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Glossary of Technical Analysis Terms for Futures ContractsThe following information is provided without warranty of any kind. Alpha-Beta Trend Channel Arms Ease of Movement Average True Range Bollinger Bands Candlestick Charts Chaikin Oscillator
Commodity Channel Index (CCI) Commodity Selection Index Cutler's RSI Demand Aggregate Demand Index Detrend Directional
Movement Index Elliott Wave Fibonacci Ratios and Retracements Gann Square Haurlan Index Online Stock Trading Commodity
Commodities Derivatives Future and options future options broker forex tips investment advisor advisorscourse investor
learn what is Technical analysis Fundamentals of Stock equity metal power Head & Shoulder Pattern Herrick Payoff Index Kagi Chart MACD (Moving Average Convergence/Divergence) McClellan Oscillator Momentum Moving Averages Norton High/Low Indicator Notis %V On Balance Volume Parabolic (SAR) Point & Figure Charts Price Patterns Random Walk Index Rate of Change Relative Strength Index Renko Chart Stochastic Stoller STARC Bands Swing Index Time Cycles Trading Index Trix Volume Accumulation Volatility Alpha-Beta Trend ChannelThe Alpha-Beta Trend Channel study uses the standard deviation of price variation to establish two trend lines, one above and one below the
moving average of a price field. This creates a channel (band) where the great majority of price field values.will occur.
Arms Ease of MovementDeveloped by Richard W. Arms, Jr., this analysis routine expands on Mr. Arms' Equivolume charting tool by quantifying the shape aspects of the
plotted boxes. The purpose of this quantifying is to determine the ease, or lack thereof, with which a particular issue is able to move in one
direction or another. The ease with which an issue moves is a product of a ratio between the height (trading range) and width (volume) of the
plotted box. In general, a higher ratio results from a wider box and indicates difficulty of movement. A lower ratio results from a narrower box and
indicates easier movement. This ratio is then related to a comparison between today's and yesterday's trading-range midpoint values to determine
the ease of movement value (EMV). A moving average is then applied to the EMV value - the moving average period can be varied in order to make
the EMV flexible as a trading tool.
Average True RangeTrue range is the greatest of the following differences:
Today's high to today's low Today's high to yesterday's close Today's low to yesterday's close The range is normally the "high - low". However, any time the value of yesterday's close is not within the range of today's bar, rule b) or rule c)
applies. As with most other indicators, the periodic value is summed and smoothed to create the final indicator.
Bollinger BandsBollinger Bands plot trading bands above and below a simple moving average. The standard deviation of closing prices for a period equal to the
moving average employed is used to determine the band width. This causes the bands to tighten in quiet markets and loosen in volatile markets.
The bands can be used to determine overbought and oversold levels, locate reversal areas, project targets for market moves, and determine
appropriate stop levels. The bands are used in conjunction with indicators such as RSI, MACD histogram, CCI and Rate of Change. Divergences
between Bollinger bands and other indicators show potential action points. As a general guidline, look for buying opportunities when prices are in
the lower band, and selling opportunities when the price activity is in the upper band.
Candlestick ChartsMethod of drawing stock (or commodity) charts which originated in Japan. Requires the presence of Open, High, Low and Close price data to be
drawn. There are two basic types of candels, the white body and the black body. As with regular bar charts, a vertical line is used to indicate the
periods (normally daily) high to low. When prices close higher than they opened a white rectangle is drawn on top of the high-low line. This
rectangle originates at the opening price level and extends up towards the closing price. A down day is drawn in black. The combination of several
candles results in patterns (with names like "two crows" or "bullish englufing patern") which give insight into future price activity. For other
Japanese charting approaches also see Renko and Kagi charts.
Chaikin OscillatorThe Chaikin Oscillator is created by subtracting a 10 period exponential moving average of the Accumulation/Distribution line from a 3 period moving
average of the Accumulation/Distribution Line.
Commodity Channel Index (CCI)The CCI is a timing system that is best applied to commodity contracts which have cyclical or seasonal tendencies. CCI does not determine the
length of cycles - it is designed to detect when such cycles begin and end through the use of a statistical analysis which incorporates a moving
average and a divisor reflecting both the possible and actual trading ranges. Although developed primarily for commodities, the CCI could
conceivably be used to analyze stocks as well.
