analysis and clustering of nifty companies … i/jers vol i issue i july... · journal of...

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.



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



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



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,



• 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



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



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



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



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



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)



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



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



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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Proceedings of the 8th Asia Pacific Finance

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[2] Fanning K. and Cogger K., (1998), ‘Neural Network Detection of Management Fraud Using

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[3] R. Gencay, “Non-linear prediction of security returns with moving average rules,” Journal of

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[4] World Federation of Exchanges. "2007 Annual

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[5] Data Mining, Nang-Pan

[6] Financial management, IM Pandey [7] www.nseindia.com

[8] www.sharemarketbasics.com

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