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School of Management SUMMER INTERNSHIP PROJECT on Technical Analysis On Indian Stock Market A Research Project Submitted to Add Value in the Degree of Masters of Business Administration (2009-2011) Faculty Guide Company Guide Prity Dawer Pradip Agrawal Head-Corporate Relations SIP Coordinators
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Page 1: Sip Report

School of Management

SUMMER INTERNSHIP PROJECT on

Technical Analysis On Indian Stock Market

A Research Project Submitted to Add Value in the Degree of Masters of Business Administration

(2009-2011)

Faculty Guide Company GuidePrity Dawer Pradip Agrawal

Head-Corporate Relations SIP CoordinatorsMr. James Pal Prof. Latika Rochlani & Prof. Hartej Khera

Chairperson DirectorProf. Gaurav Singh Dr. Prashant Gupta

Submitted by:Apoorva Murdiya MBA(III Sem)

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CERTIFICATE FROM COMPANY GUIDE

This is to certify that “Apoorva Murdiya” of MBA (Full Time) Semester III in

Sanghvi Institute of Management and Science, Indore has carried out a Summer

Internship Project titled “Technical Analysis On Indian Stock Market”. The work done

by him/her is genuine and authentic.

The work carried out by the student was found satisfactory. We wish him/her all the

success in career.

Signature

Pradip AgrawalCentre Manager- Capital

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CERTIFICATE FROM FACULTY GUIDE

This is to certify that “Apoorva Murdiya” of MBA (Full Time) Semester III in Sanghvi Institute of Management and Science, Indore has carried out a Summer Internship Project titled “Technical Analysis On Indian Stock Market”. The work done by him/her is genuine and authentic.

The work carried out by the student was found satisfactory. We wish him/her all the

success in career.

Signature

Prity Dawer

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DECLARATION

I, “Apoorva Murdiya”, a student of School of Management, Sanghvi Institute of

Management & Science, Indore, hereby declare that the work done by me to do the

Summer Internship Project titled “Technical Analysis On Indian Stock Market” is

genuine and authentic.

Name & Signature of the Student

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ACKNOWLEDGEMENT Note: It is just a specimen acknowledgement to refer; students may adopt any other

standard pattern to express their indebtedness.

I sincerely and religiously devote this folio to all the gem of persons who have openly

or silently left an ineradicable mark on this research so that they may be brought into

consideration and given their share of credit, which they genuinely and outstandingly

deserve.

This expedition of research encountered many trials, troubles and tortures along the

way. I am essentially indebted to my guides “Pradip Agrawal and Prity Dawer” for this

sweating learning experience. They overlooked my faults and follies, constantly inspired

and mentored via the proficient direction. It was a privilege to work under their sincere

guidance.

I express my thanks to Dr. Prashant Gupta, Director (M.B.A. / P.G.D.M.), Sanghvi

Institute of Management and Science, Indore for his considerate support whenever and

wherever needed. I honestly acknowledge the sincere guidance provided by the Head-

Corporate Relations, Mr. James Pal, Mr. Ashutosh Bakshi, Training & Placement

Officer, the Chairperson Prof. Gaurav Singh, Coordinators, Prof. Latika Rochlani &

Prof. Hartej Khera. I express my indebtedness to the management of Sanghvi Institute of

Management and Science, for inspiring us to grab and utilize this opportunity.

With profound sense of gratitude, I would like to truthfully thank a recognizable

number of individuals whom I have not mentioned here, but who have visibly or invisibly

facilitated in transforming this research into a success saga.

Above all, I would like to conscientiously thank the Omnipotent, Omnipresent and

Omniscient God for His priceless blessings!

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Name and Signature of Student

EXECUTIVE SUMMARY

Technical Analysis is one of the most popular techniques used to make better

investment decision nowadays. The very fact that it is used by professional hands and so

informed decision is taken before buying or selling equities and or bonds encourages

many investors to venture in to equity market segment.

The title of the project is Technical analysis of stocks. This project is divided into two

stages:

A study of Technical analysis and

To analyze Nifty movements with technical analysis indicators

The first stage of this project dealt with comprehending the various aspects of

Technical Analysis with respect to Historical and current market movements of S&P

CNX Nifty. This stage mainly dealt with the analysis of secondary data and helped a lot

to build conceptual framework for the further analysis of current market situation.

The Second Stage mainly dealt with the Technical analysis of current markets based

on primary data pertaining to Nifty Index.

