Technical Analysis on Indian Stock Markets (1)

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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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