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1 KLE’s Institute of Management Studies and Research, Hubli
Chapter.1
1.1) Executive Summary
The main aim of the investor is to minimize the risk involved in investment &
maximize the return. Today there are number of options available to investor like
Post Office investment, Bank Deposit, Insurance, Mutual Fund, Stock Market etc...
Technical analysis is a financial markets technique that claims the ability to
forecast the future direction of security prices through the study of past market
data, primarily price and volume.
This project is about a brief introduction to Technical Analysis, different price
patterns and trends in financial markets and attempt to exploit that patterns etc…
The contents in this project are made simple so as to make a layman understand the
terms used in the Technical Analysis.
The core area of this project focuses what a technical analysts may employ models
and trading rules based for example, on price transformations, Relative Strength
Index, moving averages, Rate of Change, through recognition of chart patterns.
This project contains some elementary statistics which are used in calculation
which help in drawing inferences.
This project has done in SHAREKHAN LIMITED,HUBLI which is the retail
brokering arm of SSKI; SSKI is SS Kantilal Ishwarlal Securities Pvt. Ltd. involved
in rendering different financial services like equity brokerage, commodity research
& brokerage, portfolio management services.
2 KLE’s Institute of Management Studies and Research, Hubli
1.2) Title:
A Study on Technical Analysis of IT Sector for Investment
Decision”.
1.3) Objectives:
To predict the future price of IT sector.
To study the strategies to be adopted by the investor based on the Technical
Analysis.
To predict investor positions in signaling (Buy, Hold & Sell) based on
historical price trends.
Methodology:
The data collected for the research purpose are secondary data. Closing prices of
Scrip’s were collected through National Stock Exchange website.
Sources of Data: The type of the data collection method is secondary data:
 Web sites
 Text Books
 Business magazines.
TOOLS USED:
 Relative Strength Index.
 Moving Average.
3 KLE’s Institute of Management Studies and Research, Hubli
1.1) FINDINGS:
 In the month of December 2016 and March 2017 there was a strong sell
signal of Infosys shares. And August, November 2016 and February 2017
was right time to buy the Shares.
 In the month of May, August 2016 and January 2017 there was a strong
sell signal of TCS shares. And July 2016 and November 2016 was right
time to buy the shares.
 In months of June and October 2016 there was a strong sell signal of
WIPRO shares. And in the month of September and November 2016 and
February 2017 was right time to buy the shares.
 In the month of July, August, December 2016 there was a strong sell signal
of MINDTREE shares. And in the month of May, November 2016 and
February 2017 was right time to buy the shares.
 Technical analysis will indicates the buying point and selling point.
1.2) Limitations:
This project study is limited to only one sector i.e. IT sector. The project does
not extend its scope to any other sector of companies.
The analysis is made based on the available data (April 2016 – March 2017)
considering it is correct and accurate.
Only two Technical tools (Moving Average & RSI) to predict the movement
of Stocks selected companies.
This project can’t predict the prices of stocks for long term.
Only Technical Analysis is used to predict the stock prices of the companies.
4 KLE’s Institute of Management Studies and Research, Hubli
1.3) Conclusion
Technical analysis can be used as a reliable tool for investing into stocks. Many
investors (cash market retail investors) are not having right mental setup to trade in
to stocks; there lies the importance of technical analysis. Mainly it is more useful
in the identification of buying points and selling points. Technical analysis is more
reliable and useful for short term and medium term investors.
The RSI chart shows that end of the many months the RSI of each script were
moving up and it is the right time to sell the Scrip’s. Technical analysis for long
term investment is not so much tenable. For Short term investment technical
analysis is sufficient to predict the next possible price targets without using
fundamental analysis. Technical analysis will help the investors to drive their
investment in right and profitable path.
5 KLE’s Institute of Management Studies and Research, Hubli
Chapter-2
Industry profile
6 KLE’s Institute of Management Studies and Research, Hubli
Industry Profile
The stock exchange initially Started in the nineteenth century in 1875it was
completely started in Bombay and later in Ahmadabad in 1894. To protect the
broker interest and to make active participation of the broker the voluntary
nonprofit association as generated. Securities trading were became the central
subject under the constitution in 1950. BSE were set up in 1927in Bombay. BSE
started first screen based online trading which helped to minimize the risk and
more liquidity in the market.
Stock market
Stock market it is place where the buying and selling of the stocks takes place
based on the company’s stock. The stock which trades on the market should be
listed in the market and unlisted trade takes place in terms of commodities.
Stock Exchange
Stock exchange are an organized and well functioned marketplace, here the high
net worth individuals, all financial institutes, mutual fund and corporate takes place
to make the trading. The members may act either as a agents for their customer, or
as principals for their own accounts.
Stock exchange gives the facilities related to issue of share and redemption of
securities and other financial instruments such as payment of the dividend once the
companies announces and income through trade i.e. buying and selling of the share
on profit loss. The trade on an exchange is only by stock broker do have seat on the
exchange and members who have registered.
SECURITIES AND EXCHANGE BOARD OF
INDIA (SEBI)
The Securities and Exchange Board of India (SEBI) is the regulator for
the securities market in India. It was established in the year 1988 and given
statutory powers on 12 April 1992 through the SEBI Act 1992.
It was established by The Government of India on 12 April 1988 and given
statutory powers in 1992 with SEBI Act 1992 being passed by the Indian
Parliament.SEBI has its headquarters at the business district of BandraKurla
Complex in Mumbai, and has Northern, Eastern, Southern and Western Regional
7 KLE’s Institute of Management Studies and Research, Hubli
Offices in New Delhi, Kolkata, Chennai and Ahmadabad respectively. It has
opened local offices at Jaipur and Bangalore and is planning to open offices at
Guwahati, Bhubaneswar, Patna, Kochi and Chandigarh in Financial Year 2013 -
2014.
Controller of Capital Issues was the regulatory authority before SEBI came into
existence; it derived authority from the Capital Issues (Control) Act, 1947.
Initially SEBI was a non-statutory body without any statutory power. However in
1995, the SEBI was given additional statutory power by the Government of India
through an amendment to the Securities and Exchange Board of India Act, 1992.
In April 1988 the SEBI was constituted as the regulator of capital markets in India
under a resolution of the Government of India.
The SEBI is managed by its members, which consists of following:
1.The chairman who is nominated by Union Government of India.
2.Two members, i.e., Officers from Union Finance Ministry.
3.One member from the Reserve Bank of India.
4.The remaining five members are nominated by Union Government of India, out
of them at least three shall be whole-time members.
BOMBAY STOCK EXCHANGE (BSE)
The Bombay Stock Exchange (BSE) is an Indian stock exchange located at Dalal
Street, Kala Ghoda, Mumbai, Maharashtra, India. Established in 1875 the BSE is
considered to be one of Asia’s fastest stock exchanges, with a speed of 200
microseconds and one of India’s leading exchange groups and the oldest stock
exchange in the South Asia region. Bombay Stock Exchange is the
world's 10thlargest stock market by market capitalization at $1.7 trillion as of 23
January 2015. More than 5,000 companies are listed on BSE.
The Bombay Stock Exchange is the oldest exchange in Asia. It traces its history to
1855, when four Gujarati and one Parsi stockbroker would gather under banyan
trees in front of Mumbai's Town Hall. The location of these meetings changed
many times as the number of brokers constantly increased. The group eventually
moved to Dalal Street in 1874 and in 1875 became an official organization known
as "The Native Share & Stock Brokers Association".
On 31 August 1957, the BSE became the first stock exchange to be recognized by
the Indian Government under the Securities Contracts Regulation Act. In 1980, the
8 KLE’s Institute of Management Studies and Research, Hubli
exchange moved to the PhirozeJeeieebhoy Towers at Dalai Street, Fort area. In
1986, it developed the BSE SENSEX index, giving the BSE a means to measure
overall performance of the exchange. In 2000, the BSE used this index to open its
derivatives market, trading SENSEX futures contracts. The development of
SENSEX options along with equity derivatives followed in 2001 and 2002,
expanding the BSE's trading platform.
Historically an open outcry floor trading exchange, the Bombay Stock Exchange
switched to an electronic trading system developed by CMC Ltd in 1995. It took
the exchange only fifty days to make this transition. This automated, screen based
trading platform called BSE On-line trading (BOLT) had a capacity of 8 million
orders per day. The BSE has also introduced a centralized exchange-based internet
trading system, BSEWEBx.co.in to enable investors anywhere in the world to
trade on the BSE platform.
The BSE is also a Partner Exchange of the United Nations Sustainable stock
Exchange initiative, joining in September 2012.
NATIONAL STOCK EXCHANGE (NSE)
The National Stock Exchange of India Limited (NSE) is the leading stock
exchange of India, located in Mumbai. NSE was established in 1992 as the first
demutualized electronic exchange in the country. NSE was the first exchange in
the country to provide a modern, fully automated screen-based electronic trading
system which offered easy trading facility to the investors spread across the length
and breadth of the country.
NSE has a market capitalization of more than US$1.65 trillion, making it the
world’s 12th largest stock exchange as of 23 January 2015. NSE's flagship index,
the CNX Nifty, the 50 stock indexes, is used extensively by investors in India and
around the world as a barometer of the Indian capital markets.
NSE was set up by a group of leading Indian financial institutions at the behest of
the government of India to bring transparency to the Indian capital market. Based
on the recommendations laid out by the government committee, NSE has been
established with a diversified shareholding comprising domestic and global
investors. The key domestic investors include Life InsuranceCorporation of India,
State Bank of India, IFCL Limited IDFC Limited and Stock Holding Corporation
of India Ltd. And the key global investors are Gagil FDI Limited, GS Strategic
Investments Limited, SAIF II SE Investments Mauritius Limited, Aranda
Investments (Mauritius) PVT Limited and PI Opportunities Fund I.
9 KLE’s Institute of Management Studies and Research, Hubli
NSE offers trading, clearing and settlement services in equity, equity derivatives,
debt and currency derivatives segments. It is the first exchange in India to
introduce electronic trading facility thus connecting together the investor base of
the entire country. NSE has 2500 VSATs and 3000 leased lines spread over more
than 2000 cities across India.
The exchange was incorporated in 1992 as a tax-paying company and was
recognized as a stock exchange in 1993 under the Securities Contracts (Regulation)
Act, 1956, when P.V.Narasimha Rao was the Prime Minister of India and
Manmohan Singh was the Finance Minister. NSE commenced operations in the
Wholesale Debt Market (WDM) segment in June 1994. The capital market
(equities) segment of the NSE commenced operations in November 1994, while
operations in the derivatives segment commenced in June 2000.
INDICES
In India major Indices are there known as SENSEX and NIFTY. The SENSEX
was launched in the year 1989 and NIFTY launched in the year 1995. The Sensex
have 30 listed companies based on the market capitalization and Nifty has 50 listed
companies based on the market capitalization.
Later on sector wise Indices are created by the exchange with some terms and
conditions. The rules are like company should be from part of a particular sector,
must rank in 500 companies, in the six month the trading frequency of the
particular company should be more than 90%, should have positive net worth, and
should have listing history of six months.
Under the NIFTY index, Indices were created sector wise such CNX IT, CNX
METAL CNX Small cap and so on. Under SENSEX like S & P midcap, S&P IT,
and so on.
10 KLE’s Institute of Management Studies and Research, Hubli
Chapter -3
Company profile
11 KLE’s Institute of Management Studies and Research, Hubli
BNP Paribas completes acquisition of Sharekhan
NOVEMBER 24/2016
BNP Paribas has announced that it has completed its acquisition of brokerage firm
Sharekhan, a deal that was first announced in July 2015. The transaction has now
been finalised after receiving approvals from all the relevant regulatory authorities.
Tarun Shah, CEO and Director of Sharekhan, has announced his retirement.
Jaideep Arora, Director, who has been with Sharekhan since its founding in 2000,
has been appointed as CEO with immediate effect, BNP Paribas said in a press
statement.
Sharekhan is the retail brokering arm of SSKI; SSKI is SS Kantilal Ishwarlal
Securities Pvt. Ltd. It is an organization with more than eight decades of trust and
credibility in the stock market.
12 KLE’s Institute of Management Studies and Research, Hubli
As the punch line of the company says it’s a guide to the financial jungle it has its
many group of companies carrying on financial activities.
Sharekhan – Retail broking brand
Sharekhan is the retail broking arm of SSKI group. Sharekhan has successfully
transformed into a full fledge retail brand of SSKI. It is a one stop shop for all kind
of trading activities related to share and other recent happenings like derivative
market and evolved commodity market in India.
2.2.1) Sharekhan.com
Sharekhan.com is the answer for the highly volatile stock market in India.
As the market has grown leaps and bounces in the recent year. SEBI (Securities &
Exchange Board of India) has made Demat Account mandatory for trading in any
of the stock exchanges. Share khan along with banks in India has fund transfer
facility with many of these banks.
The online form of trading is carried on through Sharkhan.com. It allows the
clients to access the website to know about the latest news in the market and the
impact it has on the various scrips. SSKI is in the Indian securities business since
1922. Share khan is serving Institutional Investors –Domestic /International. The
institutional Research team is rated as one of the best in industry Sharekhan has
been rated as among Top 3 domestic brokerage and rated as one of the most
aggressive in the industry.
2.2.2) SSKI Group Companies
 SSKI Investor Services Ltd. (Sharekhan)
 S.S. Kantilal Ishwarlal Securities.
 SSKI Corporate Finance.
2.2.3) Vision:
To be the best retail broking brand in the Indian Equities market.
2.2.4) Mission:
To educate and empower the individual investor to make better
investment decisions through quality advice and superior service.
13 KLE’s Institute of Management Studies and Research, Hubli
2.2.5) The Sharekhan Way of Life:
 People driven relationships
 Growth driven
 Values and ethics based
2.2.6) Sharekhan’s Beliefs and Expectations:
At Sharekhan people believe in and promote a culture that ….
Stimulates the employees drive to excel.
 Nurture their entrepreneurial sprit by providing them exposure to
challenging work opportunities and imparting autonomy to function
effectively.
 Enhancing transparency and trust, being non-discriminative to any
practice/procedure/system.
 Acknowledges and rewards individual and team contribution through
appropriate rewards, recognition and compensation.
 Builds a sense of ownership across the organization for adherence to risk
and compliance procedures amongst all employees and channel partners.
2.2.6) Service profile:
 Broking in Equities and derivatives on NSE & BSE.
 Depository Services.
 Commodities Trading on MCX & NCDEX.
 IPO Services.
 Portfolio management services.
 Distribution services.
 Structured products with fixed returns.
2.2.7) Achievements and Awards:
 Rated among the top 20 wired companies along with Reliance, HLL,
Infosys, etc by Business Today Jan 2004 edition.
 Amongst the top 3 online trading websites from India most preferred
financial destination amongst online banking customers.
(Source: Net sense, an independent study of financial services in India)
14 KLE’s Institute of Management Studies and Research, Hubli
 Winner of “Best Financial Website Award. CHIP- Dishnet DSL Web
Awards.
 India’s Most Preferred Broker award given to Sharekhan at the ‘Awaaz
Consumer Awards 2005’ in the “Stock Broking” category.
2.2.8) Area of Operation:
Growing network of share shops from Sharekhan.com to India’s largest chain of
branded retail share shops – 679 shops in 234 towns.
679 branded
share shops
across 234 cities
in India
India’s largest chain of branded
retail share shops
15 KLE’s Institute of Management Studies and Research, Hubli
2.2.9) Competitors Information:
Major Competitors & their Product and Services, Portfolios & Strategies
Competitors information & comparison
Reliance
Securities ltd
Sharekhan Angel Broking Motilal Oswal
Securities ltd
ICICI
Direct.Com
About
The
Broke
r
Reliance
Securities, A
Reliance
Capital Ltd
Company, is
the financial
services
division of
Reliance Anil
DhirubhaiAmb
ani (ADA)
Group.
RelianceADA
group is among
top 3 business
houses with
PAN India
presence.
Incorporated in
2000,Sharekhan is
India’s 2nd largest
stock broker
providing
brokerage
services through
its online trading
website
Sharekhan.com
and 1950 Share
shops which
include branches
& Franchises in
575 cities across
Angel Group
has emerged as
one of the top
3retail broking
houses in India.
Incorporated in
1987, it has
membership on
BSE, NSE and
the two leading
commodity
exchange in
India i.e.
NCDEX &
MCX.
Incorporated in
1987, it is a
well-diversified
financial
services firm
offering a range
of financial
products,
services such as
Wealth Mgt
Broking &
Distribution,
Commodity
Broking, &
Portfolio Mgt
Services.
It is an online
trading &
investment
platform on
ICICI
Securities, the
largest stock
broker firm in
India providing
a wide range of
investment
options to the
retail and
institutional
Customers. It is
part of ICICI
Group India.
Types
of
Broke
r
Full Service
Broker
Full Service
Broker
Full Service
Broker
Full Service
Broker
Full Service
Broker
16 KLE’s Institute of Management Studies and Research, Hubli
Table Shows Stock Brokers fees or charges
Reliance
Securities
ltd
Sharekhan Angel
Broking
MotilalOswal
Securities ltd
Icici
Direct.Com
Trading
Account
opening
Fees
Rs
950(Free
for
individuals
working in
top 500
Companies
or Free for
Prepaid
accounts).
Rs 0 Rs 575 Nil Rs975
Trading
account
AMC
Rs 0 Rs 0 Rs 347 Nil Nil
Demat
Account
Opening
Fees
Nil Nil Rs 0 Nil Nil
Demat
Account
AMC
Rs 300 Rs 0 Rs 0 Rs 441 Rs 450
17 KLE’s Institute of Management Studies and Research, Hubli
Table Shows Trading Brokerage charges
Reliance
Securities
ltd
Sharekhan Angel
Broking
MotilalOswal
Securities ltd
Icici
Direct.Com
Cm
Segment
Cash
delivery
0.40% 0.50% 0.40% to
0.10%
0.50% 0.55%
Cm
Segment
Cash
Intraday
0.03% 0.10% 0.04% to
0.01%
0.10% 0.275%
Margin
Trading _ _ _ _ 0.05% 0.03%
F&O
Segment
Futures
0.05% 0.10% 0.04% to
0.01%
0.10% 0.05% 0.03%
F&O
Segment
Options
Rs 70 per
Lot Rs 100 per
Lot
0.04% to
0.01%
Rs 100 per lot Rs 95 Rs 65
per Lot
Minimum
Brokerage
Charges
5paise per
share
10 paise per
share
_ _ Rs 25
18 KLE’s Institute of Management Studies and Research, Hubli
Table Shows Research tips Reports published
Reliance
Securitie
s ltd
Sharekha
n
Angel
Brokin
g
MotilalOswa
l Securities
ltd
Icici
Direct.Co
m
Daily
Market
Reports
   

Free Tips   
Quarterl
y Result
Analysis
    
News
Alerts
  
Table Shows Investment options available
Reliance
Securities
ltd
Sharekhan Angel
Broking
MotilalOswal
Securities ltd
Icici
Direct.
Com
Stock     
Commodity     
Currency     
IPO     
Mutual Funds     
Bond   
Debt    
Other
Financial
Options
Life
Insurance,
General
_ _ _ Life
Insuran
ce,
General
19 KLE’s Institute of Management Studies and Research, Hubli
Table Shows Customer Services Offered
Reliance
Securities
ltd
Sharekha
n
Angel
Brokin
g
MotilalOsw
al Securities
ltd
Icici
Direct.Co
m
Custome
r
Services

Email
Support
    
Online
Live
Chart
   
Phone
Support
    
Toll
Free
Number
   
20 KLE’s Institute of Management Studies and Research, Hubli
Chapter -4
Introduction to the topic
21 KLE’s Institute of Management Studies and Research, Hubli
TECHNICAL ANALYSIS
Technical analysis is the examination of past price movements to the
forecast future price movements. Technical analysts are sometimes referred to as
chartists because they rely almost exclusively on charts for their analysis.
Technical analysis is applicable to stocks, indices, commodities, futures or any
tradable instrument where the price is influenced by the forces of supply and
demand. Price refers to any combination of open high, low or closes for given
security over a specific timeframe. The timeframe can be used on intraday (tick, 5-
minute, 15-minute or hourly), daily, weekly, or monthly price data and last a few
hours or many years.
A method of evaluating securities by analyzing statistics generated by
market activity, such as past prices and volume. Technical analysts do not attempt
to measure a security's intrinsic value, but instead use charts to identify patterns
that can suggest future activity.
Technical analysts believe that the historical performance of stocks and
markets are indications of future performance. Technical analyst's belief that
securities move according to very predictable trends and patterns.
These trends continue until something happens to change the trend, and
until this change occurs, Technical analysis takes a completely different approach;
it doesn’t care one bit about the “value” of a company. Technicians (some time
called chartists) are only interested in the price movement in the market. Despite
all the fancy and exotic tools it employs, technical analysis really just studies
Supply and demand in a market in an attempt to determine what direction, or trend,
will continue in the future.
22 KLE’s Institute of Management Studies and Research, Hubli
Assumptions of Technical analysis
1. The futures market discounts everything – The technician believes that
the price at any given time is intrinsic value based upon the fundamental
factors affecting the supply and demand of the product.
2. Prices move in trends – Prices can move in one of three directions up,
down or sideways. Once a trend in any of these directions is in effect, it
usually will persist. The market trend is simply the direction of market
prices, a concept which is absolutely essential to the success of technical
analysis.
3. History repeats itself - Technical analysis include the psychology of the
market place. Patterns of human behaviors have been identified and
categorized for several hundred years and are found to be repetitive in
nature. The repetitive nature of the market place is illustrated by specific
chart patterns, from which one can forecast the next move for the prices.
4. Supply and demand- The market value of the scrip is determined by the
interaction of the demand and supply.
TECHNICAL TOOLS
23 KLE’s Institute of Management Studies and Research, Hubli
1. MOVING AVERAGES
Most chart patterns show a lot of variation in price movement. This
can make it difficult for traders to get an idea of a security's overall trend.
One simple method traders use to combat this is to apply moving. A
moving average is the average price of a security over a set amount of time.
By plotting a security's average price, the price movement is smoothed out.
Once the day-to-day fluctuations are removed, traders are better able to
identify the true trend and increase the probability that it will work in their
favor.
Types of Moving Averages:
There are a number of different types of moving averages that vary
in the way they are calculated, but how each average is interpreted remains
the same. The calculations only differ in regards to the weighting that they
place on the price data, shifting from equal weighting of each price point to
more weight being placed on recent data. The three most common types of
moving averages are simple, linear, and exponential.
Simple Moving Average (SMA):
This is the most common method used to calculate the moving
average of prices. It simply takes the sum of all of the past closing prices
over the time period and divides the result by the number of prices used in
the calculation.
For example, in a 13-day moving average, the last 13 closing prices
are added together and then divided by 13. A trader is able to make the
average less responsive to changing prices by increasing the number of
periods used in the calculation. Increasing the number of time periods in the
calculation is one of the best ways to gauge the strength of the long-term
trend and the likelihood that it will reverse.
Many individuals argue that the usefulness of this type of average is
limited because each. Point in the data series has the same impact on the
result regardless of where it occurs in the sequence. The critics argue that
the most recent data is more important and, therefore, it should also have a
higher weighting. This type of criticism has been one of the main factors
leading to the invention of other forms of moving averages.
Chart No: 1
24 KLE’s Institute of Management Studies and Research, Hubli
Linear Weighted Average:
This moving average indicator is the least common out of the three
and is used to address the problem of the equal weighting. The linear
weighted moving average is calculated by taking the sum of all the closing
prices over a certain time period and multiplying them by the position of
the data point and then dividing by the sum of the number of periods. For
example, in a five-day linear weighted average, today's closing price is
multiplied by five, yesterday's by four and so on until the first day in the
period range is reached. These numbers are then added together and
divided by the sum of the multipliers.
Exponential Moving Average:
This moving average calculation uses a smoothing factor to place a
higher weight on recent data points and is regarded as much more efficient
than the linear weighted average. Having an understanding of the
calculation is not generally required for most traders because most charting
packages do the calculation for you. The most important thing to remember
about the exponential moving average is that it is more responsive to new
information relative to the simple moving average. This responsiveness is
one of the key factors of why this is the moving average of choice among
many technical traders. As you can see in Figure 2, a 15-period EMA rises
and falls faster than a 15-period SMA. This slight difference doesn't seem
like much, but it is an important factor to be aware of since it can affect
returns.
.
2. Relative Strength Index:
25 KLE’s Institute of Management Studies and Research, Hubli
Relative Strength Index (RSI) is a popular oscillator. It was first
introduced by Welles Wilder in an article in Commodities (now known as
Futures) Magazine in June, 1978.
The name "Relative Strength Index" is slightly misleading as the
Relative Strength Index does not compare the relative strength of two
securities, but rather the internal strength of a single security. A more
appropriate name might be "Internal Strength Index."
The RSI can be calculated for any number of days depending on the
wish of the technical analyst and the time frame of trading adopted in a
particular stock market. RSI can be calculated for 5, 7, 9 and 14 days. If the
time period taken for calculation is more, the possibility of getting wrong
signals is reduced. Reactionary sustained rise or fall in the price of the scrip
is foretold by the RSI.
The Relative Strength Index is a price-following oscillator that
ranges between 0 and 100. A popular method of analyzing the Relative
Strength Index is to look for a divergence in which the security is making a
new high, but the Relative Strength Index is failing to surpass its previous
high. This divergence is an indication of an impending reversal. When the
Relative Strength Index then turns down and falls below its most recent
trough, it is said to have completed a "failure swing." The failure swing is
considered a confirmation of the impending reversal.
The RSI measures the ratio of up-moves to down-moves and normalizes the
calculation so that the index is expressed in a range of 0-100. If the RSI is
70 or greater, then the instrument is assumed to be overbought (a situation
in which prices have risen more than market expectations). An RSI of 30 or
less is taken as a signal that the instrument may be oversold (a situation in
which prices have fallen more than the market expectations. The RSI
compares the magnitude of a stock's recent gains to the magnitude of its
recent losses and turns that information into a number that ranges from 0 to
100.
26 KLE’s Institute of Management Studies and Research, Hubli
In Mr. Welder’s book, he discusses five uses of the
Relative Strength Index:
1. Tops and Bottoms-The Relative Strength Index usually tops above 70 and
bottoms below 30. It usually forms these tops and bottoms before the
underlying price chart.
2. Chart Formations-The Relative Strength Index often forms chart patterns
such as head and shoulders or triangles that may or may not be visible on
the price chart.
3. Failure Swings-(also known as support or resistance penetrations or
breakouts). This is where the Relative Strength Index surpasses a previous
high (peak) or falls below a recent low (trough).
4. Support and Resistance -The Relative Strength Index shows, sometimes
more clearly than price themselves, levels of support and resistance.
5. Divergences- As discussed above, divergences occur when the price makes
a new high (or low) that is not confirmed by a new high (or low) in the
Relative Strength Index. Prices usually correct and move in the direction of
the Relative Strength Index.
