
and P/E ratio =1570.9992/59.44 =26.43
Graphical Representation of P/E Ratio Vs
Nifty Companies
Graphical representation of P/E RATIO vs
NIFTY companies for the years 2008-2009 &
2009-2010 are shown in graph – 1 & graph- 2
respectively for better visual presentation.
GRAPH– 1: P/E RATIO VS NIFTY COMPANIES FOR THE YEAR 2008-2009
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
GRAPH- 2 : P/E RATIO VS NIFTY COMPANIES FOR THE YEAR 2009-2010
CLUSTERING OF NIFTY COMPANIES
UNDER SECTORS WISE
Clustering of NIFTY companies under sectors
wise were made based on Price per earning
ratios for the years 2008-09 & 2009-2010, and
are tabulated in table – 3 & table – 4
respectively. Pie chart - 1 & pie chart – 2
represents clustering of NIFTY companies
under sectors wise for the years 2008-2009 &
2009-2010 respectively.
TABLE – 3 : CLUSTERING OF NIFTY COMPANIES UNDER SECTORS WISE FOR THE
YEAR 2008-09
Price per earning ratio is Sector
<10 10-20 >20
Cement Acc cements Ambuja cements Nil
Bank SBI, PNB Axis, ICICI HDFC
Engineering-heavy Suzlon energy Nil BHEL
Pharmaceuticals Nil Ranbaxy CIPLA, Sun pharma
Construction Unitec DLF Nil
Oil drilling & exploration Nil Gail, ONGC Cairn india
Diversified Grasim L&T, Reliance
industries
Nil
Telecommunication Nil Bharati airtel, IDEA
cellular, SIEMENS
Tata communications
Personal care Nil Nil Hindustan unilever
Finance Nil Reliance capital,
HDFC
Nil
Journal of Engineering Research and Studies
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Computer-software Nil W IPRO, TCS,
Infosys, HCL
Nil
Automobiles Tata motors Hero honda, maruthi
suzuki
Mah & mah,
Aluminum National aluminum,
hindalco
Nil Nil
Cigarette Nil Nil ITC
Power Nil Reliance
infrastructure
NTPC, power grid
corporation, r power
Metal TATA steel, SAIL,
Sterlite
Nil Nil
TABLE – 4: CLUSTERING OF NIFTY COMPANIES UNDER
SECTORS WISE FOR THE YEAR 2009-10
Price per earning ratio is Sector
<10 10-20 >20
Cement Nil 2(acc,ambuja) Nil
Bank 1 (UCO bank) 4(icici,pnb,sbi,kotak) 1(axis bank,)
Communication Nil 2(airtel,reliance) 1(idea)
Power generator/
distributor
Nil Nil 5 (NTPC, power grid,
reliance inf, relpower, tata
power)
Finance Nil 1(HDFC) 2 (IDFC,relliance corp)
Cigrettes Nil Nil 1 (itc)
Steel 1(tata steel) 1(SAIL) 1(jindal)
Automobiles Nil 2(herohonda,tatamotors) 3(mah&mah,maruti,TVS
Oil drilling Nil 2(ONGC,CAIRN INDIA) 1(GAIL)
Pharmaceuticals Nil 1(Ranbaxy labs) 2(CIPLA,Sun pharma)
Construction Nil 1(UNITECH) 2(jaiprakash,DLF)
Heavy engg 1(suzlon) Nil 3(bhel,bpcl,l&t)
Aluminium Nil 1(hindalco) Nil
Software Nil 2(HCL),TCS 2(Infosys,wipro)
Refineries Nil 1(rel refineries) Nil
Electrical
equipment
Nil Nil 1(abb)
Journal of Engineering Research and Studies
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PIE CHART - 1 : CLUSTERING OF COMPANIES UNDER SECTOR WISE FOR THE YEAR
2008-2009
PIE CHART - 2: CLUSTERING OF COMPANIES UNDER SECTOR WISE FOR THE YEAR
2009-2010
ANALYSIS ON PRICE PER EARNINGS
RATIO (P/E RATIO)
If P/E ratio< 10, the company does not grow
and do not give expected profits / returns and
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
investors lose their investment. Hence such
companies mentioned in the list are not
recommended for investment. If P/E ratio 10 to
20, the company growth will take time and
investor has to wait to get the benefits from his
investment. Hence such company mentioned in
the list involves risk for investment. If P/E ratio
> 20, the company does well, growth is
guaranteed, gives maximum profit and high
returns. Hence such companies mentioned in
the list are recommended for investment.
CLUSTER ANALYSIS SUMMARY
Summary of Cluster Analysis based on Price
per earning ratios for the years 2008-09
2009-10 are tabulated in table – 5.
RESULTS AND CONCLUSIONS
Companies were clustered under sector wise
based on the financial ratio analysis &
clustering analysis and for better investment,
the investors are strongly recommended to
select a company & sector from the list. The
recommended NIFTY Company for guaranteed
return is reliance power for investment, since
this company performed well in the years 2008-
09 and 2009-10
TABLE – 5 : SUMMARY OF CLUSTER ANALYSIS
Price per
earnings ratio
For the year 2008-09 For the year 2009-10
<10
ACC cements, SBI, PNB, Suzlon
energy, Unitec, Grasim India, TATA
motors, national aluminum, Hindalco,
TATA steel, SAIL, Sterlite
UCO bank, TATA steel , Suzlon
10-20
Ambuja cements, AXIS bank, ICICI,
Ranbaxy, DLF, GAIL, ONGC, L&T,
Relaiance industries, Bharati airtel,
IDEA cellular, Siemens, Rel. capital, W
IPRO , TCS, Infosys, HCL, HDFC,
Hero honda, maruti suzuki, relaince
infrastructure.
ACC, Ambuja, ICICI, airtel, reliance
communication, hdfc, SAIL, TATA
motors, hero honda, ONGC, CAIRN
India, Ranbaxy labs, UNITECH,
Hindalco, HCL, TCS, Reliance
refineries
>20
HDFC, Cipla, BHEL, Sun
pharmaceuticals, Cairn India, TATA
communications, Hindustan unilever,
mah & mah, ITC, NTPC, power grid
corporation, reliance power.
Axiz bank, kotak mah, NTPC, power
grid, reliance infrastructure, tata
power, Reliance power, rel
corporation, ITC, jindal, mah & mah,
TVS, maruthi suzuki, Gail, CIPLA,
sun pharma, jay prakash, DLF, BHEL,
BPCL, L&T, Infosys, WIPRO, ABB
SCOPE FOR FUTURE WORK
Journal of Engineering Research and Studies
JERS/Vol. I/Issue I/July-Sept. 2010/152-164
The cluster analysis carried out for NIFTY
companies only and same analysis can be used
for the companies listed under National Stock
Exchange of India Limited and Bombay Stock
Exchange.
ACKNOWLEDGEMENT
The author’s are thankful to the stock exchange,
brokers and share holders for providing the
data. The author’s are also thankful to paper
reviewers
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