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Chapter 1

INTRODUCTION

Major investment instruments to be used in the market are Commodities and Equities

where return is highest in market. As an investor, everyone needs to know their behavior

and pattern before investing in to any Equity or Commodity. So Stock markets become

important benchmark to follow the condition of economy and to devise the investment

strategies for short term and long term. This study mainly tries to capture the

effectiveness of Technical Analysis while formulating investment strategies by analyzing

Secondary as well as primary data available on nifty index.

1.1 IMPORTANCE AND RELEVANCE OF STUDY

This study comprises of analytical work based on both primary real time data as well

as historical secondary data using different graphs mainly Candlesticks. So it will be of

great help in formulating various investment strategies for future keeping in perspective

both short term and long term goals.

1.2 LITERATURE REVIEW

The use of market timing has long been the subject of much discussion. Several

researchers question the usefulness of such techniques, arguing that such techniques

usually cannot produce better returns than a buy-and-hold (B-H) strategy. Many filter

rules were tested on the US stock market, with most of them concluding that filter rules

do not generate superior returns to the B-H strategy. If the cost of transactions were

considered, the returns could even be negative (Fama and Blume, 1966; Jensen and

Benington 1970). These results are consistent with the efficient markets hypothesis. This

hypothesis implies that technical analysis is without merit. In an efficient market, the

current price reflects all available information including the past history of prices and

trading volume. As investors compete to exploit their common knowledge of a stock’s

price history, they necessarily drive stock prices to levels where expected rate of return

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are exactly commensurate with risk. At those levels one cannot expect abnormal returns

(see Fama, 1970).

Although technicians recognize the value of information on future economic

prospects of the firm, their position is that such information is not mandatory for a

successful trading strategy. The reason is that whatever the fundamental reason for a

change in the stock price, if the stock price is sluggish to adjust, the analyst should be

able to identify a trend that could be exploited during the adjustment period.

Consequently, the key to successful technical analysis is a lazy response of stock prices

to fundamental supply-and-demand phenomena. Note that this prerequisite is

diametrically opposite to the notion of an efficient market.Practitioners’ reliance on

technical analysis is well documented.Frankel and Froot (1990a) noted that market

professionals tend to include technical analysis in forecasting the market.

There is also a shift away from the fundamentals to technical analysis in the 1980s,

according to a survey done by Euromoney (Frankel and Froot, 1990a). On a market level,

the prevalence of technical analysis is demonstrated by the fact that most real time

financial information services, like Reuters and Telerate, provide detailed, comprehensive

and up-to-date technical analysis information. It is obvious that the frequent upgrading of

technical analysis services is a response to the demand for technical analysis services and

competition among the financial information service providers. The guiding principle of

technical analysis is to identify and go along with the trend. When there is a trend,

whether started by random or fundamental factors, technical methods will tend to

generate signals in the same direction. This reinforces the original trend, especially when

many investors rely on the technical indicators. Thus, even if the original trend were a

random occurrence, the subsequent prediction made by the technical indicator could be

self-fulfilling. This self-fulfilling nature leads to the formation of speculative bubbles

(Froot et al.,1992).

Conrad and Kaul (1988) found that weekly returns were positively auto correlated,

particularly for portfolios of small stocks.

Frankel and Froot (1990b) suggested that the overpricing of the US dollar in the

1980s with respect to the underlying economic fundamentals could be due to the

influence of technical analysis.

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Shiller (1984, 1987) found that irrational investor behaviour resulted in excess bond

and stock market volatility. He also suggested that the October 1987 world-wide stock

market crash could be due largely to technical analysis.

Fama and French (1988) proposed a mean reverting model to explain stock price

movements. They also found that autocorrelation of returns become strongly negative for

a 3–5 year horizon.

DeBondt and Thaler (1985, 1987) found that stocks that were extreme losers over a

3–5 year period tend to have strong returns relative to the market during the following

years. Conversely, extreme winners tend to have weaker returns in subsequent years.

Sy (1990) had argued against Sharpe’s (1975) conclusion, saying that there was no

need for the predictive accuracy to be as high as 70% for the gains to be large. In

addition, he demonstrated that market timing would be increasingly rewarding when the

difference in returns between cash and stocks were narrowed and when market volatility

increased.

Balvers et al. (1990) show empirically that stock returns could be predicted based on

national aggregate output.

Other studies have shown that some fundamental data like price earnings ratio,

dividend yields, business conditions and economic variables can predict to a large degree

the returns on stocks (Campbell, 1987; Campbell and Shiller, 1988a, 1988b; Fama and

French, 1989; Breen et al., 1990, among others). For further innovations, see Wong

(1993, 1994) and Wong et al. (2001).