27 KLE’s Institute of Management Studies and Research, Hubli
Chapter-5
Analysis and data
interpretation
Table1: Calculation of Simple moving average
28 KLE’s Institute of Management Studies and Research, Hubli
Date
Infosys
closing 30 SMA
Wipro
closing 30 SMA
Mind tree
closing 30 SMA
TCS
closing 30 SMA
01-04-2016 1205.90002 562.15002 668.15 2455.4
04-04-2016 1243.55005 566.25 676.05 2470.7
05-04-2016 1218.59998 559 658.35 2462.65
06-04-2016 1201.09998 558.20001 667.9 2478.9
07-04-2016 1181.65002 551.79999 671.65 2470.95
08-04-2016 1167.34998 549.54999 667.5 2428.7
11-04-2016 1184.40002 565.75 667.7 2506.65
12-04-2016 1182.30005 569.54999 677 2512.5
13-04-2016 1172.05005 584.90002 691.6 2523.15
14-04-2016 1172.05005 584.90002 691.6 2523.15
15-04-2016 1172.05005 584.90002 691.6 2523.15
18-04-2016 1238.80005 588.59998 730.8 2522.4
19-04-2016 1238.80005 588.59998 730.8 2522.4
20-04-2016 1243.25 601.25 723.95 2451.9
21-04-2016 1226.40002 558.84998 715.8 2423.2
22-04-2016 1213.84998 557.95001 708.3 2417.2
25-04-2016 1217.05005 552.45001 698.5 2448.3
26-04-2016 1232.94995 554.45001 707.35 2488
27-04-2016 1240 560 699.7 2505.55
28-04-2016 1211.44995 553.09998 686.2 2526.95
29-04-2016 1210.84998 554.34998 678.8 2530.05
02-05-2016 1200.65002 548.5 681.85 2525.15
03-05-2016 1180.75 543.84998 670.25 2480.25
04-05-2016 1189.55005 540 661.45 2478.25
05-05-2016 1192.44995 543.09998 664 2474
06-05-2016 1181.44995 533.09998 659 2472.15
09-05-2016 1199.15002 539 657.15 2515.35
10-05-2016 1212.55005 538.65002 645.85 2523.6
11-05-2016 1201.05005 537.79999 652.35 2517.75
12-05-2016 1210.19995 1204.74 542.29999 559.095 660.25 682.0483 2567.05 2491.513
13-05-2016 1206.69995 1204.767 539.65002 558.345 652.9 681.54 2523.4 2493.78
16-05-2016 1213.94995 1203.78 540.79999 557.4967 645.3 680.515 2553.8 2496.55
17-05-2016 1214.05005 1203.628 540.15002 556.8683 645.5 680.0867 2570.2 2500.135
18-05-2016 1209.75 1203.917 539.54999 556.2467 644 679.29 2550.45 2502.52
19-05-2016 1205.34998 1204.707 542.95001 555.9517 644 678.3683 2555.55 2505.34
20-05-2016 1201.75 1205.853 543.40002 555.7467 630.45 677.1333 2532.05 2508.785
23-05-2016 1190.75 1206.065 539.84998 554.8833 640.85 676.2383 2491.7 2508.287
24-05-2016 1188.19995 1206.262 537.65002 553.82 647.75 675.2633 2467.5 2506.787
25-05-2016 1208.84998 1207.488 546.09998 552.5267 648.75 673.835 2526.7 2506.905
29 KLE’s Institute of Management Studies and Research, Hubli
26-05-2016 1231.65002 1209.475 544.95001 551.195 665.35 672.96 2552.8 2507.893
27-05-2016 1246.40002 1211.953 545.40002 549.8783 667.6 672.16 2572.05 2509.523
30-05-2016 1263.44995 1212.775 550.15002 548.5967 671.7 670.19 2635.35 2513.288
31-05-2016 1249.84998 1213.143 545.45001 547.1583 660.9 667.86 2575.1 2515.045
01-06-2016 1256.44995 1213.583 554.5 545.6 654.8 665.555 2631.85 2521.043
02-06-2016 1260.25 1214.712 540.40002 544.985 653.6 663.4817 2646.9 2528.5
03-06-2016 1266.44995 1216.465 540.79999 544.4133 647.45 661.4533 2630.85 2535.622
06-06-2016 1267.09998 1218.133 535.09998 543.835 644.55 659.655 2611.35 2541.057
07-06-2016 1257.19995 1218.942 539.84998 543.3483 650.3 657.7533 2631.45 2545.838
08-06-2016 1238.30005 1218.885 544.59998 542.835 650.7 656.12 2611.1 2549.357
09-06-2016 1185.44995 1218.018 544.79999 542.5583 639.2 654.5533 2577.5 2551.042
10-06-2016 1180.80005 1217.017 545.34998 542.2583 639.35 653.2383 2560.95 2552.072
13-06-2016 1182.55005 1216.413 541.20001 542.015 635.15 651.6817 2551.95 2552.965
14-06-2016 1175.19995 1216.228 543.09998 541.99 643.95 650.805 2534.7 2554.78
15-06-2016 1189.19995 1216.217 547.04999 542.225 640.05 650.0917 2555.7 2557.362
16-06-2016 1186.19995 1216.008 549.90002 542.4517 630.05 648.96 2557.1 2560.132
17-06-2016 1178.30005 1215.903 552.04999 543.0833 630 647.9933 2603.5 2564.51
20-06-2016 1208.59998 1216.218 557.04999 543.685 639.8 647.415 2655.7 2569.188
21-06-2016 1205.90002 1215.997 561 544.43 657.7 647.81 2647.3 2573.312
22-06-2016 1198.55005 1215.913 563.15002 545.275 653.6 647.8517 2665.5 2578.237
23-06-2016 1211.55005 1215.958 563.70001 545.9883 659.95 647.8417 2644.3 2580.812
24-06-2016 1194.5 1215.552 555.15002 546.505 659.9 648.075 2570.7 2582.388
27-06-2016 1166.25 1213.962 548 546.745 651.85 648.2933 2495.35 2580.44
28-06-2016 1161.05005 1212.195 542.40002 546.82 662.8 648.87 2461.8 2576.827
29-06-2016 1176.55005 1211.088 554.54999 547.32 663.4 649.5167 2499.6 2575.132
30-06-2016 1170.75 1209.935 557.95001 547.82 664.85 650.2117 2550.8 2574.973
01-07-2016 1172.09998 1208.947 558.90002 548.3367 673.9 651.66 2501.8 2573.965
04-07-2016 1184.25 1208.73 561.70001 549.065 672.15 652.7033 2494.8 2574.068
05-07-2016 1175.44995 1208.305 564.95001 549.975 678.3 653.7217 2482.7 2574.575
06-07-2016 1175.44995 1207.192 564.95001 550.6033 678.3 654.7067 2482.7 2573.108
07-07-2016 1157.19995 1204.71 559.59998 551.0917 659.35 654.5067 2429.05 2568.983
08-07-2016 1158.75 1201.788 561.65002 551.6333 654.4 654.0667 2425.5 2564.098
11-07-2016 1174.84998 1198.835 568.84998 552.2567 665.55 653.8617 2463.65 2558.375
12-07-2016 1176 1196.373 570.79999 553.1017 661.05 653.8667 2461.5 2554.588
13-07-2016 1193.15002 1194.263 573.95001 553.75 650.45 653.7217 2491.4 2549.907
14-07-2016 1175.84998 1191.45 570.59998 554.7567 653.3 653.7117 2520.3 2545.687
15-07-2016 1072.25 1184.977 554.5 555.2133 637.25 653.3717 2441.9 2539.388
18-07-2016 1081.69995 1178.797 551.95001 555.775 614.2 652.36 2433.5 2533.46
19-07-2016 1086.30005 1173.1 549.25 556.0883 561.55 649.4017 2461.55 2527.797
20-07-2016 1083.05005 1167.925 538.84998 555.8967 570.4 646.725 2493.25 2523.868
21-07-2016 1080.34998 1164.422 542 555.8033 565.95 644.2833 2501.25 2521.327
22-07-2016 1072.65002 1160.817 537.75 555.55 556.9 641.535 2509.15 2519.6
25-07-2016 1080.5 1157.415 542.84998 555.605 551.75 638.755 2551.55 2519.587
26-07-2016 1088.80005 1154.535 546.09998 555.705 565 636.1233 2548.3 2520.04
30 KLE’s Institute of Management Studies and Research, Hubli
27-07-2016 1087.55005 1151.147 549.15002 555.775 565.1 633.625 2576.1 2520.72
28-07-2016 1079.19995 1147.58 553.79999 555.905 582.3 632.0333 2615.55 2522.668
29-07-2016 1073.94995 1144.102 545.04999 555.6717 578.65 630.3217 2618.55 2523.17
01-08-2016 1085 1139.982 557.70001 555.6933 601.6 629.0483 2698 2524.58
02-08-2016 1084.30005 1135.928 549.59998 555.3133 612.95 627.5567 2692.1 2526.073
03-08-2016 1085 1132.143 547.95001 554.8067 600.1 625.7733 2656.25 2525.765
04-08-2016 1072.15002 1127.497 548.20001 554.29 604.85 623.9367 2652.65 2526.043
05-08-2016 1067.40002 1123.26 547.20001 554.025 613 622.3733 2648.9 2528.65
08-08-2016 1078.80005 1120.345 549 554.0583 617.8 621.2383 2651.9 2533.868
09-08-2016 1081.5 1117.693 551.34998 554.3567 596.55 619.03 2650.55 2540.16
10-08-2016 1079.94995 1114.473 542.65002 553.96 572.3 615.9933 2673.9 2545.97
11-08-2016 1077.09998 1111.352 543 553.4617 580.7 613.1883 2704.3 2551.087
12-08-2016 1063.30005 1107.725 543.75 552.9567 579.8 610.0517 2732.35 2558.772
15-08-2016 1063.30005 1103.693 543.75 552.3583 579.8 606.9733 2732.35 2566.69
16-08-2016 1050.94995 1099.543 536.5 551.41 569.15 603.335 2691.45 2573.648
17-08-2016 1033.40002 1094.808 527.79999 550.1717 566.35 599.6033 2623.9 2578.355
18-08-2016 1024.30005 1090.378 525.09998 549.0217 564.75 596.45 2636.7 2585.277
19-08-2016 1021.09998 1085.79 520.09998 547.6367 565.7 593.4933 2603.95 2591.225
22-08-2016 1015.40002 1080.475 515.5 545.8583 551.25 589.6833 2551.45 2594.152
23-08-2016 1039.25 1075.917 519.59998 544.1517 566.2 586.5217 2603.2 2598.875
24-08-2016 1057.55005 1071.397 519.65002 542.3417 568.6 583.7933 2571.9 2601.558
25-08-2016 1036.55005 1066.753 504 540.1217 567.8 580.9433 2550.1 2602.552
26-08-2016 1020.75 1065.037 490 537.9717 569.25 578.6767 2529.15 2605.46
29-08-2016 1022.25 1063.055 478.79999 535.5333 564.95 577.035 2501.6 2607.73
30-08-2016 1041 1061.545 489.45001 533.54 570.15 577.3217 2548.7 2610.635
31-08-2016 1036.80005 1060.003 491.64999 531.9667 562.55 577.06 2512.55 2611.278
01-09-2016 1037.65002 1058.58 483.95001 530.0317 553.75 576.6533 2507.6 2611.49
02-09-2016 1031.05005 1057.193 483.60001 528.2267 548.85 576.385 2513.5 2611.635
05-09-2016 1031.05005 1055.545 483.60001 526.2517 548.85 576.2883 2513.5 2610.367
06-09-2016 1045.09998 1054.088 482.89999 524.145 525 574.955 2484.05 2608.225
07-09-2016 1055 1053.003 481.75 521.8983 518.9 573.415 2447 2603.922
08-09-2016 1037.90002 1051.627 473.95001 519.2367 515.3 571.1817 2321.15 2594.108
09-09-2016 1036 1050.362 480.64999 517.09 522.8 569.32 2352.5 2585.24
12-09-2016 1054 1049.328 480.39999 514.5133 516.5 566.4833 2359.1 2573.943
13-09-2016 1054 1048.318 480.39999 512.2067 516.5 563.2683 2359.1 2562.843
14-09-2016 1047.09998 1047.055 478.04999 509.8767 513.5 560.3817 2328.55 2551.92
15-09-2016 1041.34998 1046.028 478.45001 507.5517 514 557.3533 2328.05 2541.1
16-09-2016 1060.34998 1045.793 479.39999 505.2917 512.2 553.9933 2361.15 2531.508
19-09-2016 1061.15002 1045.205 479.95001 502.99 505.25 550.2417 2407.35 2523.357
20-09-2016 1050.34998 1044.167 481.04999 500.6467 502.1 547.0933 2411.1 2515.375
21-09-2016 1056.69995 1043.392 483.85001 498.6867 510.25 545.025 2413.5 2506.695
22-09-2016 1058.5 1042.772 481.75 496.645 509.75 542.66 2377.65 2495.807
23-09-2016 1043 1042.095 480.20001 494.5267 505.2 540.1733 2397.3 2484.638
26-09-2016 1035.69995 1041.175 479.29999 492.3783 497.75 537.4383 2400.85 2473.588
31 KLE’s Institute of Management Studies and Research, Hubli
27-09-2016 1040.44995 1040.825 484.20001 490.635 493 534.9 2430.7 2464.897
28-09-2016 1038.59998 1040.998 483.70001 489.165 492.95 532.4533 2423.45 2458.215
29-09-2016 1029.90002 1041.185 472.20001 487.4017 481.6 529.6817 2434.6 2451.478
30-09-2016 1038.09998 1041.752 478.95001 486.03 482.15 526.8967 2427.2 2445.587
03-10-2016 1037.84998 1042.5 478.95001 484.8117 488.55 524.8067 2411.8 2440.932
04-10-2016 1048.80005 1042.818 481.79999 483.5517 495.95 522.465 2401.1 2434.195
05-10-2016 1041.15002 1042.272 479.54999 482.215 498.4 520.125 2382.55 2427.883
06-10-2016 1026.65002 1041.942 478 481.3483 491.2 517.5717 2384.25 2422.355
07-10-2016 1012.65002 1041.672 476.95001 480.9133 491.85 514.9917 2368.25 2416.992
10-10-2016 1029.55005 1041.915 477 480.8533 500.9 512.8567 2380.1 2412.942
11-10-2016 1029.55005 1041.533 477 480.4383 500.9 510.5483 2380.1 2407.322
12-10-2016 1029.55005 1041.292 477 479.95 500.9 508.4933 2380.1 2402.907
13-10-2016 1052.05005 1041.772 478.25 479.76 489.7 506.3583 2328.5 2396.937
14-10-2016 1027.40002 1041.65 475 479.4733 501.05 504.765 2365.9 2392.017
17-10-2016 1022.04999 1041.35 472.14999 479.0917 490.6 502.8233 2362.9 2386.997
18-10-2016 1038.19995 1041.12 482.75 479.0867 476.85 501.2183 2398.3 2384.138
19-10-2016 1041.59998 1040.673 495 479.5283 476.95 499.82 2394.2 2382.378
20-10-2016 1036.94995 1040.642 495.39999 480.2433 479.05 498.6117 2399.85 2385.002
21-10-2016 1038.09998 1040.712 499.20001 480.8617 479 497.1517 2428.7 2387.542
24-10-2016 1029 1039.878 483.95001 480.98 456 495.135 2427.85 2389.833
25-10-2016 1017.34998 1038.657 481.39999 481.0133 454.9 493.0817 2398.65 2391.152
26-10-2016 1014.84998 1037.582 471.54999 480.7967 450.2 490.9717 2396.95 2393.432
27-10-2016 1006.15002 1036.408 461.70001 480.2383 441.5 488.555 2413.25 2396.272
28-10-2016 997.45001 1034.312 462.10001 479.6617 435.95 486.0133 2399.25 2397.542
31-10-2016 997.45001 1032.188 462.10001 479.0667 435.95 483.7033 2399.25 2397.272
01-11-2016 988.84998 1030.138 460.75 478.39 439.55 481.6183 2347.7 2395.158
02-11-2016 981.09998 1027.618 457.89999 477.525 433.55 479.0617 2304.45 2391.523
03-11-2016 966.90002 1024.565 447.60001 476.3867 428.35 476.3483 2319.95 2389.6
04-11-2016 970.79999 1022.158 452.5 475.4633 425.15 473.68 2330.1 2387.36
07-11-2016 978.75 1020.26 450 474.4867 429.25 471.3967 2279.35 2383.31
08-11-2016 982.79999 1018.338 451.75 473.405 442.65 469.7183 2283.7 2378.41
09-11-2016 955.84998 1015.58 446.89999 472.1783 436.15 467.825 2171.05 2369.997
10-11-2016 938.59998 1012.537 444.95001 471.27 437.4 466.3517 2158.05 2360.778
11-11-2016 921.84998 1008.662 442.35001 470.05 423.55 464.3983 2105.05 2350.04
14-11-2016 921.84998 1004.795 442.35001 468.83 423.55 462.2317 2105.05 2339.815
15-11-2016 924.75 1000.66 447.95001 467.7017 430.55 460.0517 2122.1 2330.515
16-11-2016 940.09998 997.2917 445.29999 466.56 437.9 458.035 2190.25 2324.105
17-11-2016 929.54999 994.055 438.39999 465.24 441.75 456.3867 2142.15 2316.035
18-11-2016 919.79999 990.96 437.14999 463.9133 442.25 454.7333 2123.15 2307.865
21-11-2016 911.15002 987.0133 441.79999 462.74 441.8 452.7633 2132.55 2299.613
22-11-2016 913.95001 983.16 450.39999 461.8533 453.15 451.1717 2134.3 2291.42
23-11-2016 920.5 979.525 448.89999 460.9167 453.5 449.5917 2156.7 2283.973
24-11-2016 932.70001 975.5467 450.75 460 462.85 448.6967 2186.5 2279.24
25-11-2016 977.29999 973.8767 464.75 459.6583 478.25 447.9367 2300.85 2277.072
32 KLE’s Institute of Management Studies and Research, Hubli
28-11-2016 979.65002 972.4633 460.60001 459.2733 477.8 447.51 2277.3 2274.218
29-11-2016 972.65002 970.2783 465.14999 458.6867 473.65 447.4033 2258.4 2269.555
30-11-2016 975.45001 968.0733 465.25 457.695 477.35 447.4167 2276.75 2265.64
01-12-2016 976.04999 966.0433 468.29999 456.7917 466.6 447.0017 2266.45 2261.193
02-12-2016 964.09998 963.5767 460.39999 455.4983 460.45 446.3833 2223.9 2254.367
05-12-2016 961.40002 961.3233 456.64999 454.5883 448.35 446.1283 2186.45 2246.32
06-12-2016 966.95001 959.6433 457.79999 453.8017 459.8 446.2917 2190.45 2239.38
07-12-2016 966.59998 958.035 453.35001 453.195 457.75 446.5433 2158.2 2231.422
08-12-2016 984.75 957.3217 458.60001 453.0917 462.2 447.2333 2196.9 2224.21
09-12-2016 987.34998 956.985 458.10001 452.9583 470.65 448.39 2193.45 2217.35
12-12-2016 977.5 956.32 453.54999 452.6733 468.25 449.4667 2206.25 2210.917
13-12-2016 990.04999 956.36 463.75 452.7733 492.5 451.2317 2200.85 2206.022
14-12-2016 999.04999 956.9583 466.29999 453.0533 502.9 453.5433 2207.9 2202.803
15-12-2016 993.25 957.8367 466.10001 453.67 495.3 455.775 2259.5 2200.788
16-12-2016 1004.20001 958.95 463.5 454.0367 501.35 458.315 2281.75 2199.177
19-12-2016 1002.20001 959.7317 463.54999 454.4883 500.1 460.6767 2287.5 2199.448
20-12-2016 1010.40002 960.6517 466.64999 454.985 494.1 462.3917 2337.75 2201.25
21-12-2016 1003.70001 962.2467 462.45001 455.5033 493.95 464.3183 2312.75 2205.973
22-12-2016 985.20001 963.8 461.70001 456.0617 495.4 466.2517 2309.85 2211.033
23-12-2016 989.29999 966.0483 458.75 456.6083 496.9 468.6967 2290.2 2217.205
26-12-2016 983 968.0867 456.10001 457.0667 487.9 470.8417 2292.1 2223.44
27-12-2016 999.25 970.57 465.20001 457.6417 486.2 472.6967 2321.85 2230.098
28-12-2016 999.15002 972.5383 469.35001 458.4433 510.15 475.105 2315.8 2234.283
29-12-2016 994.09998 974.69 472.35001 459.575 523.85 477.8417 2350.75 2241.237
30-12-2016 1010.70001 977.72 474.45001 460.8183 521.65 480.4883 2361.95 2249.197
02-01-2017 1001.59998 980.735 471.54999 461.81 516.7 482.985 2359.05 2256.747
03-01-2017 994.65002 983.425 467 462.3633 507.9 484.81 2368.5 2264.553
04-01-2017 998.29999 986.0183 475.60001 463.2533 526.4 487.24 2378.55 2271.948
05-01-2017 996.40002 988.1417 480.39999 464.2417 523.7 489.2683 2334.55 2276.883
06-01-2017 971.45001 987.9467 469.95001 464.415 500.2 490 2283.6 2276.308
09-01-2017 970.54999 987.6433 472 464.795 495.5 490.59 2303.75 2277.19
10-01-2017 970.59998 987.575 476.5 465.1733 487.15 491.04 2315.45 2279.092
11-01-2017 969 987.36 476.20001 465.5383 487.3 491.3717 2323.05 2280.635
12-01-2017 1000.04999 988.16 483.20001 466.035 491.3 492.195 2343.3 2283.197
13-01-2017 975.15002 988.5283 484.64999 466.8433 490.85 493.2083 2252 2284.133
16-01-2017 955.70001 988.3383 484.75 467.78 484.95 494.4283 2258.55 2286.537
17-01-2017 956.04999 987.975 482.39999 468.6 484.85 495.2633 2277.65 2289.443
18-01-2017 950.90002 987.4517 482.95001 469.5867 495.5 496.5217 2295 2294.003
19-01-2017 958.54999 986.5783 479 470.2667 485.1 497.285 2290.3 2297.117
20-01-2017 948.79999 985.2933 477.89999 470.9267 475.25 497.4383 2287.45 2300.25
23-01-2017 951.75 984.435 479.75 471.8 471.3 497.54 2305.7 2303.565
24-01-2017 945.09998 982.9367 481.5 472.3917 470.25 496.7983 2318 2307.47
25-01-2017 936.65002 980.8567 473.70001 472.6383 461.65 495.4233 2352.7 2312.297
26-01-2017 936.65002 978.97 473.70001 472.8917 461.65 494.3017 2352.7 2315.403
33 KLE’s Institute of Management Studies and Research, Hubli
27-01-2017 942.15002 976.9017 465.54999 472.96 472.5 493.34 2358.05 2317.947
30-01-2017 948.34998 975.1067 465.75 473.0333 465.55 492.1883 2334.2 2319.503
31-01-2017 929.29999 972.4033 458 472.745 450.5 490.735 2229.9 2315.908
01-02-2017 916.54999 969.4983 456 472.53 459.85 489.5983 2169.45 2311.132
02-02-2017 935.34998 967.8367 455.64999 472.3283 461 488.4517 2205.8 2307.663
03-02-2017 934.95001 966.025 457.75 472.295 459.35 487.2 2233.75 2305.782
06-02-2017 934.45001 964.4067 461.10001 472.4617 464.85 486.4317 2240.55 2304.063
07-02-2017 944.75 962.59 458.54999 472.24 452.8 485.3183 2244.8 2301.495
08-02-2017 936.45001 960.5 460.5 471.945 450.1 483.3167 2262.65 2299.723
09-02-2017 948.09998 958.9667 466 471.7333 457.6 481.1083 2324.25 2298.84
10-02-2017 968.04999 957.545 469.25 471.56 466.65 479.275 2396.7 2299.998
13-02-2017 983.5 956.9417 474.45001 471.6567 468.15 477.6567 2410.3 2301.707
14-02-2017 987.29999 956.6967 476.70001 471.98 455.1 475.8967 2402.95 2302.855
15-02-2017 982.34998 956.165 474.70001 471.95 457.65 473.605 2415.7 2304.093
16-02-2017 1011.90002 956.6817 480.79999 471.9633 468 471.7483 2446.9 2307.838
17-02-2017 999.70001 957.6233 475.35001 472.1433 475.15 470.9133 2408.15 2311.99
20-02-2017 1011.70001 958.995 475.64999 472.265 474.4 470.21 2506.5 2318.748
21-02-2017 1012.95001 960.4067 475.79999 472.2417 474.4 469.785 2464.3 2323.71
22-02-2017 991.84998 961.1683 474.5 472.185 468.2 469.1483 2409.55 2326.593
23-02-2017 1009.04999 961.4683 486.10001 472.2817 469.9 468.435 2481.65 2331.205
24-02-2017 1009.04999 962.5983 486.10001 472.33 469.9 467.7367 2481.65 2338.86
27-02-2017 1012.75 964.5 489.75 472.4967 471.15 467.2767 2488.9 2346.538
28-02-2017 1012.29999 966.375 488.79999 472.71 474.3 466.925 2466.5 2352.833
01-03-2017 1025 968.845 488.54999 472.8967 471.95 466.14 2480.05 2359.002
02-03-2017 1020.65002 970.915 490.20001 473.27 460.3 465.3133 2501.15 2366.03
03-03-2017 1031.15002 973.66 493.85001 473.8017 464.6 464.9583 2492.35 2372.86
06-03-2017 1033.84998 976.3967 491.89999 474.2067 460.25 464.59 2470.65 2378.358
07-03-2017 1019.70001 978.8833 495.14999 474.6617 478.7 464.8717 2500.7 2384.448
08-03-2017 1007.25 981.2367 495.10001 475.375 469.25 465.125 2513.9 2389.822
09-03-2017 1011.59998 983.735 484.5 475.735 472.65 465.4917 2519.55 2395.383
10-03-2017 1020.09998 986.3333 487.04999 476.4517 474.8 465.5683 2541.8 2401.508
13-03-2017 1020.09998 988.725 487.04999 477.1617 474.8 465.8767 2541.8 2408.428
14-03-2017 1032.5 992.165 501.35001 478.6067 470.85 466.555 2562.35 2419.51
15-03-2017 1012.09998 995.35 494.79999 479.9 466.55 466.7783 2500.3 2430.538
16-03-2017 1028.5 998.455 500.54999 481.3967 469.75 467.07 2518.95 2440.977
17-03-2017 1040 1001.957 504.25 482.9467 473.45 467.54 2526.85 2450.747
20-03-2017 1020.59998 1004.828 497.5 484.16 474.1 467.8483 2480.8 2458.755
21-03-2017 1032 1007.737 498.64999 485.4967 474.85 468.5833 2486.15 2466.8
22-03-2017 1027.80005 1010.782 500.54999 486.8317 472.3 469.3233 2479.1 2474.015
23-03-2017 1040.59998 1013.865 510 488.2983 472.2 469.81 2458.9 2478.503
24-03-2017 1031.80005 1015.99 513.25 489.765 469.55 469.9067 2426.75 2479.505
27-03-2017 1028.80005 1017.5 504 490.75 461.3 469.6783 2412.1 2479.565
28-03-2017 1035.09998 1019.093 507.54999 491.7783 459.95 469.84 2429.85 2480.462
29-03-2017 1031.34998 1020.727 512.25 493.03 456.1 469.7883 2443.75 2481.397
34 KLE’s Institute of Management Studies and Research, Hubli
CHARTS
INFOSYS(Simple Moving average):
INTERPRETATION:
Moving averages provides buy and sell signal. Above figure
shows the calculation of simple moving average (SMA) for 30 days.
Downward penetration of the rising average indicates the possibility of a
further fall and gives the sell signal. Upward penetration of a falling
average would indicate the possibility of the further rise and gives the buy
signal. From the above chart we came to know that in the month of
December 2016, was right time to buy the share of Infosys. And in the
month of January 2017, was right time to sell the shares because prices
were falling.
WIPRO (Simple Moving average) :
30-03-2017 1024.5 1021.147 515.95001 494.2017 453.2 469.295 2443.75 2481.292
31-03-22017 1020.79999 1021.85 515.70001 495.5467 452.95 468.555 2431.1 2482.057
35 KLE’s Institute of Management Studies and Research, Hubli
INTERPRETATION:
Moving averages provides buy and sell signal. Above figure
shows the calculation of simple moving average (SMA) for 30 days.
Downward penetration of the rising average indicates the possibility of a
further fall and gives the sell signal. Upward penetration of a falling
average would indicate the possibility of the further rise and gives the buy
signal. From the above chart we came to know that in the month of
December 2016, was right time to buy the shares of Wipro. And in the
month of February 2017, was right time to sell the shares.
MINDTREE (Simple Moving average):
36 KLE’s Institute of Management Studies and Research, Hubli
INTERPRETATION:
Moving averages provides buy and sell signal. Above figure
shows the calculation of simple moving average (SMA) for 30 days.
Downward penetration of the rising average indicates the possibility of a
further fall and gives the sell signal. Upward penetration of a falling
average would indicate the possibility of the further rise and gives the buy
signal. From the above chart we came to know that in the month of
December 2016, was right time to buy the shares of Mindtree. And in the
month of February 2017, was right time to sell the shares because prices
were falling.
TCS (Simple Moving average):
37 KLE’s Institute of Management Studies and Research, Hubli
INTERPRETATION:
Moving averages provides buy and sell signal. Above figure
shows the calculation of simple moving average (SMA) for 30 days.
Downward penetration of the rising average indicates the possibility of a
further fall and gives the sell signal. Upward penetration of a falling
average would indicate the possibility of the further rise and gives the buy
signal. From the above chart we came to know that in the month of
December 2016 was right time to buy the shares of TCS. And in the month
of February 2017 was right time to sell the shares because prices were
falling.