Forumla: CCI=(M-MAVG)/(0.015xDAVG)
M=1/3 (H+L+C) H=Highest price for a period L=Lowest price for a period C=Closing price for a period MAVG=N-period simple moving average
of M DAVG= 1/n x SUMi=1 to n (ABS(MI-MAVG))
Commodity Selection IndexThe Commodity Selection Index is related to the Directional Movement Index. Whereas the ADXR plot of the DMI is used to rate contracts from the
longer term, trend-following point of view, the CSI is used to rate items in the more volatile short term. The Commodity Selection Index takes into
account the ADXR from the Directional Movement Index, the Average True Range, the value of a one cent move as well as margin and commission
requirements. The higher the CSI rating, the more attractive an item is for trading.
Cutler's RSICutler's RSI is a slight variation of Welles Wilder's original Relative Strength Index. The RSI is a momentum oscillator used to identify overbought
and oversold conditions by keying on specific levels, generally 30 and 70, on a chart scaled from 0 to 100. The study can also be used to detect the
following:
Movement which might not be as readily apparent on the bar chart Failure swings above 70 or below 30 which indicate reversals Support and resistance Divergences between RSI and price Cutler's RSI is calculated as follows:
RSI = 100 - (100 / ( 1 + RS ) ) RS = UPAV:x / DNAV:x, and . . . UPAV:x = (E, period's Closes UP) / period DNAV:x = (z: period's Closes DOWN) / period A Close UP (or DOWN) = CLOSE - CLOSE previous If the difference is positive, it is a Close UP. If the difference is negative, the sign is changed and it is a Close DOWN.
Demand AggregateThe Demand Aggregate is used similarly as the Demand Index but adds Open Interest as a consideration in the formula. In its simplest terms, the
system confirms price trends by analyzing concurrent Volume and Open Interest trends. For example, a rise in price, coupled with rising Volume and
Open Interest figures, is considered a bullish indicator. Interpretations are made with respect to the relationship between the movement of Volume,
Open Interest, and Price.
Demand IndexThe Demand Index is a leading indicator which combines volume and price data in such a way as to indicate a change in price trend. It is designed
so that at the very least it is a coincidental indicator, never a lagging one. The calculation of this index is relatively complex. This analysis is based
on the general observation that volume tends to peak before prices peak, both in the commodity and stock markets.
Detrend Detrend is simply another interpretation of a moving average. It provides a means of identifying underlying cycles not apparent when the moving
average is viewed in its original form by effectively hiding the major cycles from view. The moving average line is drawn as a straight, horizontal
basis line on the Detrend chart. Price bars are then re-positioned along this line depending on their relation to the moving average line.
Directional Movement IndexDirectional Movement uses a rather complicated set of calculations designed to rate the directional movement of commodities or stocks on a scale
from 0 to 100. For those traders who employ trend-following methods, commodities or stocks rating in the upper end of the scale would be
attractive. Those using non-trending methods, commodities or stocks rating at the lower end of the scale should be considered for trading. At its
most basic, the Directional Movement would affect trading in the following manner: Long positions would be taken when the "+DI" line crosses
over the "-DI" line. Short positions would be taken when the "-DI" line crosses over the "+DI" line. Further components of this index are the ADX
and ADXR lines.
Elliott WaveElliott wave theory goes beyond traditional charting techniques by providing an overall view of market movement that helps explain why and where
certain chart patterns develop. The three major aspects of wave analysis are pattern, time and ratio. The basic Elliott pattern consits of a 5 wave
uptrend followed by a three wave correction. Each "leg" of a wave in turn consists of smaller waves. Elliott waves can be used to successfully
define where the market currently is in relation to "the big picture" but is usually to unreliable for short term trading.
Fibonacci Ratios and RetracementsThey can be applied both to price and time, although it is more common to use them on prices. The most common levels used in retracement
analysis are 61.8%, 38% and 50%. When a move starts to reverse the 3 price levels are calculated (and drawn using horizontal lines) using a
movements low to high. These retracement levels are then interpreted as likely levels where counter moves will stop. It is interesting to note that
the Fibonacci ratios were also known to Greek and Egyptian mathematicians.The ratio was known as the Golden Mean and was applied in music
and architecture. A Fibonacci spiral is a logarithmic spiral that tracks natural growth patterns.
Gann SquareThe Gann Square is a mathematical system for finding support and resistance based upon a commodity or stock's extreme low or high price for a
given period. Attainment of a particular price level in a square tells you the next probable price peak or valley of future movement. The probable
price levels tend to be more reliable if they are extrapolated from Gann Square values along one of the major axes of the Gann Square. The Gann
Square is generated from a central value, normally a all-time or cyclical high or low. If a low is used, the numbers are incremented by a constant
amount to generate the Gann Square. If a high is used, the numbers are decremented during the square generation.