Brown and Jennings (1989) showed that technical analysis has value in a model in

which prices are not fully revealing and traders have rational conjectures about the

relation between prices and signals.

Frankel and Froot (1990) showed evidence for the rising importance of chartists.

Neftci (1991) showed that a few of the rules used in technical analysis generate well-

defined echniques of forecasting, but even well-defined rules were shown to be useless in

prediction if the economic time series is Gaussian. However, if the processes under

consideration are non-linear, then the rules might capture some information. Tests

showed that this may indeed be the case for the moving average rule.

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Taylor and Allen (1992) report the results of a survey among chief foreign exchange

dealers based in London in November 1988 and found that at least 90 per cent of

respondents placed some weight on technical analysis, and that there was a skew towards

using technical, rather than fundamental, analysis at shorter time horizons.

In a comprehensive and influential study Brock, Lakonishok and LeBaron (1992)

analysed 26 technical trading rules using 90 years of daily stock prices from the Dow

Jones Industrial Average up to 1987 and found that they all outperformed the market.

Blume, Easley and O’Hara (1994) show that volume provides information on

information quality that cannot be deduced from the price. They also show that traders

who use information contained in market statistics do better than traders who do not.

Neely (1997) explains and reviews technical analysis in the foreign exchange market.

Neely, Weller and Dittmar (1997) use genetic programming to find technical trading

rules in foreign exchange markets. The rules generated economically significant out-of-

sample excess returns for each of six exchange rates, over the period 1981–1995.

Lui and Mole (1998) report the results of a questionnaire survey conducted in

February 1995 on the use by foreign exchange dealers in Hong Kong of fundamental and

technical analyses. They found that over 85% of respondents rely on both methods and,

again, technical analysis was more popular at shorter time horizons.

Neely (1998) reconciles the fact that using technical trading rules to trade against US

intervention in foreign exchange markets can be profitable, yet, longterm, the

intervention tends to be profitable.

LeBaron (1999) shows that, when using technical analysis in the foreign exchange

market, after removing periods in which the Federal Reserve is active, exchange rate

predictability is dramatically reduced.

Lo, Mamaysky andWang (2000) examines the effectiveness of technical analysis on

US stocks from 1962 to 1996 and finds that over the 31-year sample period, several

technical indicators do provide incremental information and may have some practical

value.

Fern´andez-Rodr´ıguez, Gonz´alez-Martel and Sosvilla-Rivero (2000) apply an

artificial neural network to the Madrid Stock Market and find that, in the absence of

trading costs, the technical trading rule is always superior to a buy and hold strategy for

both ‘bear’ market and ‘stable’ market episodes, but not in a ‘bull’ market. One criticism

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I have is that beating the market in the absence of costs seems of little significance unless

one is interested in finding a signal which will later be incorporated into a full system.

Secondly, it is perhaps naïve to work on the premise that ‘bull’ and ‘bear’ markets exist.

Lee and Swaminathan (2000) demonstrate the importance of past trading volume.

Neely and Weller (2001) use genetic programming to show that technical trading

rules can be profitable during US foreign exchange intervention.

Cesari and Cremonini (2003) make an extensive simulation comparison of popular

dynamic strategies of asset allocation and find that technical analysis only performs well

in Pacific markets.

Cheol-Ho Park and Scott H. Irwin wrote ‘The profitability of technical analysis: A

review’ Park and Irwin (2004), an excellent review paper on technical analysis.

Kavajecz and Odders-White (2004) show that support and resistance levels coincide

with peaks in depth on the limit order book 1 and moving average forecasts reveal

information about the relative position of depth on the book.They also show that these

relationships stem from technical rules locating depth already in place on the limit order

book.

More recently, Lo et al. (2000) examined the prevalence of various technical patterns

in American share prices over the period 1962–1996 and found the patterns to be

unusually recurrent.The study does not prove that the patterns are predictable enough to

make sufficient profit to justify the risk,but the authors conclude that this is likely.

1.3 OBJECTIVE

To study the applicability of Technical analysis to stock markets using Nifty

To identify and sort out simple Technical analysis tool relevant for the

formulation of various investment strategies.

Analysis of Stock Market movements during various cyclic events.

To forecast market scenario for near future based on Technical analysis.

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CHAPTER 2

CONCEPTUAL FRAMEWORK ON TECHNICAL

ANALYSIS

The methods used to analyze securities and make investment decisions fall into two very

broad categories: fundamental analysis and technical analysis. Fundamental analysis

involves analyzing the characteristics of a company in order to estimate its value.