Table 2) Calculationof Relative Strength Index:
38 KLE’s Institute of Management Studies and Research, Hubli
Infosys ( Relative Strength Index):
Date Infosysclosing Change Gain Loss RS Value RSI
01-04-2016 1205.90002
04-04-2016 1243.55005 37.65003 37.65003 0
05-04-2016 1218.59998 -24.9501 0 24.95007
06-04-2016 1201.09998 -17.5 0 17.5
07-04-2016 1181.65002 -19.45 0 19.44996
08-04-2016 1167.34998 -14.3 0 14.30004
11-04-2016 1184.40002 17.05004 17.05004 0
12-04-2016 1182.30005 -2.09997 0 2.09997
13-04-2016 1172.05005 -10.25 0 10.25
14-04-2016 1172.05005 0 0 0
15-04-2016 1172.05005 0 0 0
18-04-2016 1238.80005 66.75 66.75 0
19-04-2016 1238.80005 0 0 0
20-04-2016 1243.25 4.44995 4.44995 0
21-04-2016 1226.40002 -16.85 0 16.84998 1.194497 54.43147
22-04-2016 1213.84998 -12.55 0 12.55004 0.748198 42.79824
25-04-2016 1217.05005 3.20007 3.20007 0 0.983334 49.57985
26-04-2016 1232.94995 15.8999 15.8999 0 1.421854 58.70932
27-04-2016 1240 7.05005 7.05005 0 2.041034 67.11645
28-04-2016 1211.44995 -28.5501 0 28.55005 1.627311 61.93827
29-04-2016 1210.84998 -0.59997 0 0.59997 1.37306 57.86032
02-05-2016 1200.65002 -10.2 0 10.19996 1.232278 55.20271
03-05-2016 1180.75 -19.9 0 19.90002 1.098138 52.3387
04-05-2016 1189.55005 8.80005 8.80005 0 1.197405 54.49179
05-05-2016 1192.44995 2.8999 2.8999 0 1.230117 55.15931
06-05-2016 1181.44995 -11 0 11 0.424485 29.79918
09-05-2016 1199.15002 17.70007 17.70007 0 0.602107 37.5822
10-05-2016 1212.55005 13.40003 13.40003 0 0.691922 40.89563
11-05-2016 1201.05005 -11.5 0 11.5 0.731178 42.23585
12-05-2016 1210.19995 9.1499 9.1499 0 0.955351 48.8583
13-05-2016 1206.69995 -3.5 0 3.5 0.878591 46.76862
16-05-2016 1213.94995 7.25 7.25 0 0.777126 43.72937
17-05-2016 1214.05005 0.1001 0 -0.1001 0.695244 41.01144
18-05-2016 1209.75 -4.30005 0 4.30005 0.972086 49.29228
19-05-2016 1205.34998 -4.40002 0 4.40002 0.914992 47.78047
20-05-2016 1201.75 -3.59998 0 3.59998 1.018933 50.46888
23-05-2016 1190.75 -11 0 11 1.203252 54.61255
24-05-2016 1188.19995 -2.55005 0 2.55005 0.973911 49.33916
25-05-2016 1208.84998 20.65003 20.65003 0 1.316909 56.83904
26-05-2016 1231.65002 22.80004 22.80004 0 2.231904 69.05848
27-05-2016 1246.40002 14.75 14.75 0 2.159509 68.34951
39 KLE’s Institute of Management Studies and Research, Hubli
30-05-2016 1263.44995 17.04993 17.04993 0 2.249077 69.22203
31-05-2016 1249.84998 -13.6 0 13.59997 2.138856 68.14126
01-06-2016 1256.44995 6.59997 6.59997 0 2.079347 67.52559
02-06-2016 1260.25 3.80005 3.80005 0 2.360866 70.24577
03-06-2016 1266.44995 6.19995 6.19995 0 2.334181 70.00763
06-06-2016 1267.09998 0.65003 0 -0.65003 2.367265 70.30231
07-06-2016 1257.19995 -9.90003 0 9.90003 2.068692 67.41283
08-06-2016 1238.30005 -18.8999 0 18.8999 1.559425 60.92872
09-06-2016 1185.44995 -52.8501 0 52.8501 0.849283 45.92499
10-06-2016 1180.80005 -4.6499 0 4.6499 0.90226 47.43094
13-06-2016 1182.55005 1.75 1.75 0 0.943074 48.53516
14-06-2016 1175.19995 -7.3501 0 7.3501 0.684334 40.62934
15-06-2016 1189.19995 14 14 0 0.601782 37.56952
16-06-2016 1186.19995 -3 0 3 0.450729 31.06914
17-06-2016 1178.30005 -7.8999 0 7.8999 0.275319 21.58826
20-06-2016 1208.59998 30.29993 30.29993 0 0.602983 37.61632
21-06-2016 1205.90002 -2.69996 0 2.69996 0.525797 34.4605
22-06-2016 1198.55005 -7.34997 0 7.34997 0.458534 31.43801
23-06-2016 1211.55005 13 13 0 0.51821 34.13295
24-06-2016 1194.5 -17.0501 0 17.05005 0.448538 30.96486
27-06-2016 1166.25 -28.25 0 28.25 0.393667 28.24682
28-06-2016 1161.05005 -5.19995 0 5.19995 0.433235 30.22778
29-06-2016 1176.55005 15.5 15.5 0 0.89335 47.18357
30-06-2016 1170.75 -5.80005 0 5.80005 0.881205 46.84258
01-07-2016 1172.09998 1.34998 1.34998 0 0.876477 46.70864
04-07-2016 1184.25 12.15002 12.15002 0 1.117153 52.76676
05-07-2016 1175.44995 -8.80005 0 8.80005 0.840209 45.65835
06-07-2016 1175.44995 0 0 0 0.87056 46.54007
07-07-2016 1157.19995 -18.25 0 18.25 0.774089 43.63304
08-07-2016 1158.75 1.55005 1.55005 0 0.466274 31.79994
11-07-2016 1174.84998 16.09998 16.09998 0 0.657662 39.67409
12-07-2016 1176 1.15002 1.15002 0 0.729454 42.17828
13-07-2016 1193.15002 17.15002 17.15002 0 0.779244 43.79636
14-07-2016 1175.84998 -17.3 0 17.30004 0.776914 43.72265
15-07-2016 1072.25 -103.6 0 103.6 0.408619 29.0085
18-07-2016 1081.69995 9.44995 9.44995 0 0.483902 32.61011
19-07-2016 1086.30005 4.6001 4.6001 0 0.413009 29.22902
20-07-2016 1083.05005 -3.25 0 3.25 0.419974 29.57618
21-07-2016 1080.34998 -2.70007 0 2.70007 0.403834 28.76652
22-07-2016 1072.65002 -7.69996 0 7.69996 0.309406 23.62952
25-07-2016 1080.5 7.84998 7.84998 0 0.3786 27.46264
26-07-2016 1088.80005 8.30005 8.30005 0 0.43292 30.21242
27-07-2016 1087.55005 -1.25 0 1.25 0.487114 32.75567
28-07-2016 1079.19995 -8.3501 0 8.3501 0.448145 30.94612
40 KLE’s Institute of Management Studies and Research, Hubli
29-07-2016 1073.94995 -5.25 0 5.25 0.324632 24.50735
01-08-2016 1085 11.05005 11.05005 0 0.390898 28.10398
02-08-2016 1084.30005 -0.69995 0 0.69995 0.274817 21.5574
03-08-2016 1085 0.69995 0 -0.69995 0.312264 23.79583
04-08-2016 1072.15002 -12.85 0 12.84998 0.997582 49.93948
05-08-2016 1067.40002 -4.75 0 4.75 0.689807 40.82165
08-08-2016 1078.80005 11.40003 11.40003 0 0.837311 45.57262
09-08-2016 1081.5 2.69995 2.69995 0 0.963826 49.079
10-08-2016 1079.94995 -1.55005 0 1.55005 0.990407 49.75902
11-08-2016 1077.09998 -2.84997 0 2.84997 1.120758 52.84706
12-08-2016 1063.30005 -13.7999 0 13.79993 0.660416 39.77412
15-08-2016 1063.30005 0 0 0 0.496545 33.17943
16-08-2016 1050.94995 -12.3501 0 12.3501 0.407287 28.94129
17-08-2016 1033.40002 -17.5499 0 17.54993 0.354476 26.17069
18-08-2016 1024.30005 -9.09997 0 9.09997 0.336231 25.16262
19-08-2016 1021.09998 -3.20007 0 3.20007 0.180769 15.30943
22-08-2016 1015.40002 -5.69996 0 5.69996 0.169879 14.52109
23-08-2016 1039.25 23.84998 23.84998 0 0.453405 31.19604
24-08-2016 1057.55005 18.30005 18.30005 0 0.793931 44.2565
25-08-2016 1036.55005 -21 0 21 0.64581 39.23963
26-08-2016 1020.75 -15.8001 0 15.80005 0.43586 30.35531
29-08-2016 1022.25 1.5 1.5 0 0.424198 29.78506
30-08-2016 1041 18.75 18.75 0 0.615689 38.10689
31-08-2016 1036.80005 -4.19995 0 4.19995 0.607595 37.7953
01-09-2016 1037.65002 0.84997 0 -0.84997 0.708688 41.47557
02-09-2016 1031.05005 -6.59997 0 6.59997 0.659271 39.73257
05-09-2016 1031.05005 0 0 0 0.758203 43.12374
06-09-2016 1045.09998 14.04993 14.04993 0 1.180694 54.14305
07-09-2016 1055 9.90002 9.90002 0 1.551661 60.80984
08-09-2016 1037.90002 -17.1 0 17.09998 1.241554 55.38808
09-09-2016 1036 -1.90002 0 1.90002 1.313308 56.77185
12-09-2016 1054 18 18 0 1.224335 55.04274
13-09-2016 1054 0 0 0 0.946007 48.61272
14-09-2016 1047.09998 -6.90002 0 6.90002 1.204258 54.63326
15-09-2016 1041.34998 -5.75 0 5.75 1.495192 59.92293
16-09-2016 1060.34998 19 19 0 1.915866 65.70487
19-09-2016 1061.15002 0.80004 0 -0.80004 1.493874 59.90174
20-09-2016 1050.34998 -10.8 0 10.80004 1.285863 56.25285
21-09-2016 1056.69995 6.34997 6.34997 0 1.394817 58.24316
22-09-2016 1058.5 1.80005 1.80005 0 1.659062 62.39276
23-09-2016 1043 -15.5 0 15.5 1.209098 54.73265
26-09-2016 1035.69995 -7.30005 0 7.30005 0.85415 46.06694
27-09-2016 1040.44995 4.75 4.75 0 0.774243 43.63794
28-09-2016 1038.59998 -1.84997 0 1.84997 1.014227 50.35316
41 KLE’s Institute of Management Studies and Research, Hubli
29-09-2016 1029.90002 -8.69996 0 8.69996 0.891072 47.11993
30-09-2016 1038.09998 8.19996 8.19996 0 0.716071 41.72736
03-10-2016 1037.84998 -0.25 0 0.25 0.712889 41.61908
04-10-2016 1048.80005 10.95007 10.95007 0 1.034449 50.84665
05-10-2016 1041.15002 -7.65003 0 7.65003 0.996098 49.90227
06-10-2016 1026.65002 -14.5 0 14.5 0.487453 32.77099
07-10-2016 1012.65002 -14 0 14 0.39789 28.46361
10-10-2016 1029.55005 16.90003 16.90003 0 0.701793 41.23845
11-10-2016 1029.55005 0 0 0 0.610754 37.91728
12-10-2016 1029.55005 0 0 0 0.584947 36.90641
13-10-2016 1052.05005 22.5 22.5 0 1.166821 53.84944
14-10-2016 1027.40002 -24.65 0 24.65003 0.884079 46.92367
17-10-2016 1022.04999 -5.35003 0 5.35003 0.760884 43.21035
18-10-2016 1038.19995 16.14996 16.14996 0 0.994673 49.86648
19-10-2016 1041.59998 3.40003 3.40003 0 1.176204 54.04843
20-10-2016 1036.94995 -4.65003 0 4.65003 0.983814 49.59204
21-10-2016 1038.09998 1.15003 1.15003 0 1.003531 50.08812
24-10-2016 1029 -9.09998 0 9.09998 0.75219 42.92856
25-10-2016 1017.34998 -11.65 0 11.65002 0.716329 41.73611
26-10-2016 1014.84998 -2.5 0 2.5 0.835883 45.53029
27-10-2016 1006.15002 -8.69996 0 8.69996 0.902402 47.43489
28-10-2016 997.45001 -8.70001 0 8.70001 0.573705 36.45569
31-10-2016 997.45001 0 0 0 0.573705 36.45569
01-11-2016 988.84998 -8.60003 0 8.60003 0.514898 33.98897
02-11-2016 981.09998 -7.75 0 7.75 0.225859 18.42457
03-11-2016 966.90002 -14.2 0 14.19996 0.254926 20.31405
04-11-2016 970.79999 3.89997 3.89997 0 0.324324 24.48979
07-11-2016 978.75 7.95001 7.95001 0 0.216217 17.77782
08-11-2016 982.79999 4.04999 4.04999 0 0.224786 18.35307
09-11-2016 955.84998 -26.95 0 26.95001 0.173714 14.80035
10-11-2016 938.59998 -17.25 0 17.25 0.137781 12.10966
11-11-2016 921.84998 -16.75 0 16.75 0.129216 11.44295
14-11-2016 921.84998 0 0 0 0.142729 12.49016
15-11-2016 924.75 2.90002 2.90002 0 0.172635 14.722
16-11-2016 940.09998 15.34998 15.34998 0 0.340818 25.41866
17-11-2016 929.54999 -10.55 0 10.54999 0.33464 25.07341
18-11-2016 919.79999 -9.75 0 9.75 0.305456 23.39841
21-11-2016 911.15002 -8.64997 0 8.64997 0.30532 23.39041
22-11-2016 913.95001 2.79999 2.79999 0 0.354947 26.19638
23-11-2016 920.5 6.54999 6.54999 0 0.483871 32.60868
24-11-2016 932.70001 12.20001 12.20001 0 0.576196 36.55611
25-11-2016 977.29999 44.59998 44.59998 0 0.983871 49.59349
28-11-2016 979.65002 2.35003 2.35003 0 0.964961 49.10841
29-11-2016 972.65002 -7 0 7 1.240172 55.36058
42 KLE’s Institute of Management Studies and Research, Hubli
30-11-2016 975.45001 2.79999 2.79999 0 1.699242 62.95256
01-12-2016 976.04999 0.59998 0 -0.59998 2.53324 71.69737
02-12-2016 964.09998 -11.95 0 11.95001 1.893235 65.43661
05-12-2016 961.40002 -2.69996 0 2.69996 1.733001 63.41019
06-12-2016 966.95001 5.54999 5.54999 0 1.537001 60.58338
07-12-2016 966.59998 -0.35003 0 0.35003 1.930905 65.88084
08-12-2016 984.75 18.15002 18.15002 0 3.161399 75.96962
09-12-2016 987.34998 2.59998 2.59998 0 4.560742 82.01679
12-12-2016 977.5 -9.84998 0 9.84998 3.0336 75.20825
13-12-2016 990.04999 12.54999 12.54999 0 3.2256 76.33472
14-12-2016 999.04999 9 9 0 3.123199 75.74699
15-12-2016 993.25 -5.79999 0 5.79999 1.4305 58.8562
16-12-2016 1004.20001 10.95001 10.95001 0 1.662618 62.44298
19-12-2016 1002.20001 -2 0 2 1.921997 65.77683
20-12-2016 1010.40002 8.20001 8.20001 0 2.090484 67.64261
21-12-2016 1003.70001 -6.70001 0 6.70001 1.702669 62.99954
22-12-2016 985.20001 -18.5 0 18.5 1.459696 59.34457
23-12-2016 989.29999 4.09998 4.09998 0 1.645832 62.20471
26-12-2016 983 -6.29999 0 6.29999 1.324242 56.97522
27-12-2016 999.25 16.25 16.25 0 1.664294 62.4666
28-12-2016 999.15002 -0.09998 0 0.09998 1.292386 56.37734
29-12-2016 994.09998 -5.05004 0 5.05004 1.124309 52.92588
30-12-2016 1010.70001 16.60003 16.60003 0 1.746907 63.59541
02-01-2017 1001.59998 -9.10003 0 9.10003 1.215686 54.86725
03-01-2017 994.65002 -6.94996 0 6.94996 0.927273 48.11322
04-01-2017 998.29999 3.64997 3.64997 0 1.092322 52.2062
05-01-2017 996.40002 -1.89997 0 1.89997 0.862191 46.29981
06-01-2017 971.45001 -24.95 0 24.95001 0.613451 38.02103
09-01-2017 970.54999 -0.90002 0 0.90002 0.504661 33.53985
10-01-2017 970.59998 0.04999 0 -0.04999 0.550882 35.52055
11-01-2017 969 -1.59998 0 1.59998 0.714789 41.68377
12-01-2017 1000.04999 31.04999 31.04999 0 1.189261 54.32248
13-01-2017 975.15002 -24.9 0 24.89997 0.895889 47.25429
16-01-2017 955.70001 -19.45 0 19.45001 0.540854 35.10092
17-01-2017 956.04999 0.34998 0 -0.34998 0.543432 35.20932
18-01-2017 950.90002 -5.14997 0 5.14997 0.542857 35.18519
19-01-2017 958.54999 7.64997 7.64997 0 0.448148 30.94627
20-01-2017 948.79999 -9.75 0 9.75 0.445086 30.79998
23-01-2017 951.75 2.95001 2.95001 0 0.513605 33.93256
24-01-2017 945.09998 -6.65002 0 6.65002 0.439114 30.51281
25-01-2017 936.65002 -8.44996 0 8.44996 0.410749 29.11569
26-01-2017 936.65002 0 0 0 0.5448 35.26672
27-01-2017 942.15002 5.5 5.5 0 0.62409 38.42706
30-01-2017 948.34998 6.19996 6.19996 0 0.705688 41.37262
43 KLE’s Institute of Management Studies and Research, Hubli
31-01-2017 929.29999 -19.05 0 19.04999 0.573347 36.44124
01-02-2017 916.54999 -12.75 0 12.75 0.210775 17.40824
02-02-2017 935.34998 18.79999 18.79999 0 0.508034 33.68849
03-02-2017 934.95001 -0.39997 0 0.39997 0.664511 39.92228
06-02-2017 934.45001 -0.5 0 0.5 0.655502 39.59537
07-02-2017 944.75 10.29999 10.29999 0 0.893136 47.17759
08-02-2017 936.45001 -8.29999 0 8.29999 0.664389 39.91788
09-02-2017 948.09998 11.64997 11.64997 0 0.987522 49.68609
10-02-2017 968.04999 19.95001 19.95001 0 1.290553 56.34242
13-02-2017 983.5 15.45001 15.45001 0 1.776544 63.984
14-02-2017 987.29999 3.79999 3.79999 0 2.235367 69.0916
15-02-2017 982.34998 -4.95001 0 4.95001 1.994559 66.6061
16-02-2017 1011.90002 29.55004 29.55004 0 2.517956 71.5744
17-02-2017 999.70001 -12.2 0 12.20001 1.883062 65.31466
20-02-2017 1011.70001 12 12 0 3.107418 75.65381
21-02-2017 1012.95001 1.25 1.25 0 4.658448 82.32731
22-02-2017 991.84998 -21.1 0 21.10003 2.190727 68.65918
23-02-2017 1009.04999 17.20001 17.20001 0 2.574919 72.02733
24-02-2017 1009.04999 0 0 0 2.602576 72.24209
27-02-2017 1012.75 3.70001 3.70001 0 2.460794 71.10489
28-02-2017 1012.29999 -0.45001 0 0.45001 2.959945 74.74712
01-03-2017 1025 12.70001 12.70001 0 2.987078 74.91897
02-03-2017 1020.65002 -4.34998 0 4.34998 2.221835 68.96178
03-03-2017 1031.15002 10.5 10.5 0 2.106852 67.81308
06-03-2017 1033.84998 2.69996 2.69996 0 2.0813 67.54616
07-03-2017 1019.70001 -14.15 0 14.14997 1.714833 63.16532
08-03-2017 1007.25 -12.45 0 12.45001 0.92813 48.13626
09-03-2017 1011.59998 4.34998 4.34998 0 1.226666 55.08981
10-03-2017 1020.09998 8.5 8.5 0 1.159999 53.70369
13-03-2017 1020.09998 0 0 0 1.13619 53.18768
14-03-2017 1032.5 12.40002 12.40002 0 2.294588 69.64719
15-03-2017 1012.09998 -20.4 0 20.40002 1.05888 51.42991
16-03-2017 1028.5 16.40002 16.40002 0 1.375483 57.9033
17-03-2017 1040 11.5 11.5 0 1.526062 60.41269
20-03-2017 1020.59998 -19.4 0 19.40002 1.117314 52.77036
21-03-2017 1032 11.40002 11.40002 0 1.09894 52.3569
22-03-2017 1027.80005 -4.19995 0 4.19995 1.101275 52.40985
23-03-2017 1040.59998 12.79993 12.79993 0 1.133852 53.1364
24-03-2017 1031.80005 -8.79993 0 8.79993 0.974182 49.34611
27-03-2017 1028.80005 -3 0 3 1.133334 53.12502
28-03-2017 1035.09998 6.29993 6.29993 0 1.499104 59.98566
29-03-2017 1031.34998 -3.75 0 3.75 1.331655 57.112
30-03-2017 1024.5 -6.84998 0 6.84998 1.066265 51.60351
31-03-2017 1020.79999 -3.70001 0 3.70001 1.009986 50.24841
44 KLE’s Institute of Management Studies and Research, Hubli
Interpretation
In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI
crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to
buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the
line crosses below 30 it shows buy signal. In months of December 2016 and March
2017the RSI crosses above 70 so it is the time to sell. And in month of August,
November and February 2017 was right time to buy as RSI crossed below 30.
Wipro ( Relative Strength Index):
45 KLE’s Institute of Management Studies and Research, Hubli
Date
Wipro
closing Change Gain Loss RS Value RSI
01-04-2016 562.15002
04-04-2016 566.25 4.09998 4.09998 0
05-04-2016 559 -7.25 0 7.25
06-04-2016 558.20001 -0.79999 0 0.79999
07-04-2016 551.79999 -6.40002 0 6.40002
08-04-2016 549.54999 -2.25 0 2.25
11-04-2016 565.75 16.20001 16.20001 0
12-04-2016 569.54999 3.79999 3.79999 0
13-04-2016 584.90002 15.35003 15.35003 0
14-04-2016 584.90002 0 0 0
15-04-2016 584.90002 0 0 0
18-04-2016 588.59998 3.69996 3.69996 0
19-04-2016 588.59998 0 0 0
20-04-2016 601.25 12.65002 12.65002 0
21-04-2016 558.84998 -42.4 0 42.40002 0.944162 48.56395
22-04-2016 557.95001 -0.89997 0 0.89997 0.861667 46.2847
25-04-2016 552.45001 -5.5 0 5.5 0.887554 47.02138
26-04-2016 554.45001 2 2 0 0.934726 48.31309
27-04-2016 560 5.54999 5.54999 0 1.160627 53.71714
28-04-2016 553.09998 -6.90002 0 6.90002 1.063734 51.54415
29-04-2016 554.34998 1.25 1.25 0 0.795332 44.29999
02-05-2016 548.5 -5.84998 0 5.84998 0.658002 39.68643
03-05-2016 543.84998 -4.65002 0 4.65002 0.379909 27.53145
04-05-2016 540 -3.84998 0 3.84998 0.359029 26.41805
05-05-2016 543.09998 3.09998 3.09998 0 0.403283 28.73852
06-05-2016 533.09998 -10 0 10 0.306683 23.47036
09-05-2016 539 5.90002 5.90002 0 0.380387 27.55657
10-05-2016 538.65002 -0.34998 0 0.34998 0.221393 18.12627
11-05-2016 537.79999 -0.85003 0 0.85003 0.458172 31.42101
12-05-2016 542.29999 4.5 4.5 0 0.587615 37.01243
13-05-2016 539.65002 -2.64997 0 2.64997 0.635328 38.85018
16-05-2016 540.79999 1.14997 1.14997 0 0.61111 37.931
17-05-2016 540.15002 -0.64997 0 0.64997 0.444755 30.78411
18-05-2016 539.54999 -0.60003 0 0.60003 0.539898 35.06063
19-05-2016 542.95001 3.40002 3.40002 0 0.612904 38.00002
20-05-2016 543.40002 0.45001 0 -0.45001 0.779698 43.8107
23-05-2016 539.84998 -3.55004 0 3.55004 0.818594 45.01247
24-05-2016 537.65002 -2.19996 0 2.19996 0.884805 46.94411
25-05-2016 546.09998 8.44996 8.44996 0 1.147059 53.42466
26-05-2016 544.95001 -1.14997 0 1.14997 2.025982 66.95288
27-05-2016 545.40002 0.45001 0 -0.45001 1.576582 61.18889
30-05-2016 550.15002 4.75 4.75 0 2.069772 67.4243
46 KLE’s Institute of Management Studies and Research, Hubli
31-05-2016 545.45001 -4.70001 0 4.70001 1.523976 60.37998
01-06-2016 554.5 9.04999 9.04999 0 1.835621 64.73436
02-06-2016 540.40002 -14.1 0 14.09998 1.028791 50.70956
03-06-2016 540.79999 0.39997 0 -0.39997 1 50
06-06-2016 535.09998 -5.70001 0 5.70001 0.835504 45.51904
07-06-2016 539.84998 4.75 4.75 0 1.009966 50.24793
08-06-2016 544.59998 4.75 4.75 0 1.054816 51.33385
09-06-2016 544.79999 0.20001 0 -0.20001 1.046128 51.12719
10-06-2016 545.34998 0.54999 0 -0.54999 1.209524 54.74139
13-06-2016 541.20001 -4.14997 0 4.14997 1.125886 52.9608
14-06-2016 543.09998 1.89997 1.89997 0 0.893617 47.19101
15-06-2016 547.04999 3.95001 3.95001 0 1.077633 51.86831
16-06-2016 549.90002 2.85003 2.85003 0 1.163636 53.78151
17-06-2016 552.04999 2.14997 2.14997 0 1.06909 51.66957
20-06-2016 557.04999 5 5 0 1.508771 60.13985
21-06-2016 561 3.95001 3.95001 0 1.285088 56.23801
22-06-2016 563.15002 2.15002 2.15002 0 3.61494 78.33124
23-06-2016 563.70001 0.54999 0 -0.54999 3.678368 78.62503
24-06-2016 555.15002 -8.54999 0 8.54999 2.75878 73.39562
27-06-2016 548 -7.15002 0 7.15002 1.439354 59.00555
28-06-2016 542.40002 -5.59998 0 5.59998 0.908904 47.61393
29-06-2016 554.54999 12.14997 12.14997 0 1.400411 58.34047
30-06-2016 557.95001 3.40002 3.40002 0 1.506026 60.09618
01-07-2016 558.90002 0.95001 0 -0.95001 1.89394 65.44504
04-07-2016 561.70001 2.79999 2.79999 0 1.939396 65.9794
05-07-2016 564.95001 3.25 3.25 0 1.904042 65.56523
06-07-2016 564.95001 0 0 0 1.760101 63.76944
07-07-2016 559.59998 -5.35003 0 5.35003 1.300198 56.52548
08-07-2016 561.65002 2.05004 2.05004 0 1.182904 54.18946
11-07-2016 568.84998 7.19996 7.19996 0 1.312126 56.74977
12-07-2016 570.79999 1.95001 1.95001 0 1.304174 56.60049
13-07-2016 573.95001 3.15002 3.15002 0 1.398833 58.31305
14-07-2016 570.59998 -3.35003 0 3.35003 1.753655 63.68463
15-07-2016 554.5 -16.1 0 16.09998 1.220713 54.96942
18-07-2016 551.95001 -2.54999 0 2.54999 1.361742 57.65837
19-07-2016 549.25 -2.70001 0 2.70001 0.81787 44.99056
20-07-2016 538.84998 -10.4 0 10.40002 0.516456 34.05675
21-07-2016 542 3.15002 3.15002 0 0.5822 36.79688
22-07-2016 537.75 -4.25 0 4.25 0.464206 31.70361
25-07-2016 542.84998 5.09998 5.09998 0 0.505593 33.58098
26-07-2016 546.09998 3.25 3.25 0 0.5783 36.64068
27-07-2016 549.15002 3.05004 3.05004 0 0.734436 42.34436
28-07-2016 553.79999 4.64997 4.64997 0 0.800508 44.46011
29-07-2016 545.04999 -8.75 0 8.75 0.505198 33.56356
47 KLE’s Institute of Management Studies and Research, Hubli
01-08-2016 557.70001 12.65002 12.65002 0 0.727651 42.11795
02-08-2016 549.59998 -8.10003 0 8.10003 0.566726 36.17263
03-08-2016 547.95001 -1.64997 0 1.64997 0.584404 36.88479
04-08-2016 548.20001 0.25 0 -0.25 0.834863 45.50001
05-08-2016 547.20001 -1 0 1 0.870219 46.53032
08-08-2016 549 1.79999 1.79999 0 0.992625 49.81495
09-08-2016 551.34998 2.34998 2.34998 0 1.531915 60.5042
10-08-2016 542.65002 -8.69996 0 8.69996 1.020187 50.49963
11-08-2016 543 0.34998 0 -0.34998 1.190218 54.34243
12-08-2016 543.75 0.75 0 -0.75 1.03352 50.82419
15-08-2016 543.75 0 0 0 0.912477 47.7118
16-08-2016 536.5 -7.25 0 7.25 0.629031 38.61383
17-08-2016 527.79999 -8.70001 0 8.70001 0.392523 28.18791
18-08-2016 525.09998 -2.70001 0 2.70001 0.457143 31.37254
19-08-2016 520.09998 -5 0 5 0.0994 9.041335
22-08-2016 515.5 -4.59998 0 4.59998 0.108496 9.787684
23-08-2016 519.59998 4.09998 4.09998 0 0.225409 18.39457
24-08-2016 519.65002 0.05004 0 -0.05004 0.224184 18.31292
25-08-2016 504 -15.65 0 15.65002 0.160349 13.81903
26-08-2016 490 -14 0 14 0.098548 8.970747
29-08-2016 478.79999 -11.2 0 11.20001 0.05349 5.077378
30-08-2016 489.45001 10.65002 10.65002 0 0.217071 17.83555
31-08-2016 491.64999 2.19998 2.19998 0 0.24817 19.88268
01-09-2016 483.95001 -7.69998 0 7.69998 0.220847 18.08964
02-09-2016 483.60001 -0.35 0 0.35 0.219844 18.02232
05-09-2016 483.60001 0 0 0 0.242663 19.52764
06-09-2016 482.89999 -0.70002 0 0.70002 0.27405 21.51014
07-09-2016 481.75 -1.14999 0 1.14999 0.281094 21.94174
08-09-2016 473.95001 -7.79999 0 7.79999 0.268621 21.17426
09-09-2016 480.64999 6.69998 6.69998 0 0.404273 28.78878
12-09-2016 480.39999 -0.25 0 0.25 0.332766 24.96806
13-09-2016 480.39999 0 0 0 0.332483 24.95212
14-09-2016 478.04999 -2.35 0 2.35 0.42967 30.05379
15-09-2016 478.45001 0.40002 0 -0.40002 0.628617 38.59822
16-09-2016 479.39999 0.94998 0 -0.94998 1.031662 50.77922
19-09-2016 479.95001 0.55002 0 -0.55002 0.483695 32.60068
20-09-2016 481.04999 1.09998 1.09998 0 0.423912 29.77093
21-09-2016 483.85001 2.80002 2.80002 0 0.990654 49.76526
22-09-2016 481.75 -2.10001 0 2.10001 0.851405 45.98696
23-09-2016 480.20001 -1.54999 0 1.54999 0.757143 43.08942
26-09-2016 479.29999 -0.90002 0 0.90002 0.746479 42.74192
27-09-2016 484.20001 4.90002 4.90002 0 1.18774 54.29074
28-09-2016 483.70001 -0.5 0 0.5 2.695652 72.94118
29-09-2016 472.20001 -11.5 0 11.5 0.510146 33.78124
48 KLE’s Institute of Management Studies and Research, Hubli
30-09-2016 478.95001 6.75 6.75 0 0.914707 47.77269
03-10-2016 478.95001 0 0 0 0.914707 47.77269
04-10-2016 481.79999 2.84998 2.84998 0 1.255973 55.67322
05-10-2016 479.54999 -2.25 0 2.25 1.063583 51.54059
06-10-2016 478 -1.54999 0 1.54999 0.929293 48.16755
07-10-2016 476.95001 -1.04999 0 1.04999 0.859813 46.23116
10-10-2016 477 0.04999 0 -0.04999 0.810305 44.76069
11-10-2016 477 0 0 0 0.679157 40.44629
12-10-2016 477 0 0 0 0.753247 42.96296
13-10-2016 478.25 1.25 1.25 0 0.88983 47.08519
14-10-2016 475 -3.25 0 3.25 0.785537 43.99443
17-10-2016 472.14999 -2.85001 0 2.85001 0.473798 32.14811
18-10-2016 482.75 10.60001 10.60001 0 0.957589 48.91675
19-10-2016 495 12.25 12.25 0 3.091742 75.56053
20-10-2016 495.39999 0.39999 0 -0.39999 2.566663 71.96259
21-10-2016 499.20001 3.80002 3.80002 0 2.92857 74.54544
24-10-2016 483.95001 -15.25 0 15.25 1.083496 52.00375
25-10-2016 481.39999 -2.55002 0 2.55002 1.071017 51.71455
26-10-2016 471.54999 -9.85 0 9.85 0.812227 44.81927
27-10-2016 461.70001 -9.84998 0 9.84998 0.646582 39.26813
28-10-2016 462.10001 0.4 0 -0.4 0.65187 39.46253
31-10-2016 462.10001 0 0 0 0.65187 39.46253
01-11-2016 460.75 -1.35001 0 1.35001 0.631937 38.72312
02-11-2016 457.89999 -2.85001 0 2.85001 0.567021 36.18466
03-11-2016 447.60001 -10.3 0 10.29998 0.493062 33.02356
04-11-2016 452.5 4.89999 4.89999 0 0.616211 38.1269
07-11-2016 450 -2.5 0 2.5 0.39013 28.06431
08-11-2016 451.75 1.75 1.75 0 0.1946 16.28996
09-11-2016 446.89999 -4.85001 0 4.85001 0.177269 15.05765
10-11-2016 444.95001 -1.94998 0 1.94998 0.109195 9.844548
11-11-2016 442.35001 -2.6 0 2.6 0.137824 12.11292
14-11-2016 442.35001 0 0 0 0.145514 12.70295
15-11-2016 447.95001 5.6 5.6 0 0.341702 25.46778
16-11-2016 445.29999 -2.65002 0 2.65002 0.427574 29.95108
17-11-2016 438.39999 -6.9 0 6.9 0.340751 25.41492
18-11-2016 437.14999 -1.25 0 1.25 0.329301 24.77248
21-11-2016 441.79999 4.65 4.65 0 0.471408 32.0379
22-11-2016 450.39999 8.6 8.6 0 0.772727 43.58974
23-11-2016 448.89999 -1.5 0 1.5 1.053718 51.30783
24-11-2016 450.75 1.85001 1.85001 0 0.927686 48.12433
25-11-2016 464.75 14 14 0 1.679723 62.68271
28-11-2016 460.60001 -4.14999 0 4.14999 1.34236 57.30802
29-11-2016 465.14999 4.54998 4.54998 0 1.869048 65.14523
30-11-2016 465.25 0.10001 0 -0.10001 2.07124 67.43986
49 KLE’s Institute of Management Studies and Research, Hubli
01-12-2016 468.29999 3.04999 3.04999 0 2.587155 72.12275
02-12-2016 460.39999 -7.9 0 7.9 1.744329 63.56122
05-12-2016 456.64999 -3.75 0 3.75 1.310714 56.72333
06-12-2016 457.79999 1.15 1.15 0 1.493097 59.88925
07-12-2016 453.35001 -4.44998 0 4.44998 1.65284 62.30456
08-12-2016 458.60001 5.25 5.25 0 1.990765 66.56374
09-12-2016 458.10001 -0.5 0 0.5 1.735894 63.44887
12-12-2016 453.54999 -4.55002 0 4.55002 1.117978 52.78515
13-12-2016 463.75 10.20001 10.20001 0 1.589287 61.37932
14-12-2016 466.29999 2.54999 2.54999 0 1.617064 61.78924
15-12-2016 466.10001 -0.19998 0 0.19998 1.05315 51.29435
16-12-2016 463.5 -2.60001 0 2.60001 1.121593 52.86561
19-12-2016 463.54999 0.04999 0 -0.04999 0.932773 48.26087
20-12-2016 466.64999 3.1 3.1 0 1.058577 51.42275
21-12-2016 462.45001 -4.19998 0 4.19998 0.791816 44.19068
22-12-2016 461.70001 -0.75 0 0.75 1.062054 51.50465
23-12-2016 458.75 -2.95001 0 2.95001 1.104219 52.47643
26-12-2016 456.10001 -2.64999 0 2.64999 0.925439 48.0638
27-12-2016 465.20001 9.1 9.1 0 1.645777 62.20391
28-12-2016 469.35001 4.15 4.15 0 1.585831 61.32771
29-12-2016 472.35001 3 3 0 1.798319 64.26426
30-12-2016 474.45001 2.1 2.1 0 2.571432 72.00003
02-01-2017 471.54999 -2.90002 0 2.90002 1.481481 59.70148
03-01-2017 467 -4.54999 0 4.54999 1.033735 50.8294
04-01-2017 475.60001 8.60001 8.60001 0 1.462287 59.38735
05-01-2017 480.39999 4.79998 4.79998 0 1.941504 66.00378
06-01-2017 469.95001 -10.45 0 10.44998 1.224957 55.05531
09-01-2017 472 2.04999 2.04999 0 1.18805 54.2972
10-01-2017 476.5 4.5 4.5 0 1.579381 61.23101
11-01-2017 476.20001 -0.29999 0 0.29999 1.609244 61.67473
12-01-2017 483.20001 7 7 0 2.172664 68.48075
13-01-2017 484.64999 1.44998 1.44998 0 2.568682 71.97845
16-01-2017 484.75 0.10001 0 -0.10001 2.080112 67.53365
17-01-2017 482.39999 -2.35001 0 2.35001 1.638141 62.09453
18-01-2017 482.95001 0.55002 0 -0.55002 1.532664 60.51589
19-01-2017 479 -3.95001 0 3.95001 1.190776 54.35406
20-01-2017 477.89999 -1.10001 0 1.10001 1.287982 56.29337
23-01-2017 479.75 1.85001 1.85001 0 1.728573 63.3508
24-01-2017 481.5 1.75 1.75 0 1.337143 57.21271
25-01-2017 473.70001 -7.79999 0 7.79999 0.735178 42.36903
26-01-2017 473.70001 0 0 0 1.252526 55.60539
27-01-2017 465.54999 -8.15002 0 8.15002 0.719565 41.84575
30-01-2017 465.75 0.20001 0 -0.20001 0.528509 34.57675
31-01-2017 458 -7.75 0 7.75 0.398347 28.48698
50 KLE’s Institute of Management Studies and Research, Hubli
01-02-2017 456 -2 0 2 0.156589 13.53885
02-02-2017 455.64999 -0.35001 0 0.35001 0.11043 9.944774
03-02-2017 457.75 2.10001 2.10001 0 0.174312 14.84379
06-02-2017 461.10001 3.35001 3.35001 0 0.298189 22.9696
07-02-2017 458.54999 -2.55002 0 2.55002 0.270554 21.29415
08-02-2017 460.5 1.95001 1.95001 0 0.372882 27.16054
09-02-2017 466 5.5 5.5 0 0.580987 36.74836
10-02-2017 469.25 3.25 3.25 0 0.630282 38.66092
13-02-2017 474.45001 5.20001 5.20001 0 0.751761 42.91459
14-02-2017 476.70001 2.25 2.25 0 1.145631 53.39366
15-02-2017 474.70001 -2 0 2 1.044248 51.08225
16-02-2017 480.79999 6.09998 6.09998 0 2.055362 67.27065
17-02-2017 475.35001 -5.44998 0 5.44998 1.477612 59.63856
20-02-2017 475.64999 0.29998 0 -0.29998 2.464726 71.13769
21-02-2017 475.79999 0.15 0 -0.15 2.999993 74.99996
22-02-2017 474.5 -1.29999 0 1.29999 2.737327 73.24291
23-02-2017 486.10001 11.60001 11.60001 0 3.612902 78.32167
24-02-2017 486.10001 0 0 0 3.304145 76.76658
27-02-2017 489.75 3.64999 3.64999 0 4.759042 82.636
28-02-2017 488.79999 -0.95001 0 0.95001 4.059458 80.23504
01-03-2017 488.54999 -0.25 0 0.25 3.373683 77.13598
02-03-2017 490.20001 1.65002 1.65002 0 3.205264 76.22028
03-03-2017 493.85001 3.65 3.65 0 3.042105 75.26042
06-03-2017 491.89999 -1.95002 0 1.95002 2.327507 69.94747
07-03-2017 495.14999 3.25 3.25 0 3.164014 75.98471
08-03-2017 495.10001 -0.04998 0 0.04998 2.505265 71.47149
09-03-2017 484.5 -10.6 0 10.60001 1.624571 61.89854
10-03-2017 487.04999 2.54999 2.54999 0 1.762541 63.80145
13-03-2017 487.04999 0 0 0 1.745033 63.57056
14-03-2017 501.35001 14.30002 14.30002 0 2.94565 74.65563
15-03-2017 494.79999 -6.55002 0 6.55002 1.427517 58.80564
16-03-2017 500.54999 5.75 5.75 0 1.710071 63.1006
17-03-2017 504.25 3.70001 3.70001 0 1.712529 63.13404
20-03-2017 497.5 -6.75 0 6.75 1.332696 57.13115
21-03-2017 498.64999 1.14999 1.14999 0 1.389961 58.15831
22-03-2017 500.54999 1.9 1.9 0 1.399613 58.32661
23-03-2017 510 9.45001 9.45001 0 1.623551 61.88372
24-03-2017 513.25 3.25 3.25 0 1.891441 65.41516
27-03-2017 504 -9.25 0 9.25 1.266566 55.8804
28-03-2017 507.54999 3.54999 3.54999 0 1.375565 57.90475
29-03-2017 512.25 4.70001 4.70001 0 2.230598 69.04597
30-03-2017 515.95001 3.70001 3.70001 0 2.281596 69.52702
31-03-2017 515.70001 -0.25 0 0.25 2.256579 69.29293
51 KLE’s Institute of Management Studies and Research, Hubli
Interpretation
In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI
crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to
buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the
line crosses below 30 it shows buy signal. In months of June, October 2016 And
March 2016 the RSI crosses above 70 so it is the time to sell. And in the month of
May, September ,November 2016 and February 2017 was right time to buy as RSI
has crossed below 30.
