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A Study of Technical analysis on Indian Stock
Markets
Project done in 24 Carat Investments Pvt. Ltd, New Delhi
Vijay Pal
FMG XVII, Roll No. 081061
FORE School of Management, New Delhi
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Vijay Pal
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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:
1) A study of Technical analysis and
2) To analyze Nifty movements with technical analysis indicators
24 Carat Investments Pvt Ltd (a part SMC Global securities Ltd.) is involved in trading in
commodities, Equities and Forex services. 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 ofcurrent market situation.
The 2nd 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.
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.
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
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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 stocks price history, they necessarily drive stock prices
to levels where expected rate of return 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).
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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.
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 35 year
horizon.
DeBondt and Thaler (1985, 1987) found that stocks that were extreme losers over a 35 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 Sharpes (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, hedemonstrated 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.
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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.
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 OHara (1994) show that volume provides information on information
quality that cannot be deduced from the price. They also show that traders who useinformation 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 19811995.
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.
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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.
Fernandez-Rodrguez, Gonzalez-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 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 nave 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 19621996 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.
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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
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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 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:
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1. Market discounts everything.
2. Price moves in trends
3. 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
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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.
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
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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 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 theperiod'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 days 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
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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
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.
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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.
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
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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 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
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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 byusing a nine-day exponential moving average of the MACD values. These values can be
adjusted to meet the needs of the technician and the 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.
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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 securitys 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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The project was done in the Karol Bagh ,Delhi office of 24 Carat Securitie Private Limited.
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 .
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
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or indication on market movements which are usually used by technical analysts at High end are
as follow
1. Metastock
2. Investar
3. 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.
Here is the Online Trading tool provided by Sharekhan to its Classic Account Holder clients
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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.
These types of trading tools just gives a online platform to see online prices and execute
buying and selling activities but these doesnt 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
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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 .
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
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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.
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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Here from the candlesticks chart Hammer formation after downward rally indicated reversalof 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.
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 9 th 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 technicals like Fibonacci
retracement give the clear picture of risk quantum.
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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.
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 whichGovernment 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 inpower 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 18 th 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.
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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
1 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 case being
discussed RSI and Stochastic Indicator give early signal about the downward trend, thus
giving investor to short his position in advance.
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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 analysiof stock market are
very helpful to make critical decision about investment timings with preciseness.
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CHAPTER4
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
1. 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.
2. 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.
3. 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.
4. Along with Technical analysis, one must keep track records of Fundamental analysis
as it makes overall analysis more precise.
4.3 LIMITATIONS AND FURTHER SCOPE OF STUDY
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1. 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.
2. 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.
3. 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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REFERENCES
1) www.investopedia.com/technical analysis
2) www.bseindia.com
3) www.nseindia.com
4) www.moneycontrol.com
5) John J.Murphy- Technical Analysis of Financial Markets
6) Steven B. Achelis- Technical Analysis from A-Z
7) Capitaline plus
8) Investar
9) Company database
10) Metastock
11) http://www.icharts.in/charts.html
12) http://indialivecharts.com/charts.aspx?Name=NSE%20NIFTY&ID=2
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24 carat aimed to spread the information among the investors that may give a paradigm shift
to Indian derivative market. Our belief says that Informed Traders Should Make Better
Trades. Our mission is to value the client requirements.
COMPETITIVE ADVANTAGE
24-catrat investments has a proactive team specialized in three critical areas
Research (In-house and Outsourced)
Operation (Back Office & Trade Desk)
Client help desk
Client services, expertise and information make 24-carat investment an elite fraternity.