Technical analysis takes a completely different approach; it doesn't care one bit about the

"value" of a company or a commodity. Technicians or chartists are only interested in the

price movements 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. In other words, technical analysis attempts to understand the

emotions in the market by studying the market itself, as opposed to its components

Technical analysis is a method of evaluating securities by analyzing the 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 and other tools to

identify patterns that can suggest future activity. Just as there are many investment styles

on the fundamental side, there are also many different types of technical traders. Some

rely on chart patterns; others use technical indicators and oscillators, and most use some

combination of the two. In any case, technical analysts' exclusive use of historical price

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and volume data is what separates them from their fundamental counterparts. Unlike

fundamental analysts, technical analysts don't care whether a stock is undervalued - the

only thing that matters is a security's past trading data and what information this data can

provide about where the security might move in the future. The field of technical analysis

is based on three assumptions:

Market discounts everything.

Price moves in trends

History tends to repeats itself.

One of the most important concepts in technical analysis is that of trend. The meaning in

finance isn't all that different from the general definition of the term - a trend is really

nothing more than the general direction in which a security or market is headed.

Above figure is an example of an uptrend. Point 2 in the chart is the first high, which is

determined after the price falls from this point. Point 3 is the low that is established as the

price falls from the high. For this to remain an uptrend each successive low must not fall

below the previous lowest point or the trend is deemed a reversal.

  

2.1 Trendline

A trendline is a simple charting technique that adds a line to a chart to represent the trend

in the market or a stock. Drawing a trend line is as simple as drawing a straight line

As you can see in following figure, an upward trendline is drawn at the lows of an

upward trend. This line represents the support the stock has every time it moves from a

high to a low.

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Support and resistance analysis is an important part of trends because it can be used to

make trading decisions and identify when a trend is reversing

As you can see in Figure, support is the price level through which a stock or market

seldom falls (illustrated by the blue arrows). Resistance, on the other hand, is the price

level that a stock or market seldom surpasses (illustrated by the red arrows).

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2.2 Role Reversal

Once a resistance or support level is broken, its role is reversed. If the price falls below a

support level, that level will become resistance. If the price rises above a resistance level,

it will often become support. As the price moves past a level of support or resistance, it is

thought that supply and demand has shifted, causing the breached level to reverse its role.

For a true reversal to occur, however, it is important that the price make a strong move

through either the support or resistance

For example, as you can see in Figure, the dotted line is shown as a level of resistance

that has prevented the price from heading higher on two previous occasions (Points 1 and

2). However, once the resistance is broken, it becomes a level of support (shown by

Points 3 and 4) by propping up the price and preventing it from heading lower again.

Support and resistance levels both test and confirm trends and need to be monitored by

anyone who uses technical analysis. As long as the price of the share remains between

these levels of support and resistance, the trend is likely to continue.

2.3 Charts

In technical analysis, charts are similar to the charts that you see in any business setting.

For example, a chart may show a stock's price movement over a one-year period, where

each point on the graph represents the closing price for each day the stock is traded.

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There are several things that you should be aware of when looking at a chart, as these

factors can affect the information that is provided. They include the time scale, the price

scale and the price point properties used. If a price scale is constructed using a linear

scale, the space between each price point (10, 20, 30, 40) is separated by an equal

amount. A price move from 10 to 20 on a linear scale is the same distance on the chart as

a move from 40 to 50. In other words, the price scale measures moves in absolute terms

and does not show the effects of percent change.

If a price scale is in logarithmic terms, then the distance between points will be equal in

terms of percent change. A price change from 10 to 20 is a 100% increase in the price

while a move from 40 to 50 is only a 25% change, even though they are represented by

the same distance on a linear scale. On a logarithmic scale, the distance of the 100% price

change from 10 to 20 will not be the same as the 25% change from 40 to 50. In this case,

the move from 10 to 20 is represented by a larger space one the chart, while the move

from 40 to 50, is represented by a smaller space because, percentage-wise, it indicates a

smaller move. In Figure, the logarithmic price scale on the right leaves the same amount

of space between 10 and 20 as it does between 20 and 40 because these both represent

100% increases.

There are four main types of charts that are used by investors and traders depending on

the information that they are seeking and their individual skill levels. The chart types are:

the line chart, the bar chart, the candlestick chart and the point and figure chart. As our

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analysis will be using more of candle sticks so here is the brief description about

candlestick charts.

2.4 Candlestick Charts

The candlestick chart is similar to a bar chart, but it differs in the way that it is visually

constructed. Similar to the bar chart, the candlestick also has a thin vertical line showing

the period's trading range. The difference comes in the formation of a wide bar on the

vertical line, which illustrates the difference between the open and close. And, like bar

charts, candlesticks also rely heavily on the use of colors to explain what has happened

during the trading period. A major problem with the candlestick color configuration,

however, is that different sites use different standards; therefore, it is important to

understand the candlestick configuration used at the chart site you are working with.