MINDTREE ( Relative Strength Index):
52 KLE’s Institute of Management Studies and Research, Hubli
Date Mind tree closing Change Gain Loss RS Value RSI
01-04-2016 668.15
04-04-2016 676.05 7.9 7.9 0
05-04-2016 658.35 -17.7 0 17.7
06-04-2016 667.9 9.55 9.55 0
07-04-2016 671.65 3.75 3.75 0
08-04-2016 667.5 -4.15 0 4.15
11-04-2016 667.7 0.2 0 -0.2
12-04-2016 677 9.3 9.3 0
13-04-2016 691.6 14.6 14.6 0
14-04-2016 691.6 0 0 0
15-04-2016 691.6 0 0 0
18-04-2016 730.8 39.2 39.2 0
19-04-2016 730.8 0 0 0
20-04-2016 723.95 -6.85 0 6.85
21-04-2016 715.8 -8.15 0 8.15 2.300136 69.69822
22-04-2016 708.3 -7.5 0 7.5 1.730464 63.37619
25-04-2016 698.5 -9.8 0 9.8 2.107586 67.82068
26-04-2016 707.35 8.85 8.85 0 2.088276 67.61947
27-04-2016 699.7 -7.65 0 7.65 1.638952 62.10617
28-04-2016 686.2 -13.5 0 13.5 1.351174 57.46805
29-04-2016 678.8 -7.4 0 7.4 1.182416 54.17922
02-05-2016 681.85 3.05 3.05 0 1.079704 51.91624
03-05-2016 670.25 -11.6 0 11.6 0.705314 41.35977
04-05-2016 661.45 -8.8 0 8.8 0.628923 38.60975
05-05-2016 664 2.55 2.55 0 0.660308 39.7702
06-05-2016 659 -5 0 5 0.167536 14.34955
09-05-2016 657.15 -1.85 0 1.85 0.164018 14.09069
10-05-2016 645.85 -11.3 0 11.3 0.156132 13.50467
11-05-2016 652.35 6.5 6.5 0 0.248223 19.88609
12-05-2016 660.25 7.9 7.9 0 0.375163 27.28132
13-05-2016 652.9 -7.35 0 7.35 0.387508 27.92836
16-05-2016 645.3 -7.6 0 7.6 0.243754 19.59824
17-05-2016 645.5 0.2 0.2 0 0.271505 21.35307
18-05-2016 644 -1.5 0 1.5 0.323718 24.45521
19-05-2016 644 0 0 0 0.367273 26.8617
20-05-2016 630.45 -13.55 0 13.55 0.250182 20.01167
23-05-2016 640.85 10.4 10.4 0 0.483758 32.60355
24-05-2016 647.75 6.9 6.9 0 0.715472 41.70702
25-05-2016 648.75 1 1 0 0.683281 40.59223
26-05-2016 665.35 16.6 16.6 0 1.147161 53.42688
27-05-2016 667.6 2.25 2.25 0 1.253027 55.61526
30-05-2016 671.7 4.1 4.1 0 1.861667 65.05533
31-05-2016 660.9 -10.8 0 10.8 1.209559 54.7421
53 KLE’s Institute of Management Studies and Research, Hubli
01-06-2016 654.8 -6.1 0 6.1 0.883795 46.91568
02-06-2016 653.6 -1.2 0 1.2 1.017178 50.42579
03-06-2016 647.45 -6.15 0 6.15 1.054707 51.33127
06-06-2016 644.55 -2.9 0 2.9 0.977488 49.4308
07-06-2016 650.3 5.75 5.75 0 1.154791 53.59179
08-06-2016 650.7 0.4 0 -0.4 1.166253 53.83734
09-06-2016 639.2 -11.5 0 11.5 1.228758 55.13196
10-06-2016 639.35 0.15 0 -0.15 0.96063 48.99598
13-06-2016 635.15 -4.2 0 4.2 0.702128 41.25
14-06-2016 643.95 8.8 8.8 0 0.886525 46.99248
15-06-2016 640.05 -3.9 0 3.9 0.452381 31.14754
16-06-2016 630.05 -10 0 10 0.331851 24.9165
17-06-2016 630 -0.05 0 0.05 0.258667 20.55085
20-06-2016 639.8 9.8 9.8 0 0.535754 34.88539
21-06-2016 657.7 17.9 17.9 0 1.073698 51.77696
22-06-2016 653.6 -4.1 0 4.1 1 50
23-06-2016 659.95 6.35 6.35 0 1.34626 57.37898
24-06-2016 659.9 -0.05 0 0.05 1.461654 59.37691
27-06-2016 651.85 -8.05 0 8.05 1.03753 50.92097
28-06-2016 662.8 10.95 10.95 0 1.290168 56.33508
29-06-2016 663.4 0.6 0.6 -0.6 1.837838 64.7619
30-06-2016 664.85 1.45 1.45 0 1.877311 65.24533
01-07-2016 673.9 9.05 9.05 0 2.540117 71.75235
04-07-2016 672.15 -1.75 0 1.75 2.054945 67.26619
05-07-2016 678.3 6.15 6.15 0 2.660256 72.67951
06-07-2016 678.3 0 0 0 4.645522 82.28685
07-07-2016 659.35 -18.95 0 18.95 1.927245 65.83818
08-07-2016 654.4 -4.95 0 4.95 1.408054 58.47269
11-07-2016 665.55 11.15 11.15 0 1.226846 55.09343
12-07-2016 661.05 -4.5 0 4.5 1.213811 54.82903
13-07-2016 650.45 -10.6 0 10.6 0.815544 44.92009
14-07-2016 653.3 2.85 2.85 0 0.875519 46.68142
15-07-2016 637.25 -16.05 0 16.05 0.75089 42.88618
18-07-2016 614.2 -23.05 0 23.05 0.394322 28.28054
19-07-2016 561.55 -52.65 0 52.65 0.231321 18.78639
20-07-2016 570.4 8.85 8.85 0 0.28717 22.31017
21-07-2016 565.95 -4.45 0 4.45 0.211756 17.47514
22-07-2016 556.9 -9.05 0 9.05 0.20104 16.73882
25-07-2016 551.75 -5.15 0 5.15 0.152945 13.2656
26-07-2016 565 13.25 13.25 0 0.241633 19.46092
27-07-2016 565.1 0.1 0.1 -0.1 0.277714 21.73521
28-07-2016 582.3 17.2 17.2 0 0.425837 29.86577
29-07-2016 578.65 -3.65 0 3.65 0.327392 24.66433
01-08-2016 601.6 22.95 22.95 0 0.523485 34.361
54 KLE’s Institute of Management Studies and Research, Hubli
02-08-2016 612.95 11.35 11.35 0 0.671786 40.18373
03-08-2016 600.1 -12.85 0 12.85 0.58123 36.7581
04-08-2016 604.85 4.75 4.75 0 0.708352 41.46406
05-08-2016 613 8.15 8.15 0 0.987457 49.68445
08-08-2016 617.8 4.8 4.8 0 2.607703 72.28153
09-08-2016 596.55 -21.25 0 21.25 1.466252 59.45265
10-08-2016 572.3 -24.25 0 24.25 1.084757 52.03278
11-08-2016 580.7 8.4 8.4 0 1.35645 57.56329
12-08-2016 579.8 -0.9 0 0.9 1.448248 59.15447
15-08-2016 579.8 0 0 0 1.237261 55.30249
16-08-2016 569.15 -10.65 0 10.65 1.055065 51.33973
17-08-2016 566.35 -2.8 0 2.8 0.791094 44.16819
18-08-2016 564.75 -1.6 0 1.6 0.812921 44.84039
19-08-2016 565.7 0.95 0.95 -0.95 0.523517 34.36242
22-08-2016 551.25 -14.45 0 14.45 0.308087 23.55246
23-08-2016 566.2 14.95 14.95 0 0.560374 35.91278
24-08-2016 568.6 2.4 2.4 0 0.529019 34.5986
25-08-2016 567.8 -0.8 0 0.8 0.415842 29.37063
26-08-2016 569.25 1.45 1.45 0 0.371617 27.09336
29-08-2016 564.95 -4.3 0 4.3 0.478741 32.37493
30-08-2016 570.15 5.2 5.2 0 0.965268 49.11635
31-08-2016 562.55 -7.6 0 7.6 0.591934 37.18331
01-09-2016 553.75 -8.8 0 8.8 0.498501 33.26667
02-09-2016 548.85 -4.9 0 4.9 0.454049 31.22653
05-09-2016 548.85 0 0 0 0.563205 36.02888
06-09-2016 525 -23.85 0 23.85 0.38179 27.63012
07-09-2016 518.9 -6.1 0 6.1 0.357194 26.31857
08-09-2016 515.3 -3.6 0 3.6 0.322581 24.39024
09-09-2016 522.8 7.5 7.5 0 0.525438 34.44505
12-09-2016 516.5 -6.3 0 6.3 0.249811 19.98792
13-09-2016 516.5 0 0 0 0.213585 17.5995
14-09-2016 513.5 -3 0 3 0.20672 17.13075
15-09-2016 514 0.5 0.5 -0.5 0.19426 16.26617
16-09-2016 512.2 -1.8 0 1.8 0.201681 16.78322
19-09-2016 505.25 -6.95 0 6.95 0.110497 9.950249
20-09-2016 502.1 -3.15 0 3.15 0.117734 10.53325
21-09-2016 510.25 8.15 8.15 0 0.273035 21.44754
22-09-2016 509.75 -0.5 0 0.5 0.294977 22.77856
23-09-2016 505.2 -4.55 0 4.55 0.272344 21.4049
26-09-2016 497.75 -7.45 0 7.45 0.376457 27.3497
27-09-2016 493 -4.75 0 4.75 0.388688 27.9896
28-09-2016 492.95 -0.05 0 0.05 0.425 29.82456
29-09-2016 481.6 -11.35 0 11.35 0.175279 14.91379
30-09-2016 482.15 0.55 0 -0.55 0.203529 16.91105
55 KLE’s Institute of Management Studies and Research, Hubli
03-10-2016 488.55 6.4 6.4 0 0.354118 26.15117
04-10-2016 495.95 7.4 7.4 0 0.568354 36.2389
05-10-2016 498.4 2.45 2.45 0 0.61 37.8882
06-10-2016 491.2 -7.2 0 7.2 0.537445 34.95702
07-10-2016 491.85 0.65 0 -0.65 0.645503 39.2283
10-10-2016 500.9 9.05 9.05 0 0.965368 49.11894
11-10-2016 500.9 0 0 0 0.730159 42.20183
12-10-2016 500.9 0 0 0 0.740849 42.55677
13-10-2016 489.7 -11.2 0 11.2 0.620098 38.27534
14-10-2016 501.05 11.35 11.35 0 1.098951 52.35714
17-10-2016 490.6 -10.45 0 10.45 0.93854 48.4148
18-10-2016 476.85 -13.75 0 13.75 0.694787 40.99553
19-10-2016 476.95 0.1 0 -0.1 0.887409 47.01732
20-10-2016 479.05 2.1 2.1 0 0.925926 48.07692
21-10-2016 479 -0.05 0 0.05 0.772076 43.56902
24-10-2016 456 -23 0 23 0.384438 27.7685
25-10-2016 454.9 -1.1 0 1.1 0.340909 25.42373
26-10-2016 450.2 -4.7 0 4.7 0.354331 26.16279
27-10-2016 441.5 -8.7 0 8.7 0.308854 23.59727
28-10-2016 435.95 -5.55 0 5.55 0.171556 14.64344
31-10-2016 435.95 0 0 0 0.171556 14.64344
01-11-2016 439.55 3.6 3.6 0 0.217474 17.86276
02-11-2016 433.55 -6 0 6 0.232923 18.89197
03-11-2016 428.35 -5.2 0 5.2 0.072704 6.777646
04-11-2016 425.15 -3.2 0 3.2 0.080112 7.417046
07-11-2016 429.25 4.1 4.1 0 0.170732 14.58333
08-11-2016 442.65 13.4 13.4 0 0.403478 28.74845
09-11-2016 436.15 -6.5 0 6.5 0.329688 24.79436
10-11-2016 437.4 1.25 1.25 0 0.349492 25.89803
11-11-2016 423.55 -13.85 0 13.85 0.407847 28.96954
14-11-2016 423.55 0 0 0 0.416201 29.38856
15-11-2016 430.55 7 7 0 0.59898 37.46011
16-11-2016 437.9 7.35 7.35 0 0.91067 47.66234
17-11-2016 441.75 3.85 3.85 0 1.166906 53.85126
18-11-2016 442.25 0.5 0 -0.5 1.183942 54.21123
21-11-2016 441.8 -0.45 0 0.45 1.064841 51.57013
22-11-2016 453.15 11.35 11.35 0 1.682927 62.72727
23-11-2016 453.5 0.35 0.35 -0.35 2.101512 67.75766
24-11-2016 462.85 9.35 9.35 0 2.907268 74.40667
25-11-2016 478.25 15.4 15.4 0 3.473684 77.64706
28-11-2016 477.8 -0.45 0 0.45 2.740196 73.26343
29-11-2016 473.65 -4.15 0 4.15 3.096953 75.59162
30-11-2016 477.35 3.7 3.7 0 3.232687 76.37435
01-12-2016 466.6 -10.75 0 10.75 3.90301 79.60437
56 KLE’s Institute of Management Studies and Research, Hubli
02-12-2016 460.45 -6.15 0 6.15 2.765403 73.44242
05-12-2016 448.35 -12.1 0 12.1 1.546687 60.73329
06-12-2016 459.8 11.45 11.45 0 1.670181 62.54935
07-12-2016 457.75 -2.05 0 2.05 1.46383 59.41278
08-12-2016 462.2 4.45 4.45 0 1.567832 61.05664
09-12-2016 470.65 8.45 8.45 0 1.827195 64.62926
12-12-2016 468.25 -2.4 0 2.4 1.409814 58.50303
13-12-2016 492.5 24.25 24.25 0 2.024967 66.94179
14-12-2016 502.9 10.4 10.4 0 2.052562 67.24064
15-12-2016 495.3 -7.6 0 7.6 1.373494 57.86802
16-12-2016 501.35 6.05 6.05 0 1.521018 60.33348
19-12-2016 500.1 -1.25 0 1.25 1.625296 61.90905
20-12-2016 494.1 -6 0 6 1.346791 57.38862
21-12-2016 493.95 -0.15 0 0.15 1.725464 63.309
22-12-2016 495.4 1.45 1.45 0 2.107765 67.82254
23-12-2016 496.9 1.5 1.5 0 3.496144 77.75872
26-12-2016 487.9 -9 0 9 1.987698 66.52941
27-12-2016 486.2 -1.7 0 1.7 2.012456 66.80449
28-12-2016 510.15 23.95 23.95 0 2.706406 73.01968
29-12-2016 523.85 13.7 13.7 0 2.893238 74.31444
30-12-2016 521.65 -2.2 0 2.2 2.913978 74.45055
02-01-2017 516.7 -4.95 0 4.95 1.736682 63.4594
03-01-2017 507.9 -8.8 0 8.8 1.120048 52.83126
04-01-2017 526.4 18.5 18.5 0 1.913363 65.6754
05-01-2017 523.7 -2.7 0 2.7 1.608163 61.65884
06-01-2017 500.2 -23.5 0 23.5 1.001695 50.04234
09-01-2017 495.5 -4.7 0 4.7 1.024263 50.59932
10-01-2017 487.15 -8.35 0 8.35 0.896813 47.28
11-01-2017 487.3 0.15 0.15 -0.15 0.879087 46.78268
12-01-2017 491.3 4 4 0 0.91711 47.83816
13-01-2017 490.85 -0.45 0 0.45 1.054196 51.31915
16-01-2017 484.95 -5.9 0 5.9 0.982085 49.54807
17-01-2017 484.85 -0.1 0 0.1 0.591057 37.1487
18-01-2017 495.5 10.65 10.65 0 0.541463 35.12658
19-01-2017 485.1 -10.4 0 10.4 0.477762 32.3301
20-01-2017 475.25 -9.85 0 9.85 0.446381 30.86191
23-01-2017 471.3 -3.95 0 3.95 0.477419 32.31441
24-01-2017 470.25 -1.05 0 1.05 0.20904 17.28972
25-01-2017 461.65 -8.6 0 8.6 0.19296 16.17486
26-01-2017 461.65 0 0 0 0.278195 21.76471
27-01-2017 472.5 10.85 10.85 0 0.528866 34.59204
30-01-2017 465.55 -6.95 0 6.95 0.544586 35.25773
31-01-2017 450.5 -15.05 0 15.05 0.40931 29.04328
01-02-2017 459.85 9.35 9.35 0 0.495185 33.11863
57 KLE’s Institute of Management Studies and Research, Hubli
02-02-2017 461 1.15 1.15 0 0.517381 34.09696
03-02-2017 459.35 -1.65 0 1.65 0.555556 35.71429
06-02-2017 464.85 5.5 5.5 0 0.652174 39.47368
07-02-2017 452.8 -12.05 0 12.05 0.386053 27.8527
08-02-2017 450.1 -2.7 0 2.7 0.434115 30.27057
09-02-2017 457.6 7.5 7.5 0 0.660577 39.77997
10-02-2017 466.65 9.05 9.05 0 0.903226 47.45763
13-02-2017 468.15 1.5 1.5 0 0.955319 48.85745
14-02-2017 455.1 -13.05 0 13.05 0.872692 46.60093
15-02-2017 457.65 2.55 2.55 0 0.922255 47.97776
16-02-2017 468 10.35 10.35 0 0.912536 47.71341
17-02-2017 475.15 7.15 7.15 0 1.21573 54.86815
20-02-2017 474.4 -0.75 0 0.75 1.791391 64.17556
21-02-2017 474.4 0 0 0 1.481788 59.70647
22-02-2017 468.2 -6.2 0 6.2 1.197802 54.5
23-02-2017 469.9 1.7 1.7 0 1.303597 56.58963
24-02-2017 469.9 0 0 0 1.145324 53.38699
27-02-2017 471.15 1.25 1.25 0 1.80837 64.39216
28-02-2017 474.3 3.15 3.15 0 2.21 68.84735
01-03-2017 471.95 -2.35 0 2.35 1.642058 62.15072
02-03-2017 460.3 -11.65 0 11.65 0.813235 44.84996
03-03-2017 464.6 4.3 4.3 0 0.895588 47.24593
06-03-2017 460.25 -4.35 0 4.35 1.203557 54.61883
07-03-2017 478.7 18.45 18.45 0 1.832016 64.68946
08-03-2017 469.25 -9.45 0 9.45 1.035971 50.88339
09-03-2017 472.65 3.4 3.4 0 0.928058 48.13433
10-03-2017 474.8 2.15 2.15 0 1.011765 50.2924
13-03-2017 474.8 0 0 0 1.011765 50.2924
14-03-2017 470.85 -3.95 0 3.95 1.083465 52.00302
15-03-2017 466.55 -4.3 0 4.3 0.907074 47.56364
16-03-2017 469.75 3.2 3.2 0 0.995839 49.89576
17-03-2017 473.45 3.7 3.7 0 1.0638 51.5457
20-03-2017 474.1 0.65 0.6 -0.65 1.011299 50.2809
21-03-2017 474.85 0.75 0.75 -0.75 1.131579 53.08642
22-03-2017 472.3 -2.55 0 2.55 1.575431 61.17155
23-03-2017 472.2 -0.1 0 0.1 1.38412 58.05581
24-03-2017 469.55 -2.65 0 2.65 1.493056 59.88858
27-03-2017 461.3 -8.25 0 8.25 0.462312 31.61512
28-03-2017 459.95 -1.35 0 1.35 0.634483 38.81857
29-03-2017 456.1 -3.85 0 3.85 0.40625 28.88889
30-03-2017 453.2 -2.9 0 2.9 0.289474 22.44898
31-03-2017 452.95 -0.25 0 0.25 0.286957 22.2973
58 KLE’s Institute of Management Studies and Research, Hubli
Interpretation
In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI
crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to
buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the
line crosses below 30 it shows buy signal. In the month of July ,August ,December
2016 the RSI crosses above 70 so it is the time to sell. And in May, September,
November 2016 was right time to buy.
TCS ( Relative Strength Index):
Date TCS closing Change Gain Loss RS Value RSI
01-04-2016 2455.4
59 KLE’s Institute of Management Studies and Research, Hubli
04-04-2016 2470.7 15.3 15.3 0
05-04-2016 2462.65 -8.05 0 8.05
06-04-2016 2478.9 16.25 16.25 0
07-04-2016 2470.95 -7.95 0 7.95
08-04-2016 2428.7 -42.25 0 42.25
11-04-2016 2506.65 77.95 77.95 0
12-04-2016 2512.5 5.85 5.85 0
13-04-2016 2523.15 10.65 10.65 0
14-04-2016 2523.15 0 0 0
15-04-2016 2523.15 0 0 0
18-04-2016 2522.4 -0.75 0 0.75
19-04-2016 2522.4 0 0 0
20-04-2016 2451.9 -70.5 0 70.5
21-04-2016 2423.2 -28.7 0 28.7 0.79646 44.33498
22-04-2016 2417.2 -6 0 6 0.674178 40.26919
25-04-2016 2448.3 31.1 31.1 0 0.908101 47.59188
26-04-2016 2488 39.7 39.7 0 1.058277 51.41568
27-04-2016 2505.55 17.55 17.55 0 1.233468 55.22659
28-04-2016 2526.95 21.4 21.4 0 1.927324 65.83911
29-04-2016 2530.05 3.1 3.1 0 1.220859 54.97238
02-05-2016 2525.15 -4.9 0 4.9 1.114118 52.69895
03-05-2016 2480.25 -44.9 0 44.9 0.724559 42.01415
04-05-2016 2478.25 -2 0 2 0.715372 41.70362
05-05-2016 2474 -4.25 0 4.25 0.696605 41.05876
06-05-2016 2472.15 -1.85 0 1.85 0.691907 40.89509
09-05-2016 2515.35 43.2 43.2 0 0.956775 48.8955
10-05-2016 2523.6 8.25 8.25 0 1.774298 63.95485
11-05-2016 2517.75 -5.85 0 5.85 2.355556 70.19868
12-05-2016 2567.05 49.3 49.3 0 3.350588 77.0146
13-05-2016 2523.4 -43.65 0 43.65 1.699255 62.95274
16-05-2016 2553.8 30.4 30.4 0 1.612663 61.72488
17-05-2016 2570.2 16.4 16.4 0 1.601955 61.56736
18-05-2016 2550.45 -19.75 0 19.75 1.184821 54.22966
19-05-2016 2555.55 5.1 5.1 0 1.200551 54.55683
20-05-2016 2532.05 -23.5 0 23.5 1.047341 51.15617
23-05-2016 2491.7 -40.35 0 40.35 1.081091 51.94827
24-05-2016 2467.5 -24.2 0 24.2 0.934211 48.29932
25-05-2016 2526.7 59.2 59.2 0 1.331134 57.10243
26-05-2016 2552.8 26.1 26.1 0 1.512715 60.2024
27-05-2016 2572.05 19.25 19.25 0 1.360458 57.63534
30-05-2016 2635.35 63.3 63.3 0 1.710426 63.10543
31-05-2016 2575.1 -60.25 0 60.25 1.270902 55.96464
01-06-2016 2631.85 56.75 56.75 0 1.306094 56.63662
02-06-2016 2646.9 15.05 15.05 0 1.7349 63.4356
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry
project work on technical analysis of Indian IT industry

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project work on technical analysis of Indian IT industry

  • 1. 1 KLE’s Institute of Management Studies and Research, Hubli Chapter.1 1.1) Executive Summary The main aim of the investor is to minimize the risk involved in investment & maximize the return. Today there are number of options available to investor like Post Office investment, Bank Deposit, Insurance, Mutual Fund, Stock Market etc... Technical analysis is a financial markets technique that claims the ability to forecast the future direction of security prices through the study of past market data, primarily price and volume. This project is about a brief introduction to Technical Analysis, different price patterns and trends in financial markets and attempt to exploit that patterns etc… The contents in this project are made simple so as to make a layman understand the terms used in the Technical Analysis. The core area of this project focuses what a technical analysts may employ models and trading rules based for example, on price transformations, Relative Strength Index, moving averages, Rate of Change, through recognition of chart patterns. This project contains some elementary statistics which are used in calculation which help in drawing inferences. This project has done in SHAREKHAN LIMITED,HUBLI which is the retail brokering arm of SSKI; SSKI is SS Kantilal Ishwarlal Securities Pvt. Ltd. involved in rendering different financial services like equity brokerage, commodity research & brokerage, portfolio management services.