Haurlan IndexThis indicator is calculated daily from the plurality of NYSE advances over declines. There are three components of the Haurlan index: Short Term,
Long Term and Intermediate Term.
1) Short Term. A 3-day exponential moving average is taken of the net NYSE advances over declines, measuring the short term condition of the
market. When this index moves above +100, a market short term buy signal is generated. The signal is in effect until the market drops below -150
at which time a sell signal is generated. The sell signal remains in effect until the index moves above +100 again.
2) Intermediate Term. Same as above but with a 20-day exponential moving average. This index is considered the most important of the three.
Market buys and sells are determined in this index by the crossing of trend lines or support/resistance levels depending on the particular market in
question. For example, when the market is basing out in preparation for an uptrend, a resistance level may be set up. Once its value is determined,
buy and sell signals could be generated for that market.
3) Long Term. Same as above except for a 200-day exponential moving average. Useful for determining trends but not for signals.
Head & Shoulder PatternAlso can be inverted. A reversal pattern that is one of the more common and reliable patterns. It is comprised of a rally which ends a fairly
extensive advance. It is followed by a reaction on less volume. This is the left shoulder. The head is comprised of a rally up on high volume
exceeding the price of the previous rally. And the head is comprised of a reaction down to the previous bottom on light volume. The right shoulder is
comprised of a rally up which fails to exceed the height of the head. It is then followed by a reaction down. this last reaction down should break a
horizontal line drawn along the bottoms of the previous lows from the left shoulder and head. This is the point in which the major decline begins.
The major difference between a head and shoulder top and bottom is that the bottom should have a large burst of activity on the breakout.
Herrick Payoff IndexThis is a commodity trading tool, useful for the early spotting of changes in price trend direction. The Payoff Index is best used to distinguish trends
that are destined to continue from those that will most likely be short-lived. The Payoff Index is a commodity trading tool that is useful in the early
identification of changes in the direction of price trends. The Payoff Index frequently helps distinguish between a rally in a trend that is destined to
continue and a significant trend change that will provide a worthwhile trading opportunity. The Payoff Index tends to give coincident signals within
a day or two before a significant change in price trend. This advance action is accomplished through use of trading volume and contract open
interest to modify the price action. Analysts have observed that volume trends often change before a price-trend change. There are also generally
accepted relationships between the price trend and the trend of open interest.
Kagi ChartLike Candlestick and Renko charts, Kagi charts come from Japan and were made popular in the USA by Steve Nison. Kagi charts display a series of
connecting vertical lines where the thickness and direction of the lines are dependent on the price action. If closing prices continue to move in the
direction of the prior vertical Kagi line, then that line is extended. However, if the closing price reverses by a pre-determined "reversal" amount, a
new Kagi line is drawn in the next column in the opposite direction. An interesting aspect of the Kagi chart is that when closing prices penetrate the
prior column's high or low, the thickness of the Kagi line changes.
MACD (Moving Average Convergence/Divergence)The MACD is used to determine overbought or oversold conditions in the market. Written for stocks and stock indices, MACD can be used for
commodities as well. The MACD line is the difference between the long and short exponential moving averages of the chosen item. The signal line
is an exponential moving average of the MACD line. Signals are generated by the relationship of the two lines. As with RSI and Stochastics,
divergences between the MACD and prices may indicate an upcoming trend reversal.
McClellan OscillatorThis index is based on New York Stock Exchange net advances over declines. It provides a measure of such conditions as overbought/oversold and
market direction on a short-to- intermediateterm basis. The McClellan Oscillator measures a bear market selling climax when it registers a very
negative reading in the vicinity of -150. A sharp buying pulse in the market would be indicated by a very positive reading, well above 100.
MomentumMomentum provides an analysis of changes in prices (as opposed to changes in price levels). Changes in the rate of ascent or descent are plotted.
The Momentum line is graphed positive or negative to a straight line representing time. The position of the time- line is determined by price at the
beginning of the Momentum period. Traders use this analysis to determine overbought and oversold conditions. When a maximum positive point is
reached, the market is said to be overbought and a downward reaction is imminent. When a maximum negative point is reached, the market is said
to be oversold and an upward reaction is indicated.