There are two color constructs for days up and one for days that the price falls. When the

price of the stock is up and closes above the opening trade, the candlestick will usually be

white or clear. If the stock has traded down for the period, then the candlestick will

usually be red or black, depending on the site. If the stock's price has closed above the

previous day’s close but below the day's open, the candlestick will be black or filled with

the color that is used to indicate an up day.

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Charts are one of the most fundamental aspects of technical analysis. It is important that

you clearly understand what is being shown on a chart and the information that it

provides. Now that we have an idea of how charts are constructed, we can move on to the

different types of chart patterns. A chart pattern is a distinct formation on a stock chart

that creates a trading signal, or a sign of future price movements. Chartists use these

patterns to identify current trends and trend reversals and to trigger buy and sell signals.

While there are general ideas and components to every chart pattern, there is no chart

pattern that will tell you with 100% certainty where a security is headed. This creates

some leeway and debate as to what a good pattern looks like, and is a major reason why

charting is often seen as more of an art than a science.

2.5 Patterns

There are two types of patterns within this area of technical analysis, reversal and

continuation. A reversal pattern signals that a prior trend will reverse upon completion of

the pattern. A continuation pattern, on the other hand, signals that a trend will continue

once the pattern is complete. These patterns can be found over charts of any timeframe.

In this section, we will review some of the more popular chart patterns. We will now

move on to other technical techniques and examine how they are used by technical

traders to gauge price movements.

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 averages. 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.

2.6 Moving Averages

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Another method of determining momentum is to look at the order of a pair of moving

averages. When a short-term average is above a longer-term average, the trend is up. On

the other hand, a long-term average above a shorter-term average signals a downward

movement.

Moving average trend reversals are formed in two main ways: when the price moves

through a moving average and when it moves through moving average crossovers. The

first common signal is when the price moves through an important moving average. For

example, when the price of a security that was in an uptrend falls below a 50-period

moving average, like in Figure below, it is a sign that the uptrend may be reversing.

The other signal of a trend reversal is when one moving average crosses through another.

For example, as you can see in Figure below, if the 15-day moving average crosses above

the 50-day moving average, it is a positive sign that the price will start to increase.

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If the periods used in the calculation are relatively short, for example 15 and 35, this

could signal a short-term trend reversal. On the other hand, when two averages with

relatively long time frames cross over (50 and 200, for example), this is used to suggest a

long-term shift in trend.

2.7 Other Important Indicators

Indicators are calculations based on the price and the volume of a security that measure

such things as money flow, trends, volatility and momentum. Indicators are used as a

secondary measure to the actual price movements and add additional information to the

analysis of securities. Indicators are used in two main ways: to confirm price movement

and the quality of chart patterns, and to form buy and sell signals.

There are two main types of indicators: leading and lagging. A leading indicator precedes

price movements, giving them a predictive quality, while a lagging indicator is a

confirmation tool because it follows price movement. A leading indicator is thought to be

the strongest during periods of sideways or non-trending trading ranges, while the

lagging indicators are still useful during trending periods.

There are also two types of indicator constructions: those that fall in a bounded range and

those that do not. The ones that are bound within a range are called oscillators - these are

the most common type of indicators. Oscillator indicators have a range, for example

between zero and 100, and signal periods where the security is overbought (near 100) or

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oversold (near zero). Non-bounded indicators still form buy and sell signals along with

displaying strength or weakness, but they vary in the way they do this.

The two main ways that indicators are used to form buy and sell signals in technical

analysis is through crossovers and divergence. Crossovers are the most popular and are

reflected when either the price moves through the moving average, or when two different

moving averages cross over each other. The second way indicators are used is through

divergence, which happens when the direction of the price trend and the direction of the

indicator trend are moving in the opposite direction.

Indicators that are used in technical analysis provide an extremely useful source of

additional information. These indicators help identify momentum, trends, volatility and

various other aspects in a security to aid in the technical analysis of trends. It is important

to note that while some traders use a single indicator solely for buy and sell signals, they

are best used in conjunction with price movement, chart patterns and other indicators.

2.7.1 MACD

The moving average convergence divergence (MACD) is one of the most well known

and used indicators in technical analysis. This indicator is comprised of two exponential

moving averages, which help to measure momentum in the security. The MACD is

simply the difference between these two moving averages plotted against a centerline.