  • 2. 2 KLE’s Institute of Management Studies and Research, Hubli 1.2) Title: A Study on Technical Analysis of IT Sector for Investment Decision”. 1.3) Objectives: To predict the future price of IT sector. To study the strategies to be adopted by the investor based on the Technical Analysis. To predict investor positions in signaling (Buy, Hold & Sell) based on historical price trends. Methodology: The data collected for the research purpose are secondary data. Closing prices of Scrip’s were collected through National Stock Exchange website. Sources of Data: The type of the data collection method is secondary data:  Web sites  Text Books  Business magazines. TOOLS USED:  Relative Strength Index.  Moving Average.
  • 3. 3 KLE’s Institute of Management Studies and Research, Hubli 1.1) FINDINGS:  In the month of December 2016 and March 2017 there was a strong sell signal of Infosys shares. And August, November 2016 and February 2017 was right time to buy the Shares.  In the month of May, August 2016 and January 2017 there was a strong sell signal of TCS shares. And July 2016 and November 2016 was right time to buy the shares.  In months of June and October 2016 there was a strong sell signal of WIPRO shares. And in the month of September and November 2016 and February 2017 was right time to buy the shares.  In the month of July, August, December 2016 there was a strong sell signal of MINDTREE shares. And in the month of May, November 2016 and February 2017 was right time to buy the shares.  Technical analysis will indicates the buying point and selling point. 1.2) Limitations: This project study is limited to only one sector i.e. IT sector. The project does not extend its scope to any other sector of companies. The analysis is made based on the available data (April 2016 – March 2017) considering it is correct and accurate. Only two Technical tools (Moving Average & RSI) to predict the movement of Stocks selected companies. This project can’t predict the prices of stocks for long term. Only Technical Analysis is used to predict the stock prices of the companies.
  • 4. 4 KLE’s Institute of Management Studies and Research, Hubli 1.3) Conclusion Technical analysis can be used as a reliable tool for investing into stocks. Many investors (cash market retail investors) are not having right mental setup to trade in to stocks; there lies the importance of technical analysis. Mainly it is more useful in the identification of buying points and selling points. Technical analysis is more reliable and useful for short term and medium term investors. The RSI chart shows that end of the many months the RSI of each script were moving up and it is the right time to sell the Scrip’s. Technical analysis for long term investment is not so much tenable. For Short term investment technical analysis is sufficient to predict the next possible price targets without using fundamental analysis. Technical analysis will help the investors to drive their investment in right and profitable path.
  • 5. 5 KLE’s Institute of Management Studies and Research, Hubli Chapter-2 Industry profile
  • 6. 6 KLE’s Institute of Management Studies and Research, Hubli Industry Profile The stock exchange initially Started in the nineteenth century in 1875it was completely started in Bombay and later in Ahmadabad in 1894. To protect the broker interest and to make active participation of the broker the voluntary nonprofit association as generated. Securities trading were became the central subject under the constitution in 1950. BSE were set up in 1927in Bombay. BSE started first screen based online trading which helped to minimize the risk and more liquidity in the market. Stock market Stock market it is place where the buying and selling of the stocks takes place based on the company’s stock. The stock which trades on the market should be listed in the market and unlisted trade takes place in terms of commodities. Stock Exchange Stock exchange are an organized and well functioned marketplace, here the high net worth individuals, all financial institutes, mutual fund and corporate takes place to make the trading. The members may act either as a agents for their customer, or as principals for their own accounts. Stock exchange gives the facilities related to issue of share and redemption of securities and other financial instruments such as payment of the dividend once the companies announces and income through trade i.e. buying and selling of the share on profit loss. The trade on an exchange is only by stock broker do have seat on the exchange and members who have registered. SECURITIES AND EXCHANGE BOARD OF INDIA (SEBI) The Securities and Exchange Board of India (SEBI) is the regulator for the securities market in India. It was established in the year 1988 and given statutory powers on 12 April 1992 through the SEBI Act 1992. It was established by The Government of India on 12 April 1988 and given statutory powers in 1992 with SEBI Act 1992 being passed by the Indian Parliament.SEBI has its headquarters at the business district of BandraKurla Complex in Mumbai, and has Northern, Eastern, Southern and Western Regional
  • 7. 7 KLE’s Institute of Management Studies and Research, Hubli Offices in New Delhi, Kolkata, Chennai and Ahmadabad respectively. It has opened local offices at Jaipur and Bangalore and is planning to open offices at Guwahati, Bhubaneswar, Patna, Kochi and Chandigarh in Financial Year 2013 - 2014. Controller of Capital Issues was the regulatory authority before SEBI came into existence; it derived authority from the Capital Issues (Control) Act, 1947. Initially SEBI was a non-statutory body without any statutory power. However in 1995, the SEBI was given additional statutory power by the Government of India through an amendment to the Securities and Exchange Board of India Act, 1992. In April 1988 the SEBI was constituted as the regulator of capital markets in India under a resolution of the Government of India. The SEBI is managed by its members, which consists of following: 1.The chairman who is nominated by Union Government of India. 2.Two members, i.e., Officers from Union Finance Ministry. 3.One member from the Reserve Bank of India. 4.The remaining five members are nominated by Union Government of India, out of them at least three shall be whole-time members. BOMBAY STOCK EXCHANGE (BSE) The Bombay Stock Exchange (BSE) is an Indian stock exchange located at Dalal Street, Kala Ghoda, Mumbai, Maharashtra, India. Established in 1875 the BSE is considered to be one of Asia’s fastest stock exchanges, with a speed of 200 microseconds and one of India’s leading exchange groups and the oldest stock exchange in the South Asia region. Bombay Stock Exchange is the world's 10thlargest stock market by market capitalization at $1.7 trillion as of 23 January 2015. More than 5,000 companies are listed on BSE. The Bombay Stock Exchange is the oldest exchange in Asia. It traces its history to 1855, when four Gujarati and one Parsi stockbroker would gather under banyan trees in front of Mumbai's Town Hall. The location of these meetings changed many times as the number of brokers constantly increased. The group eventually moved to Dalal Street in 1874 and in 1875 became an official organization known as "The Native Share & Stock Brokers Association". On 31 August 1957, the BSE became the first stock exchange to be recognized by the Indian Government under the Securities Contracts Regulation Act. In 1980, the
  • 8. 8 KLE’s Institute of Management Studies and Research, Hubli exchange moved to the PhirozeJeeieebhoy Towers at Dalai Street, Fort area. In 1986, it developed the BSE SENSEX index, giving the BSE a means to measure overall performance of the exchange. In 2000, the BSE used this index to open its derivatives market, trading SENSEX futures contracts. The development of SENSEX options along with equity derivatives followed in 2001 and 2002, expanding the BSE's trading platform. Historically an open outcry floor trading exchange, the Bombay Stock Exchange switched to an electronic trading system developed by CMC Ltd in 1995. It took the exchange only fifty days to make this transition. This automated, screen based trading platform called BSE On-line trading (BOLT) had a capacity of 8 million orders per day. The BSE has also introduced a centralized exchange-based internet trading system, BSEWEBx.co.in to enable investors anywhere in the world to trade on the BSE platform. The BSE is also a Partner Exchange of the United Nations Sustainable stock Exchange initiative, joining in September 2012. NATIONAL STOCK EXCHANGE (NSE) The National Stock Exchange of India Limited (NSE) is the leading stock exchange of India, located in Mumbai. NSE was established in 1992 as the first demutualized electronic exchange in the country. NSE was the first exchange in the country to provide a modern, fully automated screen-based electronic trading system which offered easy trading facility to the investors spread across the length and breadth of the country. NSE has a market capitalization of more than US$1.65 trillion, making it the world’s 12th largest stock exchange as of 23 January 2015. NSE's flagship index, the CNX Nifty, the 50 stock indexes, is used extensively by investors in India and around the world as a barometer of the Indian capital markets. NSE was set up by a group of leading Indian financial institutions at the behest of the government of India to bring transparency to the Indian capital market. Based on the recommendations laid out by the government committee, NSE has been established with a diversified shareholding comprising domestic and global investors. The key domestic investors include Life InsuranceCorporation of India, State Bank of India, IFCL Limited IDFC Limited and Stock Holding Corporation of India Ltd. And the key global investors are Gagil FDI Limited, GS Strategic Investments Limited, SAIF II SE Investments Mauritius Limited, Aranda Investments (Mauritius) PVT Limited and PI Opportunities Fund I.
  • 9. 9 KLE’s Institute of Management Studies and Research, Hubli NSE offers trading, clearing and settlement services in equity, equity derivatives, debt and currency derivatives segments. It is the first exchange in India to introduce electronic trading facility thus connecting together the investor base of the entire country. NSE has 2500 VSATs and 3000 leased lines spread over more than 2000 cities across India. The exchange was incorporated in 1992 as a tax-paying company and was recognized as a stock exchange in 1993 under the Securities Contracts (Regulation) Act, 1956, when P.V.Narasimha Rao was the Prime Minister of India and Manmohan Singh was the Finance Minister. NSE commenced operations in the Wholesale Debt Market (WDM) segment in June 1994. The capital market (equities) segment of the NSE commenced operations in November 1994, while operations in the derivatives segment commenced in June 2000. INDICES In India major Indices are there known as SENSEX and NIFTY. The SENSEX was launched in the year 1989 and NIFTY launched in the year 1995. The Sensex have 30 listed companies based on the market capitalization and Nifty has 50 listed companies based on the market capitalization. Later on sector wise Indices are created by the exchange with some terms and conditions. The rules are like company should be from part of a particular sector, must rank in 500 companies, in the six month the trading frequency of the particular company should be more than 90%, should have positive net worth, and should have listing history of six months. Under the NIFTY index, Indices were created sector wise such CNX IT, CNX METAL CNX Small cap and so on. Under SENSEX like S & P midcap, S&P IT, and so on.
  • 10. 10 KLE’s Institute of Management Studies and Research, Hubli Chapter -3 Company profile
  • 11. 11 KLE’s Institute of Management Studies and Research, Hubli BNP Paribas completes acquisition of Sharekhan NOVEMBER 24/2016 BNP Paribas has announced that it has completed its acquisition of brokerage firm Sharekhan, a deal that was first announced in July 2015. The transaction has now been finalised after receiving approvals from all the relevant regulatory authorities. Tarun Shah, CEO and Director of Sharekhan, has announced his retirement. Jaideep Arora, Director, who has been with Sharekhan since its founding in 2000, has been appointed as CEO with immediate effect, BNP Paribas said in a press statement. Sharekhan is the retail brokering arm of SSKI; SSKI is SS Kantilal Ishwarlal Securities Pvt. Ltd. It is an organization with more than eight decades of trust and credibility in the stock market.
  • 12. 12 KLE’s Institute of Management Studies and Research, Hubli As the punch line of the company says it’s a guide to the financial jungle it has its many group of companies carrying on financial activities. Sharekhan – Retail broking brand Sharekhan is the retail broking arm of SSKI group. Sharekhan has successfully transformed into a full fledge retail brand of SSKI. It is a one stop shop for all kind of trading activities related to share and other recent happenings like derivative market and evolved commodity market in India. 2.2.1) Sharekhan.com Sharekhan.com is the answer for the highly volatile stock market in India. As the market has grown leaps and bounces in the recent year. SEBI (Securities & Exchange Board of India) has made Demat Account mandatory for trading in any of the stock exchanges. Share khan along with banks in India has fund transfer facility with many of these banks. The online form of trading is carried on through Sharkhan.com. It allows the clients to access the website to know about the latest news in the market and the impact it has on the various scrips. SSKI is in the Indian securities business since 1922. Share khan is serving Institutional Investors –Domestic /International. The institutional Research team is rated as one of the best in industry Sharekhan has been rated as among Top 3 domestic brokerage and rated as one of the most aggressive in the industry. 2.2.2) SSKI Group Companies  SSKI Investor Services Ltd. (Sharekhan)  S.S. Kantilal Ishwarlal Securities.  SSKI Corporate Finance. 2.2.3) Vision: To be the best retail broking brand in the Indian Equities market. 2.2.4) Mission: To educate and empower the individual investor to make better investment decisions through quality advice and superior service.
  • 13. 13 KLE’s Institute of Management Studies and Research, Hubli 2.2.5) The Sharekhan Way of Life:  People driven relationships  Growth driven  Values and ethics based 2.2.6) Sharekhan’s Beliefs and Expectations: At Sharekhan people believe in and promote a culture that …. Stimulates the employees drive to excel.  Nurture their entrepreneurial sprit by providing them exposure to challenging work opportunities and imparting autonomy to function effectively.  Enhancing transparency and trust, being non-discriminative to any practice/procedure/system.  Acknowledges and rewards individual and team contribution through appropriate rewards, recognition and compensation.  Builds a sense of ownership across the organization for adherence to risk and compliance procedures amongst all employees and channel partners. 2.2.6) Service profile:  Broking in Equities and derivatives on NSE & BSE.  Depository Services.  Commodities Trading on MCX & NCDEX.  IPO Services.  Portfolio management services.  Distribution services.  Structured products with fixed returns. 2.2.7) Achievements and Awards:  Rated among the top 20 wired companies along with Reliance, HLL, Infosys, etc by Business Today Jan 2004 edition.  Amongst the top 3 online trading websites from India most preferred financial destination amongst online banking customers. (Source: Net sense, an independent study of financial services in India)
  • 14. 14 KLE’s Institute of Management Studies and Research, Hubli  Winner of “Best Financial Website Award. CHIP- Dishnet DSL Web Awards.  India’s Most Preferred Broker award given to Sharekhan at the ‘Awaaz Consumer Awards 2005’ in the “Stock Broking” category. 2.2.8) Area of Operation: Growing network of share shops from Sharekhan.com to India’s largest chain of branded retail share shops – 679 shops in 234 towns. 679 branded share shops across 234 cities in India India’s largest chain of branded retail share shops
  • 15. 15 KLE’s Institute of Management Studies and Research, Hubli 2.2.9) Competitors Information: Major Competitors & their Product and Services, Portfolios & Strategies Competitors information & comparison Reliance Securities ltd Sharekhan Angel Broking Motilal Oswal Securities ltd ICICI Direct.Com About The Broke r Reliance Securities, A Reliance Capital Ltd Company, is the financial services division of Reliance Anil DhirubhaiAmb ani (ADA) Group. RelianceADA group is among top 3 business houses with PAN India presence. Incorporated in 2000,Sharekhan is India’s 2nd largest stock broker providing brokerage services through its online trading website Sharekhan.com and 1950 Share shops which include branches & Franchises in 575 cities across Angel Group has emerged as one of the top 3retail broking houses in India. Incorporated in 1987, it has membership on BSE, NSE and the two leading commodity exchange in India i.e. NCDEX & MCX. Incorporated in 1987, it is a well-diversified financial services firm offering a range of financial products, services such as Wealth Mgt Broking & Distribution, Commodity Broking, & Portfolio Mgt Services. It is an online trading & investment platform on ICICI Securities, the largest stock broker firm in India providing a wide range of investment options to the retail and institutional Customers. It is part of ICICI Group India. Types of Broke r Full Service Broker Full Service Broker Full Service Broker Full Service Broker Full Service Broker
  • 16. 16 KLE’s Institute of Management Studies and Research, Hubli Table Shows Stock Brokers fees or charges Reliance Securities ltd Sharekhan Angel Broking MotilalOswal Securities ltd Icici Direct.Com Trading Account opening Fees Rs 950(Free for individuals working in top 500 Companies or Free for Prepaid accounts). Rs 0 Rs 575 Nil Rs975 Trading account AMC Rs 0 Rs 0 Rs 347 Nil Nil Demat Account Opening Fees Nil Nil Rs 0 Nil Nil Demat Account AMC Rs 300 Rs 0 Rs 0 Rs 441 Rs 450
  • 17. 17 KLE’s Institute of Management Studies and Research, Hubli Table Shows Trading Brokerage charges Reliance Securities ltd Sharekhan Angel Broking MotilalOswal Securities ltd Icici Direct.Com Cm Segment Cash delivery 0.40% 0.50% 0.40% to 0.10% 0.50% 0.55% Cm Segment Cash Intraday 0.03% 0.10% 0.04% to 0.01% 0.10% 0.275% Margin Trading _ _ _ _ 0.05% 0.03% F&O Segment Futures 0.05% 0.10% 0.04% to 0.01% 0.10% 0.05% 0.03% F&O Segment Options Rs 70 per Lot Rs 100 per Lot 0.04% to 0.01% Rs 100 per lot Rs 95 Rs 65 per Lot Minimum Brokerage Charges 5paise per share 10 paise per share _ _ Rs 25
  • 18. 18 KLE’s Institute of Management Studies and Research, Hubli Table Shows Research tips Reports published Reliance Securitie s ltd Sharekha n Angel Brokin g MotilalOswa l Securities ltd Icici Direct.Co m Daily Market Reports      Free Tips    Quarterl y Result Analysis      News Alerts    Table Shows Investment options available Reliance Securities ltd Sharekhan Angel Broking MotilalOswal Securities ltd Icici Direct. Com Stock      Commodity      Currency      IPO      Mutual Funds      Bond    Debt     Other Financial Options Life Insurance, General _ _ _ Life Insuran ce, General
  • 19. 19 KLE’s Institute of Management Studies and Research, Hubli Table Shows Customer Services Offered Reliance Securities ltd Sharekha n Angel Brokin g MotilalOsw al Securities ltd Icici Direct.Co m Custome r Services  Email Support      Online Live Chart     Phone Support      Toll Free Number    
  • 20. 20 KLE’s Institute of Management Studies and Research, Hubli Chapter -4 Introduction to the topic
  • 21. 21 KLE’s Institute of Management Studies and Research, Hubli TECHNICAL ANALYSIS Technical analysis is the examination of past price movements to the forecast future price movements. Technical analysts are sometimes referred to as chartists because they rely almost exclusively on charts for their analysis. Technical analysis is applicable to stocks, indices, commodities, futures or any tradable instrument where the price is influenced by the forces of supply and demand. Price refers to any combination of open high, low or closes for given security over a specific timeframe. The timeframe can be used on intraday (tick, 5- minute, 15-minute or hourly), daily, weekly, or monthly price data and last a few hours or many years. A method of evaluating securities by analyzing statistics generated by market activity, such as past prices and volume. Technical analysts do not attempt to measure a security's intrinsic value, but instead use charts to identify patterns that can suggest future activity. Technical analysts believe that the historical performance of stocks and markets are indications of future performance. Technical analyst's belief that securities move according to very predictable trends and patterns. These trends continue until something happens to change the trend, and until this change occurs, Technical analysis takes a completely different approach; it doesn’t care one bit about the “value” of a company. Technicians (some time called chartists) are only interested in the price movement in the market. Despite all the fancy and exotic tools it employs, technical analysis really just studies Supply and demand in a market in an attempt to determine what direction, or trend, will continue in the future.
  • 22. 22 KLE’s Institute of Management Studies and Research, Hubli Assumptions of Technical analysis 1. The futures market discounts everything – The technician believes that the price at any given time is intrinsic value based upon the fundamental factors affecting the supply and demand of the product. 2. Prices move in trends – Prices can move in one of three directions up, down or sideways. Once a trend in any of these directions is in effect, it usually will persist. The market trend is simply the direction of market prices, a concept which is absolutely essential to the success of technical analysis. 3. History repeats itself - Technical analysis include the psychology of the market place. Patterns of human behaviors have been identified and categorized for several hundred years and are found to be repetitive in nature. The repetitive nature of the market place is illustrated by specific chart patterns, from which one can forecast the next move for the prices. 4. Supply and demand- The market value of the scrip is determined by the interaction of the demand and supply. TECHNICAL TOOLS
  • 23. 23 KLE’s Institute of Management Studies and Research, Hubli 1. MOVING AVERAGES Most chart patterns show a lot of variation in price movement. This can make it difficult for traders to get an idea of a security's overall trend. One simple method traders use to combat this is to apply moving. A moving average is the average price of a security over a set amount of time. By plotting a security's average price, the price movement is smoothed out. Once the day-to-day fluctuations are removed, traders are better able to identify the true trend and increase the probability that it will work in their favor. Types of Moving Averages: There are a number of different types of moving averages that vary in the way they are calculated, but how each average is interpreted remains the same. The calculations only differ in regards to the weighting that they place on the price data, shifting from equal weighting of each price point to more weight being placed on recent data. The three most common types of moving averages are simple, linear, and exponential. Simple Moving Average (SMA): This is the most common method used to calculate the moving average of prices. It simply takes the sum of all of the past closing prices over the time period and divides the result by the number of prices used in the calculation. For example, in a 13-day moving average, the last 13 closing prices are added together and then divided by 13. A trader is able to make the average less responsive to changing prices by increasing the number of periods used in the calculation. Increasing the number of time periods in the calculation is one of the best ways to gauge the strength of the long-term trend and the likelihood that it will reverse. Many individuals argue that the usefulness of this type of average is limited because each. Point in the data series has the same impact on the result regardless of where it occurs in the sequence. The critics argue that the most recent data is more important and, therefore, it should also have a higher weighting. This type of criticism has been one of the main factors leading to the invention of other forms of moving averages. Chart No: 1
  • 24. 24 KLE’s Institute of Management Studies and Research, Hubli Linear Weighted Average: This moving average indicator is the least common out of the three and is used to address the problem of the equal weighting. The linear weighted moving average is calculated by taking the sum of all the closing prices over a certain time period and multiplying them by the position of the data point and then dividing by the sum of the number of periods. For example, in a five-day linear weighted average, today's closing price is multiplied by five, yesterday's by four and so on until the first day in the period range is reached. These numbers are then added together and divided by the sum of the multipliers. Exponential Moving Average: This moving average calculation uses a smoothing factor to place a higher weight on recent data points and is regarded as much more efficient than the linear weighted average. Having an understanding of the calculation is not generally required for most traders because most charting packages do the calculation for you. The most important thing to remember about the exponential moving average is that it is more responsive to new information relative to the simple moving average. This responsiveness is one of the key factors of why this is the moving average of choice among many technical traders. As you can see in Figure 2, a 15-period EMA rises and falls faster than a 15-period SMA. This slight difference doesn't seem like much, but it is an important factor to be aware of since it can affect returns. . 2. Relative Strength Index:
  • 25. 25 KLE’s Institute of Management Studies and Research, Hubli Relative Strength Index (RSI) is a popular oscillator. It was first introduced by Welles Wilder in an article in Commodities (now known as Futures) Magazine in June, 1978. The name "Relative Strength Index" is slightly misleading as the Relative Strength Index does not compare the relative strength of two securities, but rather the internal strength of a single security. A more appropriate name might be "Internal Strength Index." The RSI can be calculated for any number of days depending on the wish of the technical analyst and the time frame of trading adopted in a particular stock market. RSI can be calculated for 5, 7, 9 and 14 days. If the time period taken for calculation is more, the possibility of getting wrong signals is reduced. Reactionary sustained rise or fall in the price of the scrip is foretold by the RSI. The Relative Strength Index is a price-following oscillator that ranges between 0 and 100. A popular method of analyzing the Relative Strength Index is to look for a divergence in which the security is making a new high, but the Relative Strength Index is failing to surpass its previous high. This divergence is an indication of an impending reversal. When the Relative Strength Index then turns down and falls below its most recent trough, it is said to have completed a "failure swing." The failure swing is considered a confirmation of the impending reversal. The RSI measures the ratio of up-moves to down-moves and normalizes the calculation so that the index is expressed in a range of 0-100. If the RSI is 70 or greater, then the instrument is assumed to be overbought (a situation in which prices have risen more than market expectations). An RSI of 30 or less is taken as a signal that the instrument may be oversold (a situation in which prices have fallen more than the market expectations. The RSI compares the magnitude of a stock's recent gains to the magnitude of its recent losses and turns that information into a number that ranges from 0 to 100.
  • 26. 26 KLE’s Institute of Management Studies and Research, Hubli In Mr. Welder’s book, he discusses five uses of the Relative Strength Index: 1. Tops and Bottoms-The Relative Strength Index usually tops above 70 and bottoms below 30. It usually forms these tops and bottoms before the underlying price chart. 2. Chart Formations-The Relative Strength Index often forms chart patterns such as head and shoulders or triangles that may or may not be visible on the price chart. 3. Failure Swings-(also known as support or resistance penetrations or breakouts). This is where the Relative Strength Index surpasses a previous high (peak) or falls below a recent low (trough). 4. Support and Resistance -The Relative Strength Index shows, sometimes more clearly than price themselves, levels of support and resistance. 5. Divergences- As discussed above, divergences occur when the price makes a new high (or low) that is not confirmed by a new high (or low) in the Relative Strength Index. Prices usually correct and move in the direction of the Relative Strength Index.