Moving AveragesThe moving average is probably the best known, and most versatile, indicator in the analysts tool chest. It can be used with the price of your choice
(highs, closes or whatever) and can also be applied to other indicators, helping to smooth out volatility. As the name implies, the Moving Average is
the average of a given amount of data. For example, a 14 day average of closing prices is calculated by adding the last 14 closes and dividing by 14.
The result is noted on a chart. The next day the same calculations are performed with the new result being connected (using a solid or dotted line)
to yesterday’s. And so forth. Variations of the basic Moving Average are the Weighted and Exponential moving averages.
Norton High/Low IndicatorThe Norton High/Low Indicator uses results from the Demand Index and the Stochastic study and is designed to pick tops and bottoms on long term
price charts. Two lines are generated: the NLP line and the NHP line. The system also uses level lines at -2 and -3. The NLP line crossing -3 to the
downside is the signal that a new bottom will occur in 4-6 periods, using daily, weekly, or mnthly data. Similarly, the NHP line crossing -3 to the
downside indicates a new top in the same time frame. The indicator tends to be more reliable using longer term data (weekly or monthly). When
either indicator drops below the - 3 level, a reversal may be imminent. The reversal (or hook) is the signal to enter the market. For greater reliability,
use the Norton High/Low Indicator together with other studies for confirmation.
Notis %VA way to measure volatility is to measure the daily ranges between the high and the low. Volatility is high when the daily range is large and low
when the daily range is small. The Notis %V study contains two separate indicators. It divides market volatility into upward and downward
components (UVLT and DVLT). Both are plotted separately in the same window, and can be plotted as an oscillator. The upward component is also
compared to the total volatility (UVLT + DVLT) and expressed as a percentage; thus the name, %V. Volatility can be a key to options trading. A
good sense of market volatility can help you avoid those frustrating times when the market moves your way but your option still loses value.
On Balance Volume (OBV)OBV is one of the most popular volume indicators and was developed by Joseph Granville. Constructing an OBV line is very simple: The total volume
for each day is assigned a positive or negative value depending on whether prices closed higher or lower that day. A higher close results in the
volume for that day to get a positive value, while a lower close results in negative value. A running total is kept by adding or subtracting each day's
volume based on the direction of the close. The direction of the OBV line is the thing to watch, not the actual volume numbers.
Formula: OBV=SUM(C-CP)/(ABS(C-CP)xV)
C=Today's Close CP=Yesterday's Close V=Today's Volume
Parabolic (SAR)The Parabolic is a Time/Price system for the automatic setting of stops. The stop is both a function of price and of time. The system allows a few
days for market reaction after a trade is initiated after which stops begin to move in more rapid incremental daily amounts in the direction the trade
was initiated. For example, when a long position is taken the stop will move up regardless of price direction. However, the distance that the stop
moves up is determined by the favorable distance the price has moved. If the price fails to move favorably within a certain period of time, the stop
reverses the position and begins a new time period.
Point & Figure ChartsThe Point and Figure (PF) charting method is a technique that has been used for many years in analyzing the variations in prices of stocks and
commodities. There are several types of PF charting methods. Some employ trend lines, resistance levels, and various other additions to the chart.
In this study, we shall be concerned with only daily reversal type charts. The principal advantage of a PF chart is that it is much easier to read and
interpret than other types of charts. All the small, and often confusing, price movements are eliminated, and only the most important features of the
price action remain. It would be reasonable to think of this method as a filter that (hopefully) allows only meaningful information to enter the chart
and ultimately the decision process. Two basic symbols are used:
X Denotes the continuance of an increase in price and is always "stacked" in the vertical direction.
O Denotes the continuance of a decrease in price and is always "stacked" in the vertical direction.
While prices are rising X's are used. When falling, O's are used. They are always plotted on rectangular grid graph paper such that columns of X's
and O's alternate. A Point and Figure chart is characterized by the specification of two parameters: box size and reversal number. The box size
dictates the price range associated with a particular box (cubical area within the grid), while the reversal number specifies the conditions which
terminate a column of X's and begin a column of O's and vice-versa.
Price PatternsPrice Patterns are formations which appear on commodity and stock charts which have shown to have a certain degree of predictive value. Some
of the most common patterns include: Head & Shoulders (bearish), Inverse Head & Shoulders (bullish), Double Top (bearish), Double Bottom
(bullish), Triangles, Flags and Pennants (can be bullish or bearish depending on the prevailing trend).