The centerline is the point at which the two moving averages are equal. Along with the

MACD and the centerline, an exponential moving average of the MACD itself is plotted

on the chart. The idea behind this momentum indicator is to measure short-term

momentum compared to longer term momentum to help signal the current direction of

momentum.

When the MACD is positive, it signals that the shorter term moving average is above the

longer term moving average and suggests upward momentum. The opposite holds true

when the MACD is negative - this signals that the shorter term is below the longer and

suggest downward momentum. When the MACD line crosses over the centerline, it

signals a crossing in the moving averages. The most common moving average values

used in the calculation are the 26-day and 12-day exponential moving averages. The

signal line is commonly created by using a nine-day exponential moving average of the

MACD values. These values can be adjusted to meet the needs of the technician and the

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security. For more volatile securities, shorter term averages are used while less volatile

securities should have longer averages.

Another aspect to the MACD indicator that is often found on charts is the MACD

histogram. The histogram is plotted on the centerline and represented by bars. Each bar is

the difference between the MACD and the signal line or, in most cases, the nine-day

exponential moving average. The higher the bars are in either direction, the more

momentum behind the direction in which the bars point. As you can see in Figure

following, one of the most common buy signals is generated when the MACD crosses

above the signal line (blue dotted line), while sell signals often occur when the MACD

crosses below the signal.

2.7.2 Relative Strength Index

The relative strength index (RSI) is another one of the most used and well-known

momentum indicators in technical analysis. RSI helps to signal overbought and oversold

conditions in a security. The indicator is plotted in a range between zero and 100. A

reading above 70 is used to suggest that a security is overbought, while a reading below

30 is used to suggest that it is oversold. This indicator helps traders to identify whether a

security’s price has been unreasonably pushed to current levels and whether a reversal

may be on the way.

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The standard calculation for RSI uses 14 trading days as the basis, which can be adjusted

to meet the needs of the user. If the trading period is adjusted to use fewer days, the RSI

will be more volatile and will be used for shorter term trades.

2.7.3 Stochastic

The stochastic oscillator is one of the most recognized momentum indicators used in

technical analysis. The idea behind this indicator is that in an uptrend, the price should be

closing near the highs of the trading range, signaling upward momentum in the security.

In downtrends, the price should be closing near the lows of the trading range, signaling

downward momentum.

The stochastic oscillator is plotted within a range of zero and 100 and signals overbought

conditions above 80 and oversold conditions below 20. The stochastic oscillator contains

two lines. The first line is the %K, which is essentially the raw measure used to formulate

the idea of momentum behind the oscillator. The second line is the %D, which is simply a

moving average of the %K. The %D line is considered to be the more important of the

two lines as it is seen to produce better signals. The stochastic oscillator generally uses

the past 14 trading periods in its calculation but can be adjusted to meet the needs of the

user.

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CHAPTER 3

METHODOLOGY OF STUDY

This section deals with the actual process adopted to carry out the study. It consists of the

universe and locale of study, sample selection, data collection and process of data

analysis.

3.1 LOCALE OF STUDY

The project was done in Indore office of Reliance Securities ltd. The office is basically

Looks after all aspects Stock Broking or Trading activities like Analytics, Online Trading

and Business Development.

3.2 SAMPLE SELECTION

As per the availability of time Primary Real Time data was limited to March to June so

that proper analysis could take place on daily basis 2001 and March 2009. Daily as well

as short duration charts were captured for NSE.

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As far as analysis with secondary data is concerned, relevant period after 1991 is focused

at random periods as well during some major events.

3.3 DATA COLLECTION

Primary live data was capture from Real time websites like www.icharts.com or investor

on daily basis where as various website has been used for secondary data which mainly

pertains to long term analysis.

3.4 DATA ANALYSIS

Data analysis is done on the data collected from both the primary and secondary sources.

The main technical tools used are Candlesticks Pattern, Trend lines and Fibonacci

retracements.

Trader must invest after thorough understanding and analysis of Market

condition .Market analysis is generally done by getting data from various resources

especially

current trend and movements. Trading activity in equity is done online during market

hours from 10:00 am to 3:30 pm (Monday to Friday).Generally very sensitive online

software like Metastock is being used to see and analyse current day today market

movements. Various software tools giving information or indication on market

movements which are usually used by technical analysts at High end are as follow

Metastock

Investar

Spider

Even brokerage houses are also providing online trading tools with facilities of trading to

there clients as per specific requirements. Below are the Trading tool snap shot giving

online information of equities pertaining to Last trading price, High and low.