  • 27. 27 KLE’s Institute of Management Studies and Research, Hubli Chapter-5 Analysis and data interpretation Table1: Calculation of Simple moving average
  • 28. 28 KLE’s Institute of Management Studies and Research, Hubli Date Infosys closing 30 SMA Wipro closing 30 SMA Mind tree closing 30 SMA TCS closing 30 SMA 01-04-2016 1205.90002 562.15002 668.15 2455.4 04-04-2016 1243.55005 566.25 676.05 2470.7 05-04-2016 1218.59998 559 658.35 2462.65 06-04-2016 1201.09998 558.20001 667.9 2478.9 07-04-2016 1181.65002 551.79999 671.65 2470.95 08-04-2016 1167.34998 549.54999 667.5 2428.7 11-04-2016 1184.40002 565.75 667.7 2506.65 12-04-2016 1182.30005 569.54999 677 2512.5 13-04-2016 1172.05005 584.90002 691.6 2523.15 14-04-2016 1172.05005 584.90002 691.6 2523.15 15-04-2016 1172.05005 584.90002 691.6 2523.15 18-04-2016 1238.80005 588.59998 730.8 2522.4 19-04-2016 1238.80005 588.59998 730.8 2522.4 20-04-2016 1243.25 601.25 723.95 2451.9 21-04-2016 1226.40002 558.84998 715.8 2423.2 22-04-2016 1213.84998 557.95001 708.3 2417.2 25-04-2016 1217.05005 552.45001 698.5 2448.3 26-04-2016 1232.94995 554.45001 707.35 2488 27-04-2016 1240 560 699.7 2505.55 28-04-2016 1211.44995 553.09998 686.2 2526.95 29-04-2016 1210.84998 554.34998 678.8 2530.05 02-05-2016 1200.65002 548.5 681.85 2525.15 03-05-2016 1180.75 543.84998 670.25 2480.25 04-05-2016 1189.55005 540 661.45 2478.25 05-05-2016 1192.44995 543.09998 664 2474 06-05-2016 1181.44995 533.09998 659 2472.15 09-05-2016 1199.15002 539 657.15 2515.35 10-05-2016 1212.55005 538.65002 645.85 2523.6 11-05-2016 1201.05005 537.79999 652.35 2517.75 12-05-2016 1210.19995 1204.74 542.29999 559.095 660.25 682.0483 2567.05 2491.513 13-05-2016 1206.69995 1204.767 539.65002 558.345 652.9 681.54 2523.4 2493.78 16-05-2016 1213.94995 1203.78 540.79999 557.4967 645.3 680.515 2553.8 2496.55 17-05-2016 1214.05005 1203.628 540.15002 556.8683 645.5 680.0867 2570.2 2500.135 18-05-2016 1209.75 1203.917 539.54999 556.2467 644 679.29 2550.45 2502.52 19-05-2016 1205.34998 1204.707 542.95001 555.9517 644 678.3683 2555.55 2505.34 20-05-2016 1201.75 1205.853 543.40002 555.7467 630.45 677.1333 2532.05 2508.785 23-05-2016 1190.75 1206.065 539.84998 554.8833 640.85 676.2383 2491.7 2508.287 24-05-2016 1188.19995 1206.262 537.65002 553.82 647.75 675.2633 2467.5 2506.787 25-05-2016 1208.84998 1207.488 546.09998 552.5267 648.75 673.835 2526.7 2506.905
  • 29. 29 KLE’s Institute of Management Studies and Research, Hubli 26-05-2016 1231.65002 1209.475 544.95001 551.195 665.35 672.96 2552.8 2507.893 27-05-2016 1246.40002 1211.953 545.40002 549.8783 667.6 672.16 2572.05 2509.523 30-05-2016 1263.44995 1212.775 550.15002 548.5967 671.7 670.19 2635.35 2513.288 31-05-2016 1249.84998 1213.143 545.45001 547.1583 660.9 667.86 2575.1 2515.045 01-06-2016 1256.44995 1213.583 554.5 545.6 654.8 665.555 2631.85 2521.043 02-06-2016 1260.25 1214.712 540.40002 544.985 653.6 663.4817 2646.9 2528.5 03-06-2016 1266.44995 1216.465 540.79999 544.4133 647.45 661.4533 2630.85 2535.622 06-06-2016 1267.09998 1218.133 535.09998 543.835 644.55 659.655 2611.35 2541.057 07-06-2016 1257.19995 1218.942 539.84998 543.3483 650.3 657.7533 2631.45 2545.838 08-06-2016 1238.30005 1218.885 544.59998 542.835 650.7 656.12 2611.1 2549.357 09-06-2016 1185.44995 1218.018 544.79999 542.5583 639.2 654.5533 2577.5 2551.042 10-06-2016 1180.80005 1217.017 545.34998 542.2583 639.35 653.2383 2560.95 2552.072 13-06-2016 1182.55005 1216.413 541.20001 542.015 635.15 651.6817 2551.95 2552.965 14-06-2016 1175.19995 1216.228 543.09998 541.99 643.95 650.805 2534.7 2554.78 15-06-2016 1189.19995 1216.217 547.04999 542.225 640.05 650.0917 2555.7 2557.362 16-06-2016 1186.19995 1216.008 549.90002 542.4517 630.05 648.96 2557.1 2560.132 17-06-2016 1178.30005 1215.903 552.04999 543.0833 630 647.9933 2603.5 2564.51 20-06-2016 1208.59998 1216.218 557.04999 543.685 639.8 647.415 2655.7 2569.188 21-06-2016 1205.90002 1215.997 561 544.43 657.7 647.81 2647.3 2573.312 22-06-2016 1198.55005 1215.913 563.15002 545.275 653.6 647.8517 2665.5 2578.237 23-06-2016 1211.55005 1215.958 563.70001 545.9883 659.95 647.8417 2644.3 2580.812 24-06-2016 1194.5 1215.552 555.15002 546.505 659.9 648.075 2570.7 2582.388 27-06-2016 1166.25 1213.962 548 546.745 651.85 648.2933 2495.35 2580.44 28-06-2016 1161.05005 1212.195 542.40002 546.82 662.8 648.87 2461.8 2576.827 29-06-2016 1176.55005 1211.088 554.54999 547.32 663.4 649.5167 2499.6 2575.132 30-06-2016 1170.75 1209.935 557.95001 547.82 664.85 650.2117 2550.8 2574.973 01-07-2016 1172.09998 1208.947 558.90002 548.3367 673.9 651.66 2501.8 2573.965 04-07-2016 1184.25 1208.73 561.70001 549.065 672.15 652.7033 2494.8 2574.068 05-07-2016 1175.44995 1208.305 564.95001 549.975 678.3 653.7217 2482.7 2574.575 06-07-2016 1175.44995 1207.192 564.95001 550.6033 678.3 654.7067 2482.7 2573.108 07-07-2016 1157.19995 1204.71 559.59998 551.0917 659.35 654.5067 2429.05 2568.983 08-07-2016 1158.75 1201.788 561.65002 551.6333 654.4 654.0667 2425.5 2564.098 11-07-2016 1174.84998 1198.835 568.84998 552.2567 665.55 653.8617 2463.65 2558.375 12-07-2016 1176 1196.373 570.79999 553.1017 661.05 653.8667 2461.5 2554.588 13-07-2016 1193.15002 1194.263 573.95001 553.75 650.45 653.7217 2491.4 2549.907 14-07-2016 1175.84998 1191.45 570.59998 554.7567 653.3 653.7117 2520.3 2545.687 15-07-2016 1072.25 1184.977 554.5 555.2133 637.25 653.3717 2441.9 2539.388 18-07-2016 1081.69995 1178.797 551.95001 555.775 614.2 652.36 2433.5 2533.46 19-07-2016 1086.30005 1173.1 549.25 556.0883 561.55 649.4017 2461.55 2527.797 20-07-2016 1083.05005 1167.925 538.84998 555.8967 570.4 646.725 2493.25 2523.868 21-07-2016 1080.34998 1164.422 542 555.8033 565.95 644.2833 2501.25 2521.327 22-07-2016 1072.65002 1160.817 537.75 555.55 556.9 641.535 2509.15 2519.6 25-07-2016 1080.5 1157.415 542.84998 555.605 551.75 638.755 2551.55 2519.587 26-07-2016 1088.80005 1154.535 546.09998 555.705 565 636.1233 2548.3 2520.04
  • 30. 30 KLE’s Institute of Management Studies and Research, Hubli 27-07-2016 1087.55005 1151.147 549.15002 555.775 565.1 633.625 2576.1 2520.72 28-07-2016 1079.19995 1147.58 553.79999 555.905 582.3 632.0333 2615.55 2522.668 29-07-2016 1073.94995 1144.102 545.04999 555.6717 578.65 630.3217 2618.55 2523.17 01-08-2016 1085 1139.982 557.70001 555.6933 601.6 629.0483 2698 2524.58 02-08-2016 1084.30005 1135.928 549.59998 555.3133 612.95 627.5567 2692.1 2526.073 03-08-2016 1085 1132.143 547.95001 554.8067 600.1 625.7733 2656.25 2525.765 04-08-2016 1072.15002 1127.497 548.20001 554.29 604.85 623.9367 2652.65 2526.043 05-08-2016 1067.40002 1123.26 547.20001 554.025 613 622.3733 2648.9 2528.65 08-08-2016 1078.80005 1120.345 549 554.0583 617.8 621.2383 2651.9 2533.868 09-08-2016 1081.5 1117.693 551.34998 554.3567 596.55 619.03 2650.55 2540.16 10-08-2016 1079.94995 1114.473 542.65002 553.96 572.3 615.9933 2673.9 2545.97 11-08-2016 1077.09998 1111.352 543 553.4617 580.7 613.1883 2704.3 2551.087 12-08-2016 1063.30005 1107.725 543.75 552.9567 579.8 610.0517 2732.35 2558.772 15-08-2016 1063.30005 1103.693 543.75 552.3583 579.8 606.9733 2732.35 2566.69 16-08-2016 1050.94995 1099.543 536.5 551.41 569.15 603.335 2691.45 2573.648 17-08-2016 1033.40002 1094.808 527.79999 550.1717 566.35 599.6033 2623.9 2578.355 18-08-2016 1024.30005 1090.378 525.09998 549.0217 564.75 596.45 2636.7 2585.277 19-08-2016 1021.09998 1085.79 520.09998 547.6367 565.7 593.4933 2603.95 2591.225 22-08-2016 1015.40002 1080.475 515.5 545.8583 551.25 589.6833 2551.45 2594.152 23-08-2016 1039.25 1075.917 519.59998 544.1517 566.2 586.5217 2603.2 2598.875 24-08-2016 1057.55005 1071.397 519.65002 542.3417 568.6 583.7933 2571.9 2601.558 25-08-2016 1036.55005 1066.753 504 540.1217 567.8 580.9433 2550.1 2602.552 26-08-2016 1020.75 1065.037 490 537.9717 569.25 578.6767 2529.15 2605.46 29-08-2016 1022.25 1063.055 478.79999 535.5333 564.95 577.035 2501.6 2607.73 30-08-2016 1041 1061.545 489.45001 533.54 570.15 577.3217 2548.7 2610.635 31-08-2016 1036.80005 1060.003 491.64999 531.9667 562.55 577.06 2512.55 2611.278 01-09-2016 1037.65002 1058.58 483.95001 530.0317 553.75 576.6533 2507.6 2611.49 02-09-2016 1031.05005 1057.193 483.60001 528.2267 548.85 576.385 2513.5 2611.635 05-09-2016 1031.05005 1055.545 483.60001 526.2517 548.85 576.2883 2513.5 2610.367 06-09-2016 1045.09998 1054.088 482.89999 524.145 525 574.955 2484.05 2608.225 07-09-2016 1055 1053.003 481.75 521.8983 518.9 573.415 2447 2603.922 08-09-2016 1037.90002 1051.627 473.95001 519.2367 515.3 571.1817 2321.15 2594.108 09-09-2016 1036 1050.362 480.64999 517.09 522.8 569.32 2352.5 2585.24 12-09-2016 1054 1049.328 480.39999 514.5133 516.5 566.4833 2359.1 2573.943 13-09-2016 1054 1048.318 480.39999 512.2067 516.5 563.2683 2359.1 2562.843 14-09-2016 1047.09998 1047.055 478.04999 509.8767 513.5 560.3817 2328.55 2551.92 15-09-2016 1041.34998 1046.028 478.45001 507.5517 514 557.3533 2328.05 2541.1 16-09-2016 1060.34998 1045.793 479.39999 505.2917 512.2 553.9933 2361.15 2531.508 19-09-2016 1061.15002 1045.205 479.95001 502.99 505.25 550.2417 2407.35 2523.357 20-09-2016 1050.34998 1044.167 481.04999 500.6467 502.1 547.0933 2411.1 2515.375 21-09-2016 1056.69995 1043.392 483.85001 498.6867 510.25 545.025 2413.5 2506.695 22-09-2016 1058.5 1042.772 481.75 496.645 509.75 542.66 2377.65 2495.807 23-09-2016 1043 1042.095 480.20001 494.5267 505.2 540.1733 2397.3 2484.638 26-09-2016 1035.69995 1041.175 479.29999 492.3783 497.75 537.4383 2400.85 2473.588
  • 31. 31 KLE’s Institute of Management Studies and Research, Hubli 27-09-2016 1040.44995 1040.825 484.20001 490.635 493 534.9 2430.7 2464.897 28-09-2016 1038.59998 1040.998 483.70001 489.165 492.95 532.4533 2423.45 2458.215 29-09-2016 1029.90002 1041.185 472.20001 487.4017 481.6 529.6817 2434.6 2451.478 30-09-2016 1038.09998 1041.752 478.95001 486.03 482.15 526.8967 2427.2 2445.587 03-10-2016 1037.84998 1042.5 478.95001 484.8117 488.55 524.8067 2411.8 2440.932 04-10-2016 1048.80005 1042.818 481.79999 483.5517 495.95 522.465 2401.1 2434.195 05-10-2016 1041.15002 1042.272 479.54999 482.215 498.4 520.125 2382.55 2427.883 06-10-2016 1026.65002 1041.942 478 481.3483 491.2 517.5717 2384.25 2422.355 07-10-2016 1012.65002 1041.672 476.95001 480.9133 491.85 514.9917 2368.25 2416.992 10-10-2016 1029.55005 1041.915 477 480.8533 500.9 512.8567 2380.1 2412.942 11-10-2016 1029.55005 1041.533 477 480.4383 500.9 510.5483 2380.1 2407.322 12-10-2016 1029.55005 1041.292 477 479.95 500.9 508.4933 2380.1 2402.907 13-10-2016 1052.05005 1041.772 478.25 479.76 489.7 506.3583 2328.5 2396.937 14-10-2016 1027.40002 1041.65 475 479.4733 501.05 504.765 2365.9 2392.017 17-10-2016 1022.04999 1041.35 472.14999 479.0917 490.6 502.8233 2362.9 2386.997 18-10-2016 1038.19995 1041.12 482.75 479.0867 476.85 501.2183 2398.3 2384.138 19-10-2016 1041.59998 1040.673 495 479.5283 476.95 499.82 2394.2 2382.378 20-10-2016 1036.94995 1040.642 495.39999 480.2433 479.05 498.6117 2399.85 2385.002 21-10-2016 1038.09998 1040.712 499.20001 480.8617 479 497.1517 2428.7 2387.542 24-10-2016 1029 1039.878 483.95001 480.98 456 495.135 2427.85 2389.833 25-10-2016 1017.34998 1038.657 481.39999 481.0133 454.9 493.0817 2398.65 2391.152 26-10-2016 1014.84998 1037.582 471.54999 480.7967 450.2 490.9717 2396.95 2393.432 27-10-2016 1006.15002 1036.408 461.70001 480.2383 441.5 488.555 2413.25 2396.272 28-10-2016 997.45001 1034.312 462.10001 479.6617 435.95 486.0133 2399.25 2397.542 31-10-2016 997.45001 1032.188 462.10001 479.0667 435.95 483.7033 2399.25 2397.272 01-11-2016 988.84998 1030.138 460.75 478.39 439.55 481.6183 2347.7 2395.158 02-11-2016 981.09998 1027.618 457.89999 477.525 433.55 479.0617 2304.45 2391.523 03-11-2016 966.90002 1024.565 447.60001 476.3867 428.35 476.3483 2319.95 2389.6 04-11-2016 970.79999 1022.158 452.5 475.4633 425.15 473.68 2330.1 2387.36 07-11-2016 978.75 1020.26 450 474.4867 429.25 471.3967 2279.35 2383.31 08-11-2016 982.79999 1018.338 451.75 473.405 442.65 469.7183 2283.7 2378.41 09-11-2016 955.84998 1015.58 446.89999 472.1783 436.15 467.825 2171.05 2369.997 10-11-2016 938.59998 1012.537 444.95001 471.27 437.4 466.3517 2158.05 2360.778 11-11-2016 921.84998 1008.662 442.35001 470.05 423.55 464.3983 2105.05 2350.04 14-11-2016 921.84998 1004.795 442.35001 468.83 423.55 462.2317 2105.05 2339.815 15-11-2016 924.75 1000.66 447.95001 467.7017 430.55 460.0517 2122.1 2330.515 16-11-2016 940.09998 997.2917 445.29999 466.56 437.9 458.035 2190.25 2324.105 17-11-2016 929.54999 994.055 438.39999 465.24 441.75 456.3867 2142.15 2316.035 18-11-2016 919.79999 990.96 437.14999 463.9133 442.25 454.7333 2123.15 2307.865 21-11-2016 911.15002 987.0133 441.79999 462.74 441.8 452.7633 2132.55 2299.613 22-11-2016 913.95001 983.16 450.39999 461.8533 453.15 451.1717 2134.3 2291.42 23-11-2016 920.5 979.525 448.89999 460.9167 453.5 449.5917 2156.7 2283.973 24-11-2016 932.70001 975.5467 450.75 460 462.85 448.6967 2186.5 2279.24 25-11-2016 977.29999 973.8767 464.75 459.6583 478.25 447.9367 2300.85 2277.072
  • 32. 32 KLE’s Institute of Management Studies and Research, Hubli 28-11-2016 979.65002 972.4633 460.60001 459.2733 477.8 447.51 2277.3 2274.218 29-11-2016 972.65002 970.2783 465.14999 458.6867 473.65 447.4033 2258.4 2269.555 30-11-2016 975.45001 968.0733 465.25 457.695 477.35 447.4167 2276.75 2265.64 01-12-2016 976.04999 966.0433 468.29999 456.7917 466.6 447.0017 2266.45 2261.193 02-12-2016 964.09998 963.5767 460.39999 455.4983 460.45 446.3833 2223.9 2254.367 05-12-2016 961.40002 961.3233 456.64999 454.5883 448.35 446.1283 2186.45 2246.32 06-12-2016 966.95001 959.6433 457.79999 453.8017 459.8 446.2917 2190.45 2239.38 07-12-2016 966.59998 958.035 453.35001 453.195 457.75 446.5433 2158.2 2231.422 08-12-2016 984.75 957.3217 458.60001 453.0917 462.2 447.2333 2196.9 2224.21 09-12-2016 987.34998 956.985 458.10001 452.9583 470.65 448.39 2193.45 2217.35 12-12-2016 977.5 956.32 453.54999 452.6733 468.25 449.4667 2206.25 2210.917 13-12-2016 990.04999 956.36 463.75 452.7733 492.5 451.2317 2200.85 2206.022 14-12-2016 999.04999 956.9583 466.29999 453.0533 502.9 453.5433 2207.9 2202.803 15-12-2016 993.25 957.8367 466.10001 453.67 495.3 455.775 2259.5 2200.788 16-12-2016 1004.20001 958.95 463.5 454.0367 501.35 458.315 2281.75 2199.177 19-12-2016 1002.20001 959.7317 463.54999 454.4883 500.1 460.6767 2287.5 2199.448 20-12-2016 1010.40002 960.6517 466.64999 454.985 494.1 462.3917 2337.75 2201.25 21-12-2016 1003.70001 962.2467 462.45001 455.5033 493.95 464.3183 2312.75 2205.973 22-12-2016 985.20001 963.8 461.70001 456.0617 495.4 466.2517 2309.85 2211.033 23-12-2016 989.29999 966.0483 458.75 456.6083 496.9 468.6967 2290.2 2217.205 26-12-2016 983 968.0867 456.10001 457.0667 487.9 470.8417 2292.1 2223.44 27-12-2016 999.25 970.57 465.20001 457.6417 486.2 472.6967 2321.85 2230.098 28-12-2016 999.15002 972.5383 469.35001 458.4433 510.15 475.105 2315.8 2234.283 29-12-2016 994.09998 974.69 472.35001 459.575 523.85 477.8417 2350.75 2241.237 30-12-2016 1010.70001 977.72 474.45001 460.8183 521.65 480.4883 2361.95 2249.197 02-01-2017 1001.59998 980.735 471.54999 461.81 516.7 482.985 2359.05 2256.747 03-01-2017 994.65002 983.425 467 462.3633 507.9 484.81 2368.5 2264.553 04-01-2017 998.29999 986.0183 475.60001 463.2533 526.4 487.24 2378.55 2271.948 05-01-2017 996.40002 988.1417 480.39999 464.2417 523.7 489.2683 2334.55 2276.883 06-01-2017 971.45001 987.9467 469.95001 464.415 500.2 490 2283.6 2276.308 09-01-2017 970.54999 987.6433 472 464.795 495.5 490.59 2303.75 2277.19 10-01-2017 970.59998 987.575 476.5 465.1733 487.15 491.04 2315.45 2279.092 11-01-2017 969 987.36 476.20001 465.5383 487.3 491.3717 2323.05 2280.635 12-01-2017 1000.04999 988.16 483.20001 466.035 491.3 492.195 2343.3 2283.197 13-01-2017 975.15002 988.5283 484.64999 466.8433 490.85 493.2083 2252 2284.133 16-01-2017 955.70001 988.3383 484.75 467.78 484.95 494.4283 2258.55 2286.537 17-01-2017 956.04999 987.975 482.39999 468.6 484.85 495.2633 2277.65 2289.443 18-01-2017 950.90002 987.4517 482.95001 469.5867 495.5 496.5217 2295 2294.003 19-01-2017 958.54999 986.5783 479 470.2667 485.1 497.285 2290.3 2297.117 20-01-2017 948.79999 985.2933 477.89999 470.9267 475.25 497.4383 2287.45 2300.25 23-01-2017 951.75 984.435 479.75 471.8 471.3 497.54 2305.7 2303.565 24-01-2017 945.09998 982.9367 481.5 472.3917 470.25 496.7983 2318 2307.47 25-01-2017 936.65002 980.8567 473.70001 472.6383 461.65 495.4233 2352.7 2312.297 26-01-2017 936.65002 978.97 473.70001 472.8917 461.65 494.3017 2352.7 2315.403
  • 33. 33 KLE’s Institute of Management Studies and Research, Hubli 27-01-2017 942.15002 976.9017 465.54999 472.96 472.5 493.34 2358.05 2317.947 30-01-2017 948.34998 975.1067 465.75 473.0333 465.55 492.1883 2334.2 2319.503 31-01-2017 929.29999 972.4033 458 472.745 450.5 490.735 2229.9 2315.908 01-02-2017 916.54999 969.4983 456 472.53 459.85 489.5983 2169.45 2311.132 02-02-2017 935.34998 967.8367 455.64999 472.3283 461 488.4517 2205.8 2307.663 03-02-2017 934.95001 966.025 457.75 472.295 459.35 487.2 2233.75 2305.782 06-02-2017 934.45001 964.4067 461.10001 472.4617 464.85 486.4317 2240.55 2304.063 07-02-2017 944.75 962.59 458.54999 472.24 452.8 485.3183 2244.8 2301.495 08-02-2017 936.45001 960.5 460.5 471.945 450.1 483.3167 2262.65 2299.723 09-02-2017 948.09998 958.9667 466 471.7333 457.6 481.1083 2324.25 2298.84 10-02-2017 968.04999 957.545 469.25 471.56 466.65 479.275 2396.7 2299.998 13-02-2017 983.5 956.9417 474.45001 471.6567 468.15 477.6567 2410.3 2301.707 14-02-2017 987.29999 956.6967 476.70001 471.98 455.1 475.8967 2402.95 2302.855 15-02-2017 982.34998 956.165 474.70001 471.95 457.65 473.605 2415.7 2304.093 16-02-2017 1011.90002 956.6817 480.79999 471.9633 468 471.7483 2446.9 2307.838 17-02-2017 999.70001 957.6233 475.35001 472.1433 475.15 470.9133 2408.15 2311.99 20-02-2017 1011.70001 958.995 475.64999 472.265 474.4 470.21 2506.5 2318.748 21-02-2017 1012.95001 960.4067 475.79999 472.2417 474.4 469.785 2464.3 2323.71 22-02-2017 991.84998 961.1683 474.5 472.185 468.2 469.1483 2409.55 2326.593 23-02-2017 1009.04999 961.4683 486.10001 472.2817 469.9 468.435 2481.65 2331.205 24-02-2017 1009.04999 962.5983 486.10001 472.33 469.9 467.7367 2481.65 2338.86 27-02-2017 1012.75 964.5 489.75 472.4967 471.15 467.2767 2488.9 2346.538 28-02-2017 1012.29999 966.375 488.79999 472.71 474.3 466.925 2466.5 2352.833 01-03-2017 1025 968.845 488.54999 472.8967 471.95 466.14 2480.05 2359.002 02-03-2017 1020.65002 970.915 490.20001 473.27 460.3 465.3133 2501.15 2366.03 03-03-2017 1031.15002 973.66 493.85001 473.8017 464.6 464.9583 2492.35 2372.86 06-03-2017 1033.84998 976.3967 491.89999 474.2067 460.25 464.59 2470.65 2378.358 07-03-2017 1019.70001 978.8833 495.14999 474.6617 478.7 464.8717 2500.7 2384.448 08-03-2017 1007.25 981.2367 495.10001 475.375 469.25 465.125 2513.9 2389.822 09-03-2017 1011.59998 983.735 484.5 475.735 472.65 465.4917 2519.55 2395.383 10-03-2017 1020.09998 986.3333 487.04999 476.4517 474.8 465.5683 2541.8 2401.508 13-03-2017 1020.09998 988.725 487.04999 477.1617 474.8 465.8767 2541.8 2408.428 14-03-2017 1032.5 992.165 501.35001 478.6067 470.85 466.555 2562.35 2419.51 15-03-2017 1012.09998 995.35 494.79999 479.9 466.55 466.7783 2500.3 2430.538 16-03-2017 1028.5 998.455 500.54999 481.3967 469.75 467.07 2518.95 2440.977 17-03-2017 1040 1001.957 504.25 482.9467 473.45 467.54 2526.85 2450.747 20-03-2017 1020.59998 1004.828 497.5 484.16 474.1 467.8483 2480.8 2458.755 21-03-2017 1032 1007.737 498.64999 485.4967 474.85 468.5833 2486.15 2466.8 22-03-2017 1027.80005 1010.782 500.54999 486.8317 472.3 469.3233 2479.1 2474.015 23-03-2017 1040.59998 1013.865 510 488.2983 472.2 469.81 2458.9 2478.503 24-03-2017 1031.80005 1015.99 513.25 489.765 469.55 469.9067 2426.75 2479.505 27-03-2017 1028.80005 1017.5 504 490.75 461.3 469.6783 2412.1 2479.565 28-03-2017 1035.09998 1019.093 507.54999 491.7783 459.95 469.84 2429.85 2480.462 29-03-2017 1031.34998 1020.727 512.25 493.03 456.1 469.7883 2443.75 2481.397
  • 34. 34 KLE’s Institute of Management Studies and Research, Hubli CHARTS INFOSYS(Simple Moving average): INTERPRETATION: Moving averages provides buy and sell signal. Above figure shows the calculation of simple moving average (SMA) for 30 days. Downward penetration of the rising average indicates the possibility of a further fall and gives the sell signal. Upward penetration of a falling average would indicate the possibility of the further rise and gives the buy signal. From the above chart we came to know that in the month of December 2016, was right time to buy the share of Infosys. And in the month of January 2017, was right time to sell the shares because prices were falling. WIPRO (Simple Moving average) : 30-03-2017 1024.5 1021.147 515.95001 494.2017 453.2 469.295 2443.75 2481.292 31-03-22017 1020.79999 1021.85 515.70001 495.5467 452.95 468.555 2431.1 2482.057
  • 35. 35 KLE’s Institute of Management Studies and Research, Hubli INTERPRETATION: Moving averages provides buy and sell signal. Above figure shows the calculation of simple moving average (SMA) for 30 days. Downward penetration of the rising average indicates the possibility of a further fall and gives the sell signal. Upward penetration of a falling average would indicate the possibility of the further rise and gives the buy signal. From the above chart we came to know that in the month of December 2016, was right time to buy the shares of Wipro. And in the month of February 2017, was right time to sell the shares. MINDTREE (Simple Moving average):
  • 36. 36 KLE’s Institute of Management Studies and Research, Hubli INTERPRETATION: Moving averages provides buy and sell signal. Above figure shows the calculation of simple moving average (SMA) for 30 days. Downward penetration of the rising average indicates the possibility of a further fall and gives the sell signal. Upward penetration of a falling average would indicate the possibility of the further rise and gives the buy signal. From the above chart we came to know that in the month of December 2016, was right time to buy the shares of Mindtree. And in the month of February 2017, was right time to sell the shares because prices were falling. TCS (Simple Moving average):
  • 37. 37 KLE’s Institute of Management Studies and Research, Hubli INTERPRETATION: Moving averages provides buy and sell signal. Above figure shows the calculation of simple moving average (SMA) for 30 days. Downward penetration of the rising average indicates the possibility of a further fall and gives the sell signal. Upward penetration of a falling average would indicate the possibility of the further rise and gives the buy signal. From the above chart we came to know that in the month of December 2016 was right time to buy the shares of TCS. And in the month of February 2017 was right time to sell the shares because prices were falling. Table 2) Calculationof Relative Strength Index:
  • 38. 38 KLE’s Institute of Management Studies and Research, Hubli Infosys ( Relative Strength Index): Date Infosysclosing Change Gain Loss RS Value RSI 01-04-2016 1205.90002 04-04-2016 1243.55005 37.65003 37.65003 0 05-04-2016 1218.59998 -24.9501 0 24.95007 06-04-2016 1201.09998 -17.5 0 17.5 07-04-2016 1181.65002 -19.45 0 19.44996 08-04-2016 1167.34998 -14.3 0 14.30004 11-04-2016 1184.40002 17.05004 17.05004 0 12-04-2016 1182.30005 -2.09997 0 2.09997 13-04-2016 1172.05005 -10.25 0 10.25 14-04-2016 1172.05005 0 0 0 15-04-2016 1172.05005 0 0 0 18-04-2016 1238.80005 66.75 66.75 0 19-04-2016 1238.80005 0 0 0 20-04-2016 1243.25 4.44995 4.44995 0 21-04-2016 1226.40002 -16.85 0 16.84998 1.194497 54.43147 22-04-2016 1213.84998 -12.55 0 12.55004 0.748198 42.79824 25-04-2016 1217.05005 3.20007 3.20007 0 0.983334 49.57985 26-04-2016 1232.94995 15.8999 15.8999 0 1.421854 58.70932 27-04-2016 1240 7.05005 7.05005 0 2.041034 67.11645 28-04-2016 1211.44995 -28.5501 0 28.55005 1.627311 61.93827 29-04-2016 1210.84998 -0.59997 0 0.59997 1.37306 57.86032 02-05-2016 1200.65002 -10.2 0 10.19996 1.232278 55.20271 03-05-2016 1180.75 -19.9 0 19.90002 1.098138 52.3387 04-05-2016 1189.55005 8.80005 8.80005 0 1.197405 54.49179 05-05-2016 1192.44995 2.8999 2.8999 0 1.230117 55.15931 06-05-2016 1181.44995 -11 0 11 0.424485 29.79918 09-05-2016 1199.15002 17.70007 17.70007 0 0.602107 37.5822 10-05-2016 1212.55005 13.40003 13.40003 0 0.691922 40.89563 11-05-2016 1201.05005 -11.5 0 11.5 0.731178 42.23585 12-05-2016 1210.19995 9.1499 9.1499 0 0.955351 48.8583 13-05-2016 1206.69995 -3.5 0 3.5 0.878591 46.76862 16-05-2016 1213.94995 7.25 7.25 0 0.777126 43.72937 17-05-2016 1214.05005 0.1001 0 -0.1001 0.695244 41.01144 18-05-2016 1209.75 -4.30005 0 4.30005 0.972086 49.29228 19-05-2016 1205.34998 -4.40002 0 4.40002 0.914992 47.78047 20-05-2016 1201.75 -3.59998 0 3.59998 1.018933 50.46888 23-05-2016 1190.75 -11 0 11 1.203252 54.61255 24-05-2016 1188.19995 -2.55005 0 2.55005 0.973911 49.33916 25-05-2016 1208.84998 20.65003 20.65003 0 1.316909 56.83904 26-05-2016 1231.65002 22.80004 22.80004 0 2.231904 69.05848 27-05-2016 1246.40002 14.75 14.75 0 2.159509 68.34951
  • 39. 39 KLE’s Institute of Management Studies and Research, Hubli 30-05-2016 1263.44995 17.04993 17.04993 0 2.249077 69.22203 31-05-2016 1249.84998 -13.6 0 13.59997 2.138856 68.14126 01-06-2016 1256.44995 6.59997 6.59997 0 2.079347 67.52559 02-06-2016 1260.25 3.80005 3.80005 0 2.360866 70.24577 03-06-2016 1266.44995 6.19995 6.19995 0 2.334181 70.00763 06-06-2016 1267.09998 0.65003 0 -0.65003 2.367265 70.30231 07-06-2016 1257.19995 -9.90003 0 9.90003 2.068692 67.41283 08-06-2016 1238.30005 -18.8999 0 18.8999 1.559425 60.92872 09-06-2016 1185.44995 -52.8501 0 52.8501 0.849283 45.92499 10-06-2016 1180.80005 -4.6499 0 4.6499 0.90226 47.43094 13-06-2016 1182.55005 1.75 1.75 0 0.943074 48.53516 14-06-2016 1175.19995 -7.3501 0 7.3501 0.684334 40.62934 15-06-2016 1189.19995 14 14 0 0.601782 37.56952 16-06-2016 1186.19995 -3 0 3 0.450729 31.06914 17-06-2016 1178.30005 -7.8999 0 7.8999 0.275319 21.58826 20-06-2016 1208.59998 30.29993 30.29993 0 0.602983 37.61632 21-06-2016 1205.90002 -2.69996 0 2.69996 0.525797 34.4605 22-06-2016 1198.55005 -7.34997 0 7.34997 0.458534 31.43801 23-06-2016 1211.55005 13 13 0 0.51821 34.13295 24-06-2016 1194.5 -17.0501 0 17.05005 0.448538 30.96486 27-06-2016 1166.25 -28.25 0 28.25 0.393667 28.24682 28-06-2016 1161.05005 -5.19995 0 5.19995 0.433235 30.22778 29-06-2016 1176.55005 15.5 15.5 0 0.89335 47.18357 30-06-2016 1170.75 -5.80005 0 5.80005 0.881205 46.84258 01-07-2016 1172.09998 1.34998 1.34998 0 0.876477 46.70864 04-07-2016 1184.25 12.15002 12.15002 0 1.117153 52.76676 05-07-2016 1175.44995 -8.80005 0 8.80005 0.840209 45.65835 06-07-2016 1175.44995 0 0 0 0.87056 46.54007 07-07-2016 1157.19995 -18.25 0 18.25 0.774089 43.63304 08-07-2016 1158.75 1.55005 1.55005 0 0.466274 31.79994 11-07-2016 1174.84998 16.09998 16.09998 0 0.657662 39.67409 12-07-2016 1176 1.15002 1.15002 0 0.729454 42.17828 13-07-2016 1193.15002 17.15002 17.15002 0 0.779244 43.79636 14-07-2016 1175.84998 -17.3 0 17.30004 0.776914 43.72265 15-07-2016 1072.25 -103.6 0 103.6 0.408619 29.0085 18-07-2016 1081.69995 9.44995 9.44995 0 0.483902 32.61011 19-07-2016 1086.30005 4.6001 4.6001 0 0.413009 29.22902 20-07-2016 1083.05005 -3.25 0 3.25 0.419974 29.57618 21-07-2016 1080.34998 -2.70007 0 2.70007 0.403834 28.76652 22-07-2016 1072.65002 -7.69996 0 7.69996 0.309406 23.62952 25-07-2016 1080.5 7.84998 7.84998 0 0.3786 27.46264 26-07-2016 1088.80005 8.30005 8.30005 0 0.43292 30.21242 27-07-2016 1087.55005 -1.25 0 1.25 0.487114 32.75567 28-07-2016 1079.19995 -8.3501 0 8.3501 0.448145 30.94612
  • 40. 40 KLE’s Institute of Management Studies and Research, Hubli 29-07-2016 1073.94995 -5.25 0 5.25 0.324632 24.50735 01-08-2016 1085 11.05005 11.05005 0 0.390898 28.10398 02-08-2016 1084.30005 -0.69995 0 0.69995 0.274817 21.5574 03-08-2016 1085 0.69995 0 -0.69995 0.312264 23.79583 04-08-2016 1072.15002 -12.85 0 12.84998 0.997582 49.93948 05-08-2016 1067.40002 -4.75 0 4.75 0.689807 40.82165 08-08-2016 1078.80005 11.40003 11.40003 0 0.837311 45.57262 09-08-2016 1081.5 2.69995 2.69995 0 0.963826 49.079 10-08-2016 1079.94995 -1.55005 0 1.55005 0.990407 49.75902 11-08-2016 1077.09998 -2.84997 0 2.84997 1.120758 52.84706 12-08-2016 1063.30005 -13.7999 0 13.79993 0.660416 39.77412 15-08-2016 1063.30005 0 0 0 0.496545 33.17943 16-08-2016 1050.94995 -12.3501 0 12.3501 0.407287 28.94129 17-08-2016 1033.40002 -17.5499 0 17.54993 0.354476 26.17069 18-08-2016 1024.30005 -9.09997 0 9.09997 0.336231 25.16262 19-08-2016 1021.09998 -3.20007 0 3.20007 0.180769 15.30943 22-08-2016 1015.40002 -5.69996 0 5.69996 0.169879 14.52109 23-08-2016 1039.25 23.84998 23.84998 0 0.453405 31.19604 24-08-2016 1057.55005 18.30005 18.30005 0 0.793931 44.2565 25-08-2016 1036.55005 -21 0 21 0.64581 39.23963 26-08-2016 1020.75 -15.8001 0 15.80005 0.43586 30.35531 29-08-2016 1022.25 1.5 1.5 0 0.424198 29.78506 30-08-2016 1041 18.75 18.75 0 0.615689 38.10689 31-08-2016 1036.80005 -4.19995 0 4.19995 0.607595 37.7953 01-09-2016 1037.65002 0.84997 0 -0.84997 0.708688 41.47557 02-09-2016 1031.05005 -6.59997 0 6.59997 0.659271 39.73257 05-09-2016 1031.05005 0 0 0 0.758203 43.12374 06-09-2016 1045.09998 14.04993 14.04993 0 1.180694 54.14305 07-09-2016 1055 9.90002 9.90002 0 1.551661 60.80984 08-09-2016 1037.90002 -17.1 0 17.09998 1.241554 55.38808 09-09-2016 1036 -1.90002 0 1.90002 1.313308 56.77185 12-09-2016 1054 18 18 0 1.224335 55.04274 13-09-2016 1054 0 0 0 0.946007 48.61272 14-09-2016 1047.09998 -6.90002 0 6.90002 1.204258 54.63326 15-09-2016 1041.34998 -5.75 0 5.75 1.495192 59.92293 16-09-2016 1060.34998 19 19 0 1.915866 65.70487 19-09-2016 1061.15002 0.80004 0 -0.80004 1.493874 59.90174 20-09-2016 1050.34998 -10.8 0 10.80004 1.285863 56.25285 21-09-2016 1056.69995 6.34997 6.34997 0 1.394817 58.24316 22-09-2016 1058.5 1.80005 1.80005 0 1.659062 62.39276 23-09-2016 1043 -15.5 0 15.5 1.209098 54.73265 26-09-2016 1035.69995 -7.30005 0 7.30005 0.85415 46.06694 27-09-2016 1040.44995 4.75 4.75 0 0.774243 43.63794 28-09-2016 1038.59998 -1.84997 0 1.84997 1.014227 50.35316
  • 41. 41 KLE’s Institute of Management Studies and Research, Hubli 29-09-2016 1029.90002 -8.69996 0 8.69996 0.891072 47.11993 30-09-2016 1038.09998 8.19996 8.19996 0 0.716071 41.72736 03-10-2016 1037.84998 -0.25 0 0.25 0.712889 41.61908 04-10-2016 1048.80005 10.95007 10.95007 0 1.034449 50.84665 05-10-2016 1041.15002 -7.65003 0 7.65003 0.996098 49.90227 06-10-2016 1026.65002 -14.5 0 14.5 0.487453 32.77099 07-10-2016 1012.65002 -14 0 14 0.39789 28.46361 10-10-2016 1029.55005 16.90003 16.90003 0 0.701793 41.23845 11-10-2016 1029.55005 0 0 0 0.610754 37.91728 12-10-2016 1029.55005 0 0 0 0.584947 36.90641 13-10-2016 1052.05005 22.5 22.5 0 1.166821 53.84944 14-10-2016 1027.40002 -24.65 0 24.65003 0.884079 46.92367 17-10-2016 1022.04999 -5.35003 0 5.35003 0.760884 43.21035 18-10-2016 1038.19995 16.14996 16.14996 0 0.994673 49.86648 19-10-2016 1041.59998 3.40003 3.40003 0 1.176204 54.04843 20-10-2016 1036.94995 -4.65003 0 4.65003 0.983814 49.59204 21-10-2016 1038.09998 1.15003 1.15003 0 1.003531 50.08812 24-10-2016 1029 -9.09998 0 9.09998 0.75219 42.92856 25-10-2016 1017.34998 -11.65 0 11.65002 0.716329 41.73611 26-10-2016 1014.84998 -2.5 0 2.5 0.835883 45.53029 27-10-2016 1006.15002 -8.69996 0 8.69996 0.902402 47.43489 28-10-2016 997.45001 -8.70001 0 8.70001 0.573705 36.45569 31-10-2016 997.45001 0 0 0 0.573705 36.45569 01-11-2016 988.84998 -8.60003 0 8.60003 0.514898 33.98897 02-11-2016 981.09998 -7.75 0 7.75 0.225859 18.42457 03-11-2016 966.90002 -14.2 0 14.19996 0.254926 20.31405 04-11-2016 970.79999 3.89997 3.89997 0 0.324324 24.48979 07-11-2016 978.75 7.95001 7.95001 0 0.216217 17.77782 08-11-2016 982.79999 4.04999 4.04999 0 0.224786 18.35307 09-11-2016 955.84998 -26.95 0 26.95001 0.173714 14.80035 10-11-2016 938.59998 -17.25 0 17.25 0.137781 12.10966 11-11-2016 921.84998 -16.75 0 16.75 0.129216 11.44295 14-11-2016 921.84998 0 0 0 0.142729 12.49016 15-11-2016 924.75 2.90002 2.90002 0 0.172635 14.722 16-11-2016 940.09998 15.34998 15.34998 0 0.340818 25.41866 17-11-2016 929.54999 -10.55 0 10.54999 0.33464 25.07341 18-11-2016 919.79999 -9.75 0 9.75 0.305456 23.39841 21-11-2016 911.15002 -8.64997 0 8.64997 0.30532 23.39041 22-11-2016 913.95001 2.79999 2.79999 0 0.354947 26.19638 23-11-2016 920.5 6.54999 6.54999 0 0.483871 32.60868 24-11-2016 932.70001 12.20001 12.20001 0 0.576196 36.55611 25-11-2016 977.29999 44.59998 44.59998 0 0.983871 49.59349 28-11-2016 979.65002 2.35003 2.35003 0 0.964961 49.10841 29-11-2016 972.65002 -7 0 7 1.240172 55.36058
  • 42. 42 KLE’s Institute of Management Studies and Research, Hubli 30-11-2016 975.45001 2.79999 2.79999 0 1.699242 62.95256 01-12-2016 976.04999 0.59998 0 -0.59998 2.53324 71.69737 02-12-2016 964.09998 -11.95 0 11.95001 1.893235 65.43661 05-12-2016 961.40002 -2.69996 0 2.69996 1.733001 63.41019 06-12-2016 966.95001 5.54999 5.54999 0 1.537001 60.58338 07-12-2016 966.59998 -0.35003 0 0.35003 1.930905 65.88084 08-12-2016 984.75 18.15002 18.15002 0 3.161399 75.96962 09-12-2016 987.34998 2.59998 2.59998 0 4.560742 82.01679 12-12-2016 977.5 -9.84998 0 9.84998 3.0336 75.20825 13-12-2016 990.04999 12.54999 12.54999 0 3.2256 76.33472 14-12-2016 999.04999 9 9 0 3.123199 75.74699 15-12-2016 993.25 -5.79999 0 5.79999 1.4305 58.8562 16-12-2016 1004.20001 10.95001 10.95001 0 1.662618 62.44298 19-12-2016 1002.20001 -2 0 2 1.921997 65.77683 20-12-2016 1010.40002 8.20001 8.20001 0 2.090484 67.64261 21-12-2016 1003.70001 -6.70001 0 6.70001 1.702669 62.99954 22-12-2016 985.20001 -18.5 0 18.5 1.459696 59.34457 23-12-2016 989.29999 4.09998 4.09998 0 1.645832 62.20471 26-12-2016 983 -6.29999 0 6.29999 1.324242 56.97522 27-12-2016 999.25 16.25 16.25 0 1.664294 62.4666 28-12-2016 999.15002 -0.09998 0 0.09998 1.292386 56.37734 29-12-2016 994.09998 -5.05004 0 5.05004 1.124309 52.92588 30-12-2016 1010.70001 16.60003 16.60003 0 1.746907 63.59541 02-01-2017 1001.59998 -9.10003 0 9.10003 1.215686 54.86725 03-01-2017 994.65002 -6.94996 0 6.94996 0.927273 48.11322 04-01-2017 998.29999 3.64997 3.64997 0 1.092322 52.2062 05-01-2017 996.40002 -1.89997 0 1.89997 0.862191 46.29981 06-01-2017 971.45001 -24.95 0 24.95001 0.613451 38.02103 09-01-2017 970.54999 -0.90002 0 0.90002 0.504661 33.53985 10-01-2017 970.59998 0.04999 0 -0.04999 0.550882 35.52055 11-01-2017 969 -1.59998 0 1.59998 0.714789 41.68377 12-01-2017 1000.04999 31.04999 31.04999 0 1.189261 54.32248 13-01-2017 975.15002 -24.9 0 24.89997 0.895889 47.25429 16-01-2017 955.70001 -19.45 0 19.45001 0.540854 35.10092 17-01-2017 956.04999 0.34998 0 -0.34998 0.543432 35.20932 18-01-2017 950.90002 -5.14997 0 5.14997 0.542857 35.18519 19-01-2017 958.54999 7.64997 7.64997 0 0.448148 30.94627 20-01-2017 948.79999 -9.75 0 9.75 0.445086 30.79998 23-01-2017 951.75 2.95001 2.95001 0 0.513605 33.93256 24-01-2017 945.09998 -6.65002 0 6.65002 0.439114 30.51281 25-01-2017 936.65002 -8.44996 0 8.44996 0.410749 29.11569 26-01-2017 936.65002 0 0 0 0.5448 35.26672 27-01-2017 942.15002 5.5 5.5 0 0.62409 38.42706 30-01-2017 948.34998 6.19996 6.19996 0 0.705688 41.37262
  • 43. 43 KLE’s Institute of Management Studies and Research, Hubli 31-01-2017 929.29999 -19.05 0 19.04999 0.573347 36.44124 01-02-2017 916.54999 -12.75 0 12.75 0.210775 17.40824 02-02-2017 935.34998 18.79999 18.79999 0 0.508034 33.68849 03-02-2017 934.95001 -0.39997 0 0.39997 0.664511 39.92228 06-02-2017 934.45001 -0.5 0 0.5 0.655502 39.59537 07-02-2017 944.75 10.29999 10.29999 0 0.893136 47.17759 08-02-2017 936.45001 -8.29999 0 8.29999 0.664389 39.91788 09-02-2017 948.09998 11.64997 11.64997 0 0.987522 49.68609 10-02-2017 968.04999 19.95001 19.95001 0 1.290553 56.34242 13-02-2017 983.5 15.45001 15.45001 0 1.776544 63.984 14-02-2017 987.29999 3.79999 3.79999 0 2.235367 69.0916 15-02-2017 982.34998 -4.95001 0 4.95001 1.994559 66.6061 16-02-2017 1011.90002 29.55004 29.55004 0 2.517956 71.5744 17-02-2017 999.70001 -12.2 0 12.20001 1.883062 65.31466 20-02-2017 1011.70001 12 12 0 3.107418 75.65381 21-02-2017 1012.95001 1.25 1.25 0 4.658448 82.32731 22-02-2017 991.84998 -21.1 0 21.10003 2.190727 68.65918 23-02-2017 1009.04999 17.20001 17.20001 0 2.574919 72.02733 24-02-2017 1009.04999 0 0 0 2.602576 72.24209 27-02-2017 1012.75 3.70001 3.70001 0 2.460794 71.10489 28-02-2017 1012.29999 -0.45001 0 0.45001 2.959945 74.74712 01-03-2017 1025 12.70001 12.70001 0 2.987078 74.91897 02-03-2017 1020.65002 -4.34998 0 4.34998 2.221835 68.96178 03-03-2017 1031.15002 10.5 10.5 0 2.106852 67.81308 06-03-2017 1033.84998 2.69996 2.69996 0 2.0813 67.54616 07-03-2017 1019.70001 -14.15 0 14.14997 1.714833 63.16532 08-03-2017 1007.25 -12.45 0 12.45001 0.92813 48.13626 09-03-2017 1011.59998 4.34998 4.34998 0 1.226666 55.08981 10-03-2017 1020.09998 8.5 8.5 0 1.159999 53.70369 13-03-2017 1020.09998 0 0 0 1.13619 53.18768 14-03-2017 1032.5 12.40002 12.40002 0 2.294588 69.64719 15-03-2017 1012.09998 -20.4 0 20.40002 1.05888 51.42991 16-03-2017 1028.5 16.40002 16.40002 0 1.375483 57.9033 17-03-2017 1040 11.5 11.5 0 1.526062 60.41269 20-03-2017 1020.59998 -19.4 0 19.40002 1.117314 52.77036 21-03-2017 1032 11.40002 11.40002 0 1.09894 52.3569 22-03-2017 1027.80005 -4.19995 0 4.19995 1.101275 52.40985 23-03-2017 1040.59998 12.79993 12.79993 0 1.133852 53.1364 24-03-2017 1031.80005 -8.79993 0 8.79993 0.974182 49.34611 27-03-2017 1028.80005 -3 0 3 1.133334 53.12502 28-03-2017 1035.09998 6.29993 6.29993 0 1.499104 59.98566 29-03-2017 1031.34998 -3.75 0 3.75 1.331655 57.112 30-03-2017 1024.5 -6.84998 0 6.84998 1.066265 51.60351 31-03-2017 1020.79999 -3.70001 0 3.70001 1.009986 50.24841
  • 44. 44 KLE’s Institute of Management Studies and Research, Hubli Interpretation In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the line crosses below 30 it shows buy signal. In months of December 2016 and March 2017the RSI crosses above 70 so it is the time to sell. And in month of August, November and February 2017 was right time to buy as RSI crossed below 30. Wipro ( Relative Strength Index):
  • 45. 45 KLE’s Institute of Management Studies and Research, Hubli Date Wipro closing Change Gain Loss RS Value RSI 01-04-2016 562.15002 04-04-2016 566.25 4.09998 4.09998 0 05-04-2016 559 -7.25 0 7.25 06-04-2016 558.20001 -0.79999 0 0.79999 07-04-2016 551.79999 -6.40002 0 6.40002 08-04-2016 549.54999 -2.25 0 2.25 11-04-2016 565.75 16.20001 16.20001 0 12-04-2016 569.54999 3.79999 3.79999 0 13-04-2016 584.90002 15.35003 15.35003 0 14-04-2016 584.90002 0 0 0 15-04-2016 584.90002 0 0 0 18-04-2016 588.59998 3.69996 3.69996 0 19-04-2016 588.59998 0 0 0 20-04-2016 601.25 12.65002 12.65002 0 21-04-2016 558.84998 -42.4 0 42.40002 0.944162 48.56395 22-04-2016 557.95001 -0.89997 0 0.89997 0.861667 46.2847 25-04-2016 552.45001 -5.5 0 5.5 0.887554 47.02138 26-04-2016 554.45001 2 2 0 0.934726 48.31309 27-04-2016 560 5.54999 5.54999 0 1.160627 53.71714 28-04-2016 553.09998 -6.90002 0 6.90002 1.063734 51.54415 29-04-2016 554.34998 1.25 1.25 0 0.795332 44.29999 02-05-2016 548.5 -5.84998 0 5.84998 0.658002 39.68643 03-05-2016 543.84998 -4.65002 0 4.65002 0.379909 27.53145 04-05-2016 540 -3.84998 0 3.84998 0.359029 26.41805 05-05-2016 543.09998 3.09998 3.09998 0 0.403283 28.73852 06-05-2016 533.09998 -10 0 10 0.306683 23.47036 09-05-2016 539 5.90002 5.90002 0 0.380387 27.55657 10-05-2016 538.65002 -0.34998 0 0.34998 0.221393 18.12627 11-05-2016 537.79999 -0.85003 0 0.85003 0.458172 31.42101 12-05-2016 542.29999 4.5 4.5 0 0.587615 37.01243 13-05-2016 539.65002 -2.64997 0 2.64997 0.635328 38.85018 16-05-2016 540.79999 1.14997 1.14997 0 0.61111 37.931 17-05-2016 540.15002 -0.64997 0 0.64997 0.444755 30.78411 18-05-2016 539.54999 -0.60003 0 0.60003 0.539898 35.06063 19-05-2016 542.95001 3.40002 3.40002 0 0.612904 38.00002 20-05-2016 543.40002 0.45001 0 -0.45001 0.779698 43.8107 23-05-2016 539.84998 -3.55004 0 3.55004 0.818594 45.01247 24-05-2016 537.65002 -2.19996 0 2.19996 0.884805 46.94411 25-05-2016 546.09998 8.44996 8.44996 0 1.147059 53.42466 26-05-2016 544.95001 -1.14997 0 1.14997 2.025982 66.95288 27-05-2016 545.40002 0.45001 0 -0.45001 1.576582 61.18889 30-05-2016 550.15002 4.75 4.75 0 2.069772 67.4243
  • 46. 46 KLE’s Institute of Management Studies and Research, Hubli 31-05-2016 545.45001 -4.70001 0 4.70001 1.523976 60.37998 01-06-2016 554.5 9.04999 9.04999 0 1.835621 64.73436 02-06-2016 540.40002 -14.1 0 14.09998 1.028791 50.70956 03-06-2016 540.79999 0.39997 0 -0.39997 1 50 06-06-2016 535.09998 -5.70001 0 5.70001 0.835504 45.51904 07-06-2016 539.84998 4.75 4.75 0 1.009966 50.24793 08-06-2016 544.59998 4.75 4.75 0 1.054816 51.33385 09-06-2016 544.79999 0.20001 0 -0.20001 1.046128 51.12719 10-06-2016 545.34998 0.54999 0 -0.54999 1.209524 54.74139 13-06-2016 541.20001 -4.14997 0 4.14997 1.125886 52.9608 14-06-2016 543.09998 1.89997 1.89997 0 0.893617 47.19101 15-06-2016 547.04999 3.95001 3.95001 0 1.077633 51.86831 16-06-2016 549.90002 2.85003 2.85003 0 1.163636 53.78151 17-06-2016 552.04999 2.14997 2.14997 0 1.06909 51.66957 20-06-2016 557.04999 5 5 0 1.508771 60.13985 21-06-2016 561 3.95001 3.95001 0 1.285088 56.23801 22-06-2016 563.15002 2.15002 2.15002 0 3.61494 78.33124 23-06-2016 563.70001 0.54999 0 -0.54999 3.678368 78.62503 24-06-2016 555.15002 -8.54999 0 8.54999 2.75878 73.39562 27-06-2016 548 -7.15002 0 7.15002 1.439354 59.00555 28-06-2016 542.40002 -5.59998 0 5.59998 0.908904 47.61393 29-06-2016 554.54999 12.14997 12.14997 0 1.400411 58.34047 30-06-2016 557.95001 3.40002 3.40002 0 1.506026 60.09618 01-07-2016 558.90002 0.95001 0 -0.95001 1.89394 65.44504 04-07-2016 561.70001 2.79999 2.79999 0 1.939396 65.9794 05-07-2016 564.95001 3.25 3.25 0 1.904042 65.56523 06-07-2016 564.95001 0 0 0 1.760101 63.76944 07-07-2016 559.59998 -5.35003 0 5.35003 1.300198 56.52548 08-07-2016 561.65002 2.05004 2.05004 0 1.182904 54.18946 11-07-2016 568.84998 7.19996 7.19996 0 1.312126 56.74977 12-07-2016 570.79999 1.95001 1.95001 0 1.304174 56.60049 13-07-2016 573.95001 3.15002 3.15002 0 1.398833 58.31305 14-07-2016 570.59998 -3.35003 0 3.35003 1.753655 63.68463 15-07-2016 554.5 -16.1 0 16.09998 1.220713 54.96942 18-07-2016 551.95001 -2.54999 0 2.54999 1.361742 57.65837 19-07-2016 549.25 -2.70001 0 2.70001 0.81787 44.99056 20-07-2016 538.84998 -10.4 0 10.40002 0.516456 34.05675 21-07-2016 542 3.15002 3.15002 0 0.5822 36.79688 22-07-2016 537.75 -4.25 0 4.25 0.464206 31.70361 25-07-2016 542.84998 5.09998 5.09998 0 0.505593 33.58098 26-07-2016 546.09998 3.25 3.25 0 0.5783 36.64068 27-07-2016 549.15002 3.05004 3.05004 0 0.734436 42.34436 28-07-2016 553.79999 4.64997 4.64997 0 0.800508 44.46011 29-07-2016 545.04999 -8.75 0 8.75 0.505198 33.56356
  • 47. 47 KLE’s Institute of Management Studies and Research, Hubli 01-08-2016 557.70001 12.65002 12.65002 0 0.727651 42.11795 02-08-2016 549.59998 -8.10003 0 8.10003 0.566726 36.17263 03-08-2016 547.95001 -1.64997 0 1.64997 0.584404 36.88479 04-08-2016 548.20001 0.25 0 -0.25 0.834863 45.50001 05-08-2016 547.20001 -1 0 1 0.870219 46.53032 08-08-2016 549 1.79999 1.79999 0 0.992625 49.81495 09-08-2016 551.34998 2.34998 2.34998 0 1.531915 60.5042 10-08-2016 542.65002 -8.69996 0 8.69996 1.020187 50.49963 11-08-2016 543 0.34998 0 -0.34998 1.190218 54.34243 12-08-2016 543.75 0.75 0 -0.75 1.03352 50.82419 15-08-2016 543.75 0 0 0 0.912477 47.7118 16-08-2016 536.5 -7.25 0 7.25 0.629031 38.61383 17-08-2016 527.79999 -8.70001 0 8.70001 0.392523 28.18791 18-08-2016 525.09998 -2.70001 0 2.70001 0.457143 31.37254 19-08-2016 520.09998 -5 0 5 0.0994 9.041335 22-08-2016 515.5 -4.59998 0 4.59998 0.108496 9.787684 23-08-2016 519.59998 4.09998 4.09998 0 0.225409 18.39457 24-08-2016 519.65002 0.05004 0 -0.05004 0.224184 18.31292 25-08-2016 504 -15.65 0 15.65002 0.160349 13.81903 26-08-2016 490 -14 0 14 0.098548 8.970747 29-08-2016 478.79999 -11.2 0 11.20001 0.05349 5.077378 30-08-2016 489.45001 10.65002 10.65002 0 0.217071 17.83555 31-08-2016 491.64999 2.19998 2.19998 0 0.24817 19.88268 01-09-2016 483.95001 -7.69998 0 7.69998 0.220847 18.08964 02-09-2016 483.60001 -0.35 0 0.35 0.219844 18.02232 05-09-2016 483.60001 0 0 0 0.242663 19.52764 06-09-2016 482.89999 -0.70002 0 0.70002 0.27405 21.51014 07-09-2016 481.75 -1.14999 0 1.14999 0.281094 21.94174 08-09-2016 473.95001 -7.79999 0 7.79999 0.268621 21.17426 09-09-2016 480.64999 6.69998 6.69998 0 0.404273 28.78878 12-09-2016 480.39999 -0.25 0 0.25 0.332766 24.96806 13-09-2016 480.39999 0 0 0 0.332483 24.95212 14-09-2016 478.04999 -2.35 0 2.35 0.42967 30.05379 15-09-2016 478.45001 0.40002 0 -0.40002 0.628617 38.59822 16-09-2016 479.39999 0.94998 0 -0.94998 1.031662 50.77922 19-09-2016 479.95001 0.55002 0 -0.55002 0.483695 32.60068 20-09-2016 481.04999 1.09998 1.09998 0 0.423912 29.77093 21-09-2016 483.85001 2.80002 2.80002 0 0.990654 49.76526 22-09-2016 481.75 -2.10001 0 2.10001 0.851405 45.98696 23-09-2016 480.20001 -1.54999 0 1.54999 0.757143 43.08942 26-09-2016 479.29999 -0.90002 0 0.90002 0.746479 42.74192 27-09-2016 484.20001 4.90002 4.90002 0 1.18774 54.29074 28-09-2016 483.70001 -0.5 0 0.5 2.695652 72.94118 29-09-2016 472.20001 -11.5 0 11.5 0.510146 33.78124