Randow Walk IndexThis indicator is defined as the ratio of an acutal price move to the expected random walk. If the move is greater than a random walk, and thus a
trend is present, its index will be larger that 1.0
Rate of ChangeRate of Change is used to monitor momentum by making direct comparisons between current and past prices on a continual basis. The results can
be used to determine the strength of price trends. Note: This study is the same as the Momentum except that Momentum uses subtraction in its
calculations while Rate of Change uses division. The resulting lines of these two studies operated over the same data will look exactly the same -
only the scale values will differ.
RSI - Relative Strength IndexThis indicator was developed by Welles Wilder Jr. Relative Strength is often used to identify price tops and bottoms by keying on specific levels
(usually "30" and "70") on the RSI chart which is scaled from from 0-100. The study is also useful to detect the following:
Movement which might not be as readily apparent on the bar chart Failure swings above 70 or below 30 which can warn of coming reversals Support and resistance levels Divergence between the RSI and price which is often a useful reversal indicator The Relative Strength Index requires a certain amount of lead-up time in order to operate successfully.The formula for calculating the RSI is:
rsi=100-(100/1-rs) rs= average of x day’s up closes divided by average of x day’s down closes Renko ChartThe Renko charting method probably got its name from "renga", which is the Japanese word for bricks. Introduced by Steve Nison, a well-known
authority on the Candlestick charting method, Renko charts are similar to Three Line Break charts except that in a Renko chart, a line is drawn in
the direction of the prior move only if a fixed amount (i.e., the box size) has been exceeded. The bricks are always equal in size. Example: With a
five unit Renko chart, a 20 point rally is displayed as four equally sized, five unit high Renko bricks.
StochasticThe Stochastic Indicator is based on the observation that as prices increase, closing prices tend to accumulate ever closer to the highs for the
period. Conversely, as prices decrease, closing prices tend to accumulate ever closer to the lows for the period. Trading decisions are made with
respect to divergence between % of "D" (one of the two lines generated by the study) and the item's price. For example, when a commodity or
stock makes a high, reacts, and subsequently moves to a higher high while corresponding peaks on the % of "D" line make a high and then a lower
high, a bearish divergence is indicated. When a commodity or stock has established a new low, reacts, and moves to a lower low while the
corresponding low points on the % of "D" line make a low and then a higher low, a bullish divergence is indicated. Traders act upon this divergence
when the other line generated by the study (K) crosses on the right-hand side of the peak of the % of "D" line in the case of a top, or on the
right-hand side of the low point of the % of "D" line in the case of a bottom. Two variations of the Stochastic Indicator are in use: Regular and Slow.
When the Regular plot of the Stochastic too choppy, the "Slow" version can often clarify the results by reducing the sensitivity of the calculations.
The formula is:
Note: 5 Days is the most commonly used value for %K %K=100 {(C-L5)/(H5-L5)}
The %D line is a 3 day smoothed version of the %K line %D=100(H3/L3) where H3 is the 3 day sum of (C-L5) and L3 is the 3 day sum of (H5-L5)
Stoller STARC BandsSTARC bands create a channel surrounding a simple moving average. The width of the created channel varies with a period of the average range;
thus the name ('ST' for Stoller, plus 'ARC' for Average Range Channel). STARC Bands, in a fashion similar to Bollinger Bands, will tighten in steady
markets and loosen in volatile markets. However, rather than being based on closes, the STARC Bands are based on the average true range, thus
giving a more in depth picture of the market volatility. While the penetration of a Bollinger Band may indicate a continuation of a price move, the
STARC Bands define upper and lower limits for normal price action.
Swing Index The Swing Index (primarily for use with commodity trading) attempts to determine real market direction, and changes in direction, by making use of
the most significant comparisons between the results (Open-High-Low-Close) of the current and previous days' trading.
Time CyclesSome analysts believe that price analysis alone only offers half the information needed for successful trading. The other part is time, more exactly
time cycles, which give actual insight into understanding the movements of markets. Common cycles are the seasonal cycles apparent in many
commodity markets, but cylces can be detected on intra-day charts as well.
Trading IndexThis index (also kown as the "Arms" index, or "TRIN") measures the relative strength of volume associated with advancing stocks against the
strength of volume associated with declining stocks. When used as a short term indicator, readings below 1.0 are considered bullish while readings
above 1.0 are considered bearish. An extreme bearish reading would be 1.5 or higher; an extreme bullish reading would be .5 and lower. Readings of
2.0 or .3 would be considered "climactic". For the intermediate term, a bearish sign is an index over 1.0, bullish under 1.0. For the long term, the
Trading Index can be viewed as an overbought / oversold indicator.