Trading software generally provided by various brokerage houses to its clients is

ODIN .Shown here is the snapshot of ODIN online window with various functionalities

like price watch, order entry, order book etc.

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These types of trading tools just gives a online platform to see online prices and execute

buying and selling activities but these doesn’t provide enough information on analytical

information or insight as when to buy or sell. So we can say these may provide just data

but no analysis.

Analytical aspect is taken care by Technical analyst by looking at the various Technical

indicators like Line and Candlesticks charts and Oscillators. Technical analysts know

how to read various indicators and interpret how the market will behave in short and long

term. So here we will study and analyze secondary and primary data taken from from

various Tools and website keeping in mind both long term and short term perspectives.

Our study mainly concentrate on nifty charts.

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Analysis based on different parameter is as follow

3.4.1 Trendlines

Here we have nifty line chart from 1991 to 2000 showing market behaviour in long term

with the help Trendline as indicator. So a long term investor can get selling and buy

signal by see-

Ing and studying trendlines. We can also observe the cyclic up and down movement of

the market for 10 years .Here we are clearly getting buy signal below 900 and respective

selling signal at more than 300 points profit. In the last rally after getting buy signal

below 900, nifty rose as high as 1500 .So trend line speak a lot about price movement in

long term which is clearly evident from the line graph.

3.4.2 Volume

Along with trendlines volume movement is also used as indicator which generally

confirms the move of the market as a indicator.

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Here the line graph shows an upward movement 2003 onwards with the help of trend line

which is clearly being confirmed by rising volume. Also fall in volume during July –

august 2008 predicted the fall of market in near future. So we can say that volume also

plays important role as confirmatory indicator along with upward or downward trend.

3.4.3 Exponential Moving Averages

Exponential Moving Averages calculated with short and long period also gives vital

information about nifty movements and reversal signals thus providing information about

when to enter or exit market. Long and short term EMA Crossover gives buy and sell

signal as evident from the chart.

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Candlestick pattern below shows highly volatile market period between July 2008 and

June 2008.This period has been a very volatile period full of major events. After a

downward rally which is shown by percentage retracement from 4500 level to 2500 level

with in 2 months, market became range bound for almost 4 months and again

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After March market saw an upward rally from levels of 2500 to 4250 which is shown by

Fibonacci retracement.

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3.4.4 Resistance and support

After upward or downward movements many a time market movements become sluggish

on both upward and downward direction, such type market is called range bound market.

Here we can see from the chart below that market is range bound between Nov 2008 and

March 2009 though both side of this period market remained highly volatile.

Here from the candlesticks chart Hammer formation after downward rally indicated

reversal of the market move. After this market moved in range with lower support at

2500 and upper resistance at 3328. But the breaking of upper resistance in beginning of

April confirmed the upward rally.

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3.4.5 Oscillators

Oscillators like Relative Strength Index (RSI), MACD and Stochastic are also

prominently used for confirmation of moves given by Trends .Especially when market

becomes range bounds and moves sideways in low range , it is prudent to use oscillators

for Buying and selling signals. As seen from the graph below for range bound market,

indicators like RSI, MACD and Stochastics gives frequent indication of buying or selling.

Though this sideways market is risky to invest but still range is from 2600 to 3100 thus

giving a range of 500 points to play. So to be on safer side in such market one should use

Oscillators in such markets.

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3.4.6 Fibonacci and Percentage Retracement

If we critically analyze market in the near term from 9th March to 20th May, it had

clearly followed Fibonacci retracement by retracing from 50 % to 61.8% gaining almost

200 points near 4th May and then again retracing from 61.8 % to 100% with gain of 700

points after election results. Thus we see here that such events of uncertainty can lead to

anything ,heavy gains as well as heavy losses if speculations are wrong but technical’s

like Fibonacci retracement give the clear picture of risk quantum.

On Friday just before the declaration of election results there was uncertainty about the

market movement as the stability of Government affects the market a lot which evident

from the market during this election.

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3.4.7 Volatility during elections

Generally during election phase and till the results are announced, uncertain conditions

prevail which make the market volatile. There are unanswered questions like which

Government will be in power and what will be the policy map? So investment should be

done cautiously and prudently during election phase.

Period of just 40 months from 1996 to 1999 saw 3 Loksabha elections due unstable

coalition governments which resulted into highly volatile market during this period.

Below chart from 1994 to 1997 shows that 1996-1997 phase remained highly volatile

with high frequency of ups and downs.

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Chart below also shows erratic behavior of market during 1997-1999 due to unstable

govt. because of lack majority with any single party.