  • 48. 48 KLE’s Institute of Management Studies and Research, Hubli 30-09-2016 478.95001 6.75 6.75 0 0.914707 47.77269 03-10-2016 478.95001 0 0 0 0.914707 47.77269 04-10-2016 481.79999 2.84998 2.84998 0 1.255973 55.67322 05-10-2016 479.54999 -2.25 0 2.25 1.063583 51.54059 06-10-2016 478 -1.54999 0 1.54999 0.929293 48.16755 07-10-2016 476.95001 -1.04999 0 1.04999 0.859813 46.23116 10-10-2016 477 0.04999 0 -0.04999 0.810305 44.76069 11-10-2016 477 0 0 0 0.679157 40.44629 12-10-2016 477 0 0 0 0.753247 42.96296 13-10-2016 478.25 1.25 1.25 0 0.88983 47.08519 14-10-2016 475 -3.25 0 3.25 0.785537 43.99443 17-10-2016 472.14999 -2.85001 0 2.85001 0.473798 32.14811 18-10-2016 482.75 10.60001 10.60001 0 0.957589 48.91675 19-10-2016 495 12.25 12.25 0 3.091742 75.56053 20-10-2016 495.39999 0.39999 0 -0.39999 2.566663 71.96259 21-10-2016 499.20001 3.80002 3.80002 0 2.92857 74.54544 24-10-2016 483.95001 -15.25 0 15.25 1.083496 52.00375 25-10-2016 481.39999 -2.55002 0 2.55002 1.071017 51.71455 26-10-2016 471.54999 -9.85 0 9.85 0.812227 44.81927 27-10-2016 461.70001 -9.84998 0 9.84998 0.646582 39.26813 28-10-2016 462.10001 0.4 0 -0.4 0.65187 39.46253 31-10-2016 462.10001 0 0 0 0.65187 39.46253 01-11-2016 460.75 -1.35001 0 1.35001 0.631937 38.72312 02-11-2016 457.89999 -2.85001 0 2.85001 0.567021 36.18466 03-11-2016 447.60001 -10.3 0 10.29998 0.493062 33.02356 04-11-2016 452.5 4.89999 4.89999 0 0.616211 38.1269 07-11-2016 450 -2.5 0 2.5 0.39013 28.06431 08-11-2016 451.75 1.75 1.75 0 0.1946 16.28996 09-11-2016 446.89999 -4.85001 0 4.85001 0.177269 15.05765 10-11-2016 444.95001 -1.94998 0 1.94998 0.109195 9.844548 11-11-2016 442.35001 -2.6 0 2.6 0.137824 12.11292 14-11-2016 442.35001 0 0 0 0.145514 12.70295 15-11-2016 447.95001 5.6 5.6 0 0.341702 25.46778 16-11-2016 445.29999 -2.65002 0 2.65002 0.427574 29.95108 17-11-2016 438.39999 -6.9 0 6.9 0.340751 25.41492 18-11-2016 437.14999 -1.25 0 1.25 0.329301 24.77248 21-11-2016 441.79999 4.65 4.65 0 0.471408 32.0379 22-11-2016 450.39999 8.6 8.6 0 0.772727 43.58974 23-11-2016 448.89999 -1.5 0 1.5 1.053718 51.30783 24-11-2016 450.75 1.85001 1.85001 0 0.927686 48.12433 25-11-2016 464.75 14 14 0 1.679723 62.68271 28-11-2016 460.60001 -4.14999 0 4.14999 1.34236 57.30802 29-11-2016 465.14999 4.54998 4.54998 0 1.869048 65.14523 30-11-2016 465.25 0.10001 0 -0.10001 2.07124 67.43986
  • 49. 49 KLE’s Institute of Management Studies and Research, Hubli 01-12-2016 468.29999 3.04999 3.04999 0 2.587155 72.12275 02-12-2016 460.39999 -7.9 0 7.9 1.744329 63.56122 05-12-2016 456.64999 -3.75 0 3.75 1.310714 56.72333 06-12-2016 457.79999 1.15 1.15 0 1.493097 59.88925 07-12-2016 453.35001 -4.44998 0 4.44998 1.65284 62.30456 08-12-2016 458.60001 5.25 5.25 0 1.990765 66.56374 09-12-2016 458.10001 -0.5 0 0.5 1.735894 63.44887 12-12-2016 453.54999 -4.55002 0 4.55002 1.117978 52.78515 13-12-2016 463.75 10.20001 10.20001 0 1.589287 61.37932 14-12-2016 466.29999 2.54999 2.54999 0 1.617064 61.78924 15-12-2016 466.10001 -0.19998 0 0.19998 1.05315 51.29435 16-12-2016 463.5 -2.60001 0 2.60001 1.121593 52.86561 19-12-2016 463.54999 0.04999 0 -0.04999 0.932773 48.26087 20-12-2016 466.64999 3.1 3.1 0 1.058577 51.42275 21-12-2016 462.45001 -4.19998 0 4.19998 0.791816 44.19068 22-12-2016 461.70001 -0.75 0 0.75 1.062054 51.50465 23-12-2016 458.75 -2.95001 0 2.95001 1.104219 52.47643 26-12-2016 456.10001 -2.64999 0 2.64999 0.925439 48.0638 27-12-2016 465.20001 9.1 9.1 0 1.645777 62.20391 28-12-2016 469.35001 4.15 4.15 0 1.585831 61.32771 29-12-2016 472.35001 3 3 0 1.798319 64.26426 30-12-2016 474.45001 2.1 2.1 0 2.571432 72.00003 02-01-2017 471.54999 -2.90002 0 2.90002 1.481481 59.70148 03-01-2017 467 -4.54999 0 4.54999 1.033735 50.8294 04-01-2017 475.60001 8.60001 8.60001 0 1.462287 59.38735 05-01-2017 480.39999 4.79998 4.79998 0 1.941504 66.00378 06-01-2017 469.95001 -10.45 0 10.44998 1.224957 55.05531 09-01-2017 472 2.04999 2.04999 0 1.18805 54.2972 10-01-2017 476.5 4.5 4.5 0 1.579381 61.23101 11-01-2017 476.20001 -0.29999 0 0.29999 1.609244 61.67473 12-01-2017 483.20001 7 7 0 2.172664 68.48075 13-01-2017 484.64999 1.44998 1.44998 0 2.568682 71.97845 16-01-2017 484.75 0.10001 0 -0.10001 2.080112 67.53365 17-01-2017 482.39999 -2.35001 0 2.35001 1.638141 62.09453 18-01-2017 482.95001 0.55002 0 -0.55002 1.532664 60.51589 19-01-2017 479 -3.95001 0 3.95001 1.190776 54.35406 20-01-2017 477.89999 -1.10001 0 1.10001 1.287982 56.29337 23-01-2017 479.75 1.85001 1.85001 0 1.728573 63.3508 24-01-2017 481.5 1.75 1.75 0 1.337143 57.21271 25-01-2017 473.70001 -7.79999 0 7.79999 0.735178 42.36903 26-01-2017 473.70001 0 0 0 1.252526 55.60539 27-01-2017 465.54999 -8.15002 0 8.15002 0.719565 41.84575 30-01-2017 465.75 0.20001 0 -0.20001 0.528509 34.57675 31-01-2017 458 -7.75 0 7.75 0.398347 28.48698
  • 50. 50 KLE’s Institute of Management Studies and Research, Hubli 01-02-2017 456 -2 0 2 0.156589 13.53885 02-02-2017 455.64999 -0.35001 0 0.35001 0.11043 9.944774 03-02-2017 457.75 2.10001 2.10001 0 0.174312 14.84379 06-02-2017 461.10001 3.35001 3.35001 0 0.298189 22.9696 07-02-2017 458.54999 -2.55002 0 2.55002 0.270554 21.29415 08-02-2017 460.5 1.95001 1.95001 0 0.372882 27.16054 09-02-2017 466 5.5 5.5 0 0.580987 36.74836 10-02-2017 469.25 3.25 3.25 0 0.630282 38.66092 13-02-2017 474.45001 5.20001 5.20001 0 0.751761 42.91459 14-02-2017 476.70001 2.25 2.25 0 1.145631 53.39366 15-02-2017 474.70001 -2 0 2 1.044248 51.08225 16-02-2017 480.79999 6.09998 6.09998 0 2.055362 67.27065 17-02-2017 475.35001 -5.44998 0 5.44998 1.477612 59.63856 20-02-2017 475.64999 0.29998 0 -0.29998 2.464726 71.13769 21-02-2017 475.79999 0.15 0 -0.15 2.999993 74.99996 22-02-2017 474.5 -1.29999 0 1.29999 2.737327 73.24291 23-02-2017 486.10001 11.60001 11.60001 0 3.612902 78.32167 24-02-2017 486.10001 0 0 0 3.304145 76.76658 27-02-2017 489.75 3.64999 3.64999 0 4.759042 82.636 28-02-2017 488.79999 -0.95001 0 0.95001 4.059458 80.23504 01-03-2017 488.54999 -0.25 0 0.25 3.373683 77.13598 02-03-2017 490.20001 1.65002 1.65002 0 3.205264 76.22028 03-03-2017 493.85001 3.65 3.65 0 3.042105 75.26042 06-03-2017 491.89999 -1.95002 0 1.95002 2.327507 69.94747 07-03-2017 495.14999 3.25 3.25 0 3.164014 75.98471 08-03-2017 495.10001 -0.04998 0 0.04998 2.505265 71.47149 09-03-2017 484.5 -10.6 0 10.60001 1.624571 61.89854 10-03-2017 487.04999 2.54999 2.54999 0 1.762541 63.80145 13-03-2017 487.04999 0 0 0 1.745033 63.57056 14-03-2017 501.35001 14.30002 14.30002 0 2.94565 74.65563 15-03-2017 494.79999 -6.55002 0 6.55002 1.427517 58.80564 16-03-2017 500.54999 5.75 5.75 0 1.710071 63.1006 17-03-2017 504.25 3.70001 3.70001 0 1.712529 63.13404 20-03-2017 497.5 -6.75 0 6.75 1.332696 57.13115 21-03-2017 498.64999 1.14999 1.14999 0 1.389961 58.15831 22-03-2017 500.54999 1.9 1.9 0 1.399613 58.32661 23-03-2017 510 9.45001 9.45001 0 1.623551 61.88372 24-03-2017 513.25 3.25 3.25 0 1.891441 65.41516 27-03-2017 504 -9.25 0 9.25 1.266566 55.8804 28-03-2017 507.54999 3.54999 3.54999 0 1.375565 57.90475 29-03-2017 512.25 4.70001 4.70001 0 2.230598 69.04597 30-03-2017 515.95001 3.70001 3.70001 0 2.281596 69.52702 31-03-2017 515.70001 -0.25 0 0.25 2.256579 69.29293
  • 51. 51 KLE’s Institute of Management Studies and Research, Hubli Interpretation In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the line crosses below 30 it shows buy signal. In months of June, October 2016 And March 2016 the RSI crosses above 70 so it is the time to sell. And in the month of May, September ,November 2016 and February 2017 was right time to buy as RSI has crossed below 30. MINDTREE ( Relative Strength Index):
  • 52. 52 KLE’s Institute of Management Studies and Research, Hubli Date Mind tree closing Change Gain Loss RS Value RSI 01-04-2016 668.15 04-04-2016 676.05 7.9 7.9 0 05-04-2016 658.35 -17.7 0 17.7 06-04-2016 667.9 9.55 9.55 0 07-04-2016 671.65 3.75 3.75 0 08-04-2016 667.5 -4.15 0 4.15 11-04-2016 667.7 0.2 0 -0.2 12-04-2016 677 9.3 9.3 0 13-04-2016 691.6 14.6 14.6 0 14-04-2016 691.6 0 0 0 15-04-2016 691.6 0 0 0 18-04-2016 730.8 39.2 39.2 0 19-04-2016 730.8 0 0 0 20-04-2016 723.95 -6.85 0 6.85 21-04-2016 715.8 -8.15 0 8.15 2.300136 69.69822 22-04-2016 708.3 -7.5 0 7.5 1.730464 63.37619 25-04-2016 698.5 -9.8 0 9.8 2.107586 67.82068 26-04-2016 707.35 8.85 8.85 0 2.088276 67.61947 27-04-2016 699.7 -7.65 0 7.65 1.638952 62.10617 28-04-2016 686.2 -13.5 0 13.5 1.351174 57.46805 29-04-2016 678.8 -7.4 0 7.4 1.182416 54.17922 02-05-2016 681.85 3.05 3.05 0 1.079704 51.91624 03-05-2016 670.25 -11.6 0 11.6 0.705314 41.35977 04-05-2016 661.45 -8.8 0 8.8 0.628923 38.60975 05-05-2016 664 2.55 2.55 0 0.660308 39.7702 06-05-2016 659 -5 0 5 0.167536 14.34955 09-05-2016 657.15 -1.85 0 1.85 0.164018 14.09069 10-05-2016 645.85 -11.3 0 11.3 0.156132 13.50467 11-05-2016 652.35 6.5 6.5 0 0.248223 19.88609 12-05-2016 660.25 7.9 7.9 0 0.375163 27.28132 13-05-2016 652.9 -7.35 0 7.35 0.387508 27.92836 16-05-2016 645.3 -7.6 0 7.6 0.243754 19.59824 17-05-2016 645.5 0.2 0.2 0 0.271505 21.35307 18-05-2016 644 -1.5 0 1.5 0.323718 24.45521 19-05-2016 644 0 0 0 0.367273 26.8617 20-05-2016 630.45 -13.55 0 13.55 0.250182 20.01167 23-05-2016 640.85 10.4 10.4 0 0.483758 32.60355 24-05-2016 647.75 6.9 6.9 0 0.715472 41.70702 25-05-2016 648.75 1 1 0 0.683281 40.59223 26-05-2016 665.35 16.6 16.6 0 1.147161 53.42688 27-05-2016 667.6 2.25 2.25 0 1.253027 55.61526 30-05-2016 671.7 4.1 4.1 0 1.861667 65.05533 31-05-2016 660.9 -10.8 0 10.8 1.209559 54.7421
  • 53. 53 KLE’s Institute of Management Studies and Research, Hubli 01-06-2016 654.8 -6.1 0 6.1 0.883795 46.91568 02-06-2016 653.6 -1.2 0 1.2 1.017178 50.42579 03-06-2016 647.45 -6.15 0 6.15 1.054707 51.33127 06-06-2016 644.55 -2.9 0 2.9 0.977488 49.4308 07-06-2016 650.3 5.75 5.75 0 1.154791 53.59179 08-06-2016 650.7 0.4 0 -0.4 1.166253 53.83734 09-06-2016 639.2 -11.5 0 11.5 1.228758 55.13196 10-06-2016 639.35 0.15 0 -0.15 0.96063 48.99598 13-06-2016 635.15 -4.2 0 4.2 0.702128 41.25 14-06-2016 643.95 8.8 8.8 0 0.886525 46.99248 15-06-2016 640.05 -3.9 0 3.9 0.452381 31.14754 16-06-2016 630.05 -10 0 10 0.331851 24.9165 17-06-2016 630 -0.05 0 0.05 0.258667 20.55085 20-06-2016 639.8 9.8 9.8 0 0.535754 34.88539 21-06-2016 657.7 17.9 17.9 0 1.073698 51.77696 22-06-2016 653.6 -4.1 0 4.1 1 50 23-06-2016 659.95 6.35 6.35 0 1.34626 57.37898 24-06-2016 659.9 -0.05 0 0.05 1.461654 59.37691 27-06-2016 651.85 -8.05 0 8.05 1.03753 50.92097 28-06-2016 662.8 10.95 10.95 0 1.290168 56.33508 29-06-2016 663.4 0.6 0.6 -0.6 1.837838 64.7619 30-06-2016 664.85 1.45 1.45 0 1.877311 65.24533 01-07-2016 673.9 9.05 9.05 0 2.540117 71.75235 04-07-2016 672.15 -1.75 0 1.75 2.054945 67.26619 05-07-2016 678.3 6.15 6.15 0 2.660256 72.67951 06-07-2016 678.3 0 0 0 4.645522 82.28685 07-07-2016 659.35 -18.95 0 18.95 1.927245 65.83818 08-07-2016 654.4 -4.95 0 4.95 1.408054 58.47269 11-07-2016 665.55 11.15 11.15 0 1.226846 55.09343 12-07-2016 661.05 -4.5 0 4.5 1.213811 54.82903 13-07-2016 650.45 -10.6 0 10.6 0.815544 44.92009 14-07-2016 653.3 2.85 2.85 0 0.875519 46.68142 15-07-2016 637.25 -16.05 0 16.05 0.75089 42.88618 18-07-2016 614.2 -23.05 0 23.05 0.394322 28.28054 19-07-2016 561.55 -52.65 0 52.65 0.231321 18.78639 20-07-2016 570.4 8.85 8.85 0 0.28717 22.31017 21-07-2016 565.95 -4.45 0 4.45 0.211756 17.47514 22-07-2016 556.9 -9.05 0 9.05 0.20104 16.73882 25-07-2016 551.75 -5.15 0 5.15 0.152945 13.2656 26-07-2016 565 13.25 13.25 0 0.241633 19.46092 27-07-2016 565.1 0.1 0.1 -0.1 0.277714 21.73521 28-07-2016 582.3 17.2 17.2 0 0.425837 29.86577 29-07-2016 578.65 -3.65 0 3.65 0.327392 24.66433 01-08-2016 601.6 22.95 22.95 0 0.523485 34.361
  • 54. 54 KLE’s Institute of Management Studies and Research, Hubli 02-08-2016 612.95 11.35 11.35 0 0.671786 40.18373 03-08-2016 600.1 -12.85 0 12.85 0.58123 36.7581 04-08-2016 604.85 4.75 4.75 0 0.708352 41.46406 05-08-2016 613 8.15 8.15 0 0.987457 49.68445 08-08-2016 617.8 4.8 4.8 0 2.607703 72.28153 09-08-2016 596.55 -21.25 0 21.25 1.466252 59.45265 10-08-2016 572.3 -24.25 0 24.25 1.084757 52.03278 11-08-2016 580.7 8.4 8.4 0 1.35645 57.56329 12-08-2016 579.8 -0.9 0 0.9 1.448248 59.15447 15-08-2016 579.8 0 0 0 1.237261 55.30249 16-08-2016 569.15 -10.65 0 10.65 1.055065 51.33973 17-08-2016 566.35 -2.8 0 2.8 0.791094 44.16819 18-08-2016 564.75 -1.6 0 1.6 0.812921 44.84039 19-08-2016 565.7 0.95 0.95 -0.95 0.523517 34.36242 22-08-2016 551.25 -14.45 0 14.45 0.308087 23.55246 23-08-2016 566.2 14.95 14.95 0 0.560374 35.91278 24-08-2016 568.6 2.4 2.4 0 0.529019 34.5986 25-08-2016 567.8 -0.8 0 0.8 0.415842 29.37063 26-08-2016 569.25 1.45 1.45 0 0.371617 27.09336 29-08-2016 564.95 -4.3 0 4.3 0.478741 32.37493 30-08-2016 570.15 5.2 5.2 0 0.965268 49.11635 31-08-2016 562.55 -7.6 0 7.6 0.591934 37.18331 01-09-2016 553.75 -8.8 0 8.8 0.498501 33.26667 02-09-2016 548.85 -4.9 0 4.9 0.454049 31.22653 05-09-2016 548.85 0 0 0 0.563205 36.02888 06-09-2016 525 -23.85 0 23.85 0.38179 27.63012 07-09-2016 518.9 -6.1 0 6.1 0.357194 26.31857 08-09-2016 515.3 -3.6 0 3.6 0.322581 24.39024 09-09-2016 522.8 7.5 7.5 0 0.525438 34.44505 12-09-2016 516.5 -6.3 0 6.3 0.249811 19.98792 13-09-2016 516.5 0 0 0 0.213585 17.5995 14-09-2016 513.5 -3 0 3 0.20672 17.13075 15-09-2016 514 0.5 0.5 -0.5 0.19426 16.26617 16-09-2016 512.2 -1.8 0 1.8 0.201681 16.78322 19-09-2016 505.25 -6.95 0 6.95 0.110497 9.950249 20-09-2016 502.1 -3.15 0 3.15 0.117734 10.53325 21-09-2016 510.25 8.15 8.15 0 0.273035 21.44754 22-09-2016 509.75 -0.5 0 0.5 0.294977 22.77856 23-09-2016 505.2 -4.55 0 4.55 0.272344 21.4049 26-09-2016 497.75 -7.45 0 7.45 0.376457 27.3497 27-09-2016 493 -4.75 0 4.75 0.388688 27.9896 28-09-2016 492.95 -0.05 0 0.05 0.425 29.82456 29-09-2016 481.6 -11.35 0 11.35 0.175279 14.91379 30-09-2016 482.15 0.55 0 -0.55 0.203529 16.91105
  • 55. 55 KLE’s Institute of Management Studies and Research, Hubli 03-10-2016 488.55 6.4 6.4 0 0.354118 26.15117 04-10-2016 495.95 7.4 7.4 0 0.568354 36.2389 05-10-2016 498.4 2.45 2.45 0 0.61 37.8882 06-10-2016 491.2 -7.2 0 7.2 0.537445 34.95702 07-10-2016 491.85 0.65 0 -0.65 0.645503 39.2283 10-10-2016 500.9 9.05 9.05 0 0.965368 49.11894 11-10-2016 500.9 0 0 0 0.730159 42.20183 12-10-2016 500.9 0 0 0 0.740849 42.55677 13-10-2016 489.7 -11.2 0 11.2 0.620098 38.27534 14-10-2016 501.05 11.35 11.35 0 1.098951 52.35714 17-10-2016 490.6 -10.45 0 10.45 0.93854 48.4148 18-10-2016 476.85 -13.75 0 13.75 0.694787 40.99553 19-10-2016 476.95 0.1 0 -0.1 0.887409 47.01732 20-10-2016 479.05 2.1 2.1 0 0.925926 48.07692 21-10-2016 479 -0.05 0 0.05 0.772076 43.56902 24-10-2016 456 -23 0 23 0.384438 27.7685 25-10-2016 454.9 -1.1 0 1.1 0.340909 25.42373 26-10-2016 450.2 -4.7 0 4.7 0.354331 26.16279 27-10-2016 441.5 -8.7 0 8.7 0.308854 23.59727 28-10-2016 435.95 -5.55 0 5.55 0.171556 14.64344 31-10-2016 435.95 0 0 0 0.171556 14.64344 01-11-2016 439.55 3.6 3.6 0 0.217474 17.86276 02-11-2016 433.55 -6 0 6 0.232923 18.89197 03-11-2016 428.35 -5.2 0 5.2 0.072704 6.777646 04-11-2016 425.15 -3.2 0 3.2 0.080112 7.417046 07-11-2016 429.25 4.1 4.1 0 0.170732 14.58333 08-11-2016 442.65 13.4 13.4 0 0.403478 28.74845 09-11-2016 436.15 -6.5 0 6.5 0.329688 24.79436 10-11-2016 437.4 1.25 1.25 0 0.349492 25.89803 11-11-2016 423.55 -13.85 0 13.85 0.407847 28.96954 14-11-2016 423.55 0 0 0 0.416201 29.38856 15-11-2016 430.55 7 7 0 0.59898 37.46011 16-11-2016 437.9 7.35 7.35 0 0.91067 47.66234 17-11-2016 441.75 3.85 3.85 0 1.166906 53.85126 18-11-2016 442.25 0.5 0 -0.5 1.183942 54.21123 21-11-2016 441.8 -0.45 0 0.45 1.064841 51.57013 22-11-2016 453.15 11.35 11.35 0 1.682927 62.72727 23-11-2016 453.5 0.35 0.35 -0.35 2.101512 67.75766 24-11-2016 462.85 9.35 9.35 0 2.907268 74.40667 25-11-2016 478.25 15.4 15.4 0 3.473684 77.64706 28-11-2016 477.8 -0.45 0 0.45 2.740196 73.26343 29-11-2016 473.65 -4.15 0 4.15 3.096953 75.59162 30-11-2016 477.35 3.7 3.7 0 3.232687 76.37435 01-12-2016 466.6 -10.75 0 10.75 3.90301 79.60437
  • 56. 56 KLE’s Institute of Management Studies and Research, Hubli 02-12-2016 460.45 -6.15 0 6.15 2.765403 73.44242 05-12-2016 448.35 -12.1 0 12.1 1.546687 60.73329 06-12-2016 459.8 11.45 11.45 0 1.670181 62.54935 07-12-2016 457.75 -2.05 0 2.05 1.46383 59.41278 08-12-2016 462.2 4.45 4.45 0 1.567832 61.05664 09-12-2016 470.65 8.45 8.45 0 1.827195 64.62926 12-12-2016 468.25 -2.4 0 2.4 1.409814 58.50303 13-12-2016 492.5 24.25 24.25 0 2.024967 66.94179 14-12-2016 502.9 10.4 10.4 0 2.052562 67.24064 15-12-2016 495.3 -7.6 0 7.6 1.373494 57.86802 16-12-2016 501.35 6.05 6.05 0 1.521018 60.33348 19-12-2016 500.1 -1.25 0 1.25 1.625296 61.90905 20-12-2016 494.1 -6 0 6 1.346791 57.38862 21-12-2016 493.95 -0.15 0 0.15 1.725464 63.309 22-12-2016 495.4 1.45 1.45 0 2.107765 67.82254 23-12-2016 496.9 1.5 1.5 0 3.496144 77.75872 26-12-2016 487.9 -9 0 9 1.987698 66.52941 27-12-2016 486.2 -1.7 0 1.7 2.012456 66.80449 28-12-2016 510.15 23.95 23.95 0 2.706406 73.01968 29-12-2016 523.85 13.7 13.7 0 2.893238 74.31444 30-12-2016 521.65 -2.2 0 2.2 2.913978 74.45055 02-01-2017 516.7 -4.95 0 4.95 1.736682 63.4594 03-01-2017 507.9 -8.8 0 8.8 1.120048 52.83126 04-01-2017 526.4 18.5 18.5 0 1.913363 65.6754 05-01-2017 523.7 -2.7 0 2.7 1.608163 61.65884 06-01-2017 500.2 -23.5 0 23.5 1.001695 50.04234 09-01-2017 495.5 -4.7 0 4.7 1.024263 50.59932 10-01-2017 487.15 -8.35 0 8.35 0.896813 47.28 11-01-2017 487.3 0.15 0.15 -0.15 0.879087 46.78268 12-01-2017 491.3 4 4 0 0.91711 47.83816 13-01-2017 490.85 -0.45 0 0.45 1.054196 51.31915 16-01-2017 484.95 -5.9 0 5.9 0.982085 49.54807 17-01-2017 484.85 -0.1 0 0.1 0.591057 37.1487 18-01-2017 495.5 10.65 10.65 0 0.541463 35.12658 19-01-2017 485.1 -10.4 0 10.4 0.477762 32.3301 20-01-2017 475.25 -9.85 0 9.85 0.446381 30.86191 23-01-2017 471.3 -3.95 0 3.95 0.477419 32.31441 24-01-2017 470.25 -1.05 0 1.05 0.20904 17.28972 25-01-2017 461.65 -8.6 0 8.6 0.19296 16.17486 26-01-2017 461.65 0 0 0 0.278195 21.76471 27-01-2017 472.5 10.85 10.85 0 0.528866 34.59204 30-01-2017 465.55 -6.95 0 6.95 0.544586 35.25773 31-01-2017 450.5 -15.05 0 15.05 0.40931 29.04328 01-02-2017 459.85 9.35 9.35 0 0.495185 33.11863
  • 57. 57 KLE’s Institute of Management Studies and Research, Hubli 02-02-2017 461 1.15 1.15 0 0.517381 34.09696 03-02-2017 459.35 -1.65 0 1.65 0.555556 35.71429 06-02-2017 464.85 5.5 5.5 0 0.652174 39.47368 07-02-2017 452.8 -12.05 0 12.05 0.386053 27.8527 08-02-2017 450.1 -2.7 0 2.7 0.434115 30.27057 09-02-2017 457.6 7.5 7.5 0 0.660577 39.77997 10-02-2017 466.65 9.05 9.05 0 0.903226 47.45763 13-02-2017 468.15 1.5 1.5 0 0.955319 48.85745 14-02-2017 455.1 -13.05 0 13.05 0.872692 46.60093 15-02-2017 457.65 2.55 2.55 0 0.922255 47.97776 16-02-2017 468 10.35 10.35 0 0.912536 47.71341 17-02-2017 475.15 7.15 7.15 0 1.21573 54.86815 20-02-2017 474.4 -0.75 0 0.75 1.791391 64.17556 21-02-2017 474.4 0 0 0 1.481788 59.70647 22-02-2017 468.2 -6.2 0 6.2 1.197802 54.5 23-02-2017 469.9 1.7 1.7 0 1.303597 56.58963 24-02-2017 469.9 0 0 0 1.145324 53.38699 27-02-2017 471.15 1.25 1.25 0 1.80837 64.39216 28-02-2017 474.3 3.15 3.15 0 2.21 68.84735 01-03-2017 471.95 -2.35 0 2.35 1.642058 62.15072 02-03-2017 460.3 -11.65 0 11.65 0.813235 44.84996 03-03-2017 464.6 4.3 4.3 0 0.895588 47.24593 06-03-2017 460.25 -4.35 0 4.35 1.203557 54.61883 07-03-2017 478.7 18.45 18.45 0 1.832016 64.68946 08-03-2017 469.25 -9.45 0 9.45 1.035971 50.88339 09-03-2017 472.65 3.4 3.4 0 0.928058 48.13433 10-03-2017 474.8 2.15 2.15 0 1.011765 50.2924 13-03-2017 474.8 0 0 0 1.011765 50.2924 14-03-2017 470.85 -3.95 0 3.95 1.083465 52.00302 15-03-2017 466.55 -4.3 0 4.3 0.907074 47.56364 16-03-2017 469.75 3.2 3.2 0 0.995839 49.89576 17-03-2017 473.45 3.7 3.7 0 1.0638 51.5457 20-03-2017 474.1 0.65 0.6 -0.65 1.011299 50.2809 21-03-2017 474.85 0.75 0.75 -0.75 1.131579 53.08642 22-03-2017 472.3 -2.55 0 2.55 1.575431 61.17155 23-03-2017 472.2 -0.1 0 0.1 1.38412 58.05581 24-03-2017 469.55 -2.65 0 2.65 1.493056 59.88858 27-03-2017 461.3 -8.25 0 8.25 0.462312 31.61512 28-03-2017 459.95 -1.35 0 1.35 0.634483 38.81857 29-03-2017 456.1 -3.85 0 3.85 0.40625 28.88889 30-03-2017 453.2 -2.9 0 2.9 0.289474 22.44898 31-03-2017 452.95 -0.25 0 0.25 0.286957 22.2973
  • 58. 58 KLE’s Institute of Management Studies and Research, Hubli Interpretation In the above chart RSI is calculated for 14 days. The Wilder rule, if RSI crosses 70 there may be downturn & time to sell. If RSI falls below 30 it is time to buy the share. Here in above chart if the line crosses 70 it shows sell signal & if the line crosses below 30 it shows buy signal. In the month of July ,August ,December 2016 the RSI crosses above 70 so it is the time to sell. And in May, September, November 2016 was right time to buy. TCS ( Relative Strength Index): Date TCS closing Change Gain Loss RS Value RSI 01-04-2016 2455.4
  • 59. 59 KLE’s Institute of Management Studies and Research, Hubli 04-04-2016 2470.7 15.3 15.3 0 05-04-2016 2462.65 -8.05 0 8.05 06-04-2016 2478.9 16.25 16.25 0 07-04-2016 2470.95 -7.95 0 7.95 08-04-2016 2428.7 -42.25 0 42.25 11-04-2016 2506.65 77.95 77.95 0 12-04-2016 2512.5 5.85 5.85 0 13-04-2016 2523.15 10.65 10.65 0 14-04-2016 2523.15 0 0 0 15-04-2016 2523.15 0 0 0 18-04-2016 2522.4 -0.75 0 0.75 19-04-2016 2522.4 0 0 0 20-04-2016 2451.9 -70.5 0 70.5 21-04-2016 2423.2 -28.7 0 28.7 0.79646 44.33498 22-04-2016 2417.2 -6 0 6 0.674178 40.26919 25-04-2016 2448.3 31.1 31.1 0 0.908101 47.59188 26-04-2016 2488 39.7 39.7 0 1.058277 51.41568 27-04-2016 2505.55 17.55 17.55 0 1.233468 55.22659 28-04-2016 2526.95 21.4 21.4 0 1.927324 65.83911 29-04-2016 2530.05 3.1 3.1 0 1.220859 54.97238 02-05-2016 2525.15 -4.9 0 4.9 1.114118 52.69895 03-05-2016 2480.25 -44.9 0 44.9 0.724559 42.01415 04-05-2016 2478.25 -2 0 2 0.715372 41.70362 05-05-2016 2474 -4.25 0 4.25 0.696605 41.05876 06-05-2016 2472.15 -1.85 0 1.85 0.691907 40.89509 09-05-2016 2515.35 43.2 43.2 0 0.956775 48.8955 10-05-2016 2523.6 8.25 8.25 0 1.774298 63.95485 11-05-2016 2517.75 -5.85 0 5.85 2.355556 70.19868 12-05-2016 2567.05 49.3 49.3 0 3.350588 77.0146 13-05-2016 2523.4 -43.65 0 43.65 1.699255 62.95274 16-05-2016 2553.8 30.4 30.4 0 1.612663 61.72488 17-05-2016 2570.2 16.4 16.4 0 1.601955 61.56736 18-05-2016 2550.45 -19.75 0 19.75 1.184821 54.22966 19-05-2016 2555.55 5.1 5.1 0 1.200551 54.55683 20-05-2016 2532.05 -23.5 0 23.5 1.047341 51.15617 23-05-2016 2491.7 -40.35 0 40.35 1.081091 51.94827 24-05-2016 2467.5 -24.2 0 24.2 0.934211 48.29932 25-05-2016 2526.7 59.2 59.2 0 1.331134 57.10243 26-05-2016 2552.8 26.1 26.1 0 1.512715 60.2024 27-05-2016 2572.05 19.25 19.25 0 1.360458 57.63534 30-05-2016 2635.35 63.3 63.3 0 1.710426 63.10543 31-05-2016 2575.1 -60.25 0 60.25 1.270902 55.96464 01-06-2016 2631.85 56.75 56.75 0 1.306094 56.63662 02-06-2016 2646.9 15.05 15.05 0 1.7349 63.4356