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On the contrary when on Oct 13, BJP Government came into with stability and remain in

power for 5 years ,market also followed a trend .At the same time at completion of term

of BJP Government and Congress being the next Govt. in power on 13th May

2004,Market saw a sudden fall.

Recently after the results of these election also on 18th May 2009, again Market saw a

sudden surge and first time in history of India stock market it experienced 2 upper circuit

with minutes of opening on Monday. Reason may be the same Government again coming

back to power with full majority.

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3.4.8 Candlesticks

Candlesticks pattern is highly sophisticated technique where specific patterns of candles

in a candlestick chart are identified which give prior indication of market movements.

Here we have captured some real time daily data on candlestick charts and market

movement analysis has been made accordingly.

In the candlestick chart for 3rd June, 2009 there few pattern formations which give

indication for future market moves. At 11am formation of Evening Star pattern indicated

that market is ready for reversal which is further strengthened by formation of Three

Inside Down. With in one hour of this confirmatory signal market slide down by 80 nifty

points. Further reversal of downward trend takes place with Hammer formation and trend

shift upwards.

But sometimes market moves in very narrow range as in this case of 27th May, 2009,

where market moved in narrow range till 1:30pm as per candlestick pattern. So in such

scenario investor is not sure about the continuation of pattern. Here comes the role of

Oscillators which give early indication to take buying or selling position. In this specific

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case being discussed RSI and Stochastic Indicator give early signal about the downward

trend, thus giving investor to short his position in advance.

Early formation of Two Bullish Engulfing Pattern on 4th June, 2009, gives indication of

upward market movement so investor can go long for time being. These indication are

also confirmed by EMA crossovers.

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In this we observe that its very simple to analyse and intpret Candlestick charts and thus

thus providing valuable insight to investor.

Finally we see that various indicators used being used in Technical analysis of stock

market are very helpful to make critical decision about investment timings with

preciseness.

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CHAPTER 4

CONCLUSION

4.1 FINDINGS OF THE STUDY

It is observed from the analysis of the primary data that Technical analysis is of great

significance while investing in equities or commodities. It provides right signal at right

time in most of the cases. Use of various indicator makes the analytical task a lot easier

and thus help greatly in indecisive times. As observed during various major events like

Election, Budget etc one must be very cautious and should Technical indicators keeping

in mind short term perspective. Besides this, trend along with confirmation from volume

activities and Oscillators provide buying and selling signal especially from long term

perspective.

4.2 RECOMMENDATIONS

Technical analysis is helpful in more than 80% cases but still there is need to decide trade

off between profit and loss. So investment must be done prudently.

Risk should be minimized while uncertain period by hedging your investment or keeping

away from market during volatile times if we are not sure of which way the market will

move. Generally when market becomes range bound and we are not in position to find

out which way the market will move, we should liquidate our positions.

We should always keep in mind whether we are investing for long term or short term and

accordingly we should analyze the situation. For short term, along with trend we must

also look for what the confirmatory indicator say.

Along with Technical analysis, one must keep track records of Fundamental analysis as it

makes overall analysis more precise.

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4.3 LIMITATIONS AND FURTHER SCOPE OF STUDY

Time scale for data used is more than 10 min ,so for better results time scale must be

minimized to minimum possible so that very sensitive results can be produced.

Due to Limited resources and limited time analysis remained confined to Nifty index and

to random small sample, so analysis may not exactly same for the whole population.

Further study can be taken up by exploring different industrial sector along with Nifty

and sample horizon could be increased to maximum possible. Raw data should be

extracted from more advanced trading tools like Metastock so that sensitivity and

accuracy of analysis could be maximized.

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REFERENCESwww.investopedia.com/technical analysis

www.bseindia.com

www.nseindia.com

www.moneycontrol.com

John J.Murphy- Technical Analysis of Financial Markets

Steven B. Achelis- Technical Analysis from A-Z

Capitaline plus

Investar

Company database

Metastock

http://www.icharts.in/charts.html

http://indialivecharts.com/charts.aspx?Name=NSE%20NIFTY&ID=2

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BIBLIOGRAPHY Donald E. Fisher and Ronald J. Jordan, “Security Analysis And Portfolio

Management”.

V.A. Avadhani, “Investment and Security Markets In India”.

Getting Started in Technical Analysis" 1999 Jack D. Schwager.

Taylor, Mark P., and Helen Allen (1992). "The Use of Technical Analysis in the

Foreign Exchange Market," Journal of International Money and Finance.

V.K. Bhalla “Investment Management: Security Analysis And Portfolio

Management”.

John J. Murphy, Technical Analysis of the Financial Markets.

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ANNEXURE

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