Trix Single linear exponential smoothing was developed in the early 1950s as a means of prediction along a straight line whose slope was based on
previous data. The Triple Exponential Smoothing Oscillator (Trix) has now been developed to act on trends of a higher order than linear. Trix uses a
one-day momentum of a triple exponential smoothed price series to produce an indicator which is cycle dependent. Changes in the Trix direction are
less prone to whipsaws than standard cycle-momentum indicators. The period is chosen to filter out any insignificant cycles shorter than the period.
Fourier Analysis or visual observation may be used to find the proper cycle length of a given market. Raising the number of days will remove more
small cycles and smooth out the oscillator, but at the loss of sensitivity. The more smoothing that is applied to the data, the more of a lag in the
oscillator, but not nearly the lag of a normal moving average.
Volume AccumulationThis volume indicator addresses some of On Balance Volume's shortcomings and was developed by Marc Chaikin. Where OBV assigns all of a day's
volume a positive or negative value, Volume Accumulation counts only a percentage of the volume as positive or negative, depending on where the
close is in relation to the average price of the day. The only time the entire day's volume is assigned a positive value is when the close is the same
as the day's high. The opposite applies for a close at the day's low.
VolatilityThis analysis is based on the idea that stocks bottom from "panic" selling, after which a rebound is imminent. One way of measuring this
phenomenon is to observe a widening range between high and low prices each day. In general a progressively wider range, observed over a
relatively short period of time, can indicate that a bottom is near. Price tops are generally reached at a more leisurely pace and can be characterized
by a narrowing of the price range. This measure of the trading range takes place over a specified period in order to determine whether or not an
issue is being "dumped" and is approaching a bottom. A pre-requisite to a valid bottom is an increase in the volatility line above the reference line. In
a similar manner, an indication of an imminent top would be a decrease in the volatility line below the reference line. As long as volatility is rising, in
all probability a stock will not approach a top. It should be noted that this study should be used in conjunction with trend following analyses and
momentum oscillators for confirmation and accuracy.
Types of Stocks Stock Common stock Preferred stock Outstanding stock Treasury stock Trading Stock Participants: Market maker Exchanges: Stock exchange List of stock exchanges New York Stock Exchange NASDAQ Toronto Stock Exchange London Stock Exchange Euronext Frankfurt Stock Exchange Tokyo Stock Exchange Hong Kong Stock Exchange Australian Securities Exchange Stock Valuation Trading Theories: Dow Theory Elliott Wave Theory Fundamental analysis Technical analysis Mark Twain effect January effect Efficient market hypothesis Stock Pricing: Dividend yield Gordon model Income per share Book value Earnings yield Beta coefficient Ratios: Financial ratio P/CF ratio PE ratio PEG ratio Price/sales ratio P/B ratio Stock Related Terms Dividend Stock split Growth stock Investment Speculation Trade Day trading Aluminum Arecanut Basmati Rice Brent Crude Oil Cardamom Cashew Castor Seeds Caster Seeds Castor Oil Chana Chilli
Coconut Oil Coffee Copper Copra Cotton Cotton Seed Cotton Seed Oil Cotton Yarn Crude Oil Crude Palm Oil Cumin Seed(Jeera)
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Linseed Oil M E Sour Crude Oil Maize Masur Mentha Oil Mustard Oil Mustard Seed Mustard Seed Oil Natural Gas Nickel Pepper
Polypropylene(PP) Potato (Agra) Potato (Tarkeshwar) PVC RBD Palmolein Refined Soy Oil Refined Sunflower Oil Rice Rice Bran
Refined Oil Rubber Safflower Safflower Oil Sarbati Rice Sesam Oil Silver Soy Meal Soyabean Oil Soybean Sponge Iron Steel
Sugar Sunflower Oil Sunflower Seed Tin Tur Urad Wheat Yellow Peas 3i infotech acc aban offshore adani enterpris adhunik
metalik advanta aftek alembic ambika cotton aptech arvind mills ashok leyland assam company atul autolite india bag films
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Technical analysis is the study of past financial market data, primarily through the use of charts, to forecast price trends and make investment
decisions.[1] In its purest form, technical analysis considers only the actual price behavior of the market or instrument, based on the premise that
price reflects all relevant factors before an investor becomes aware of them through other channels.
Technical analysis is widely used among traders and financial professionals, and some studies say its use is more widespread than is
"fundamental" analysis in the foreign exchange market.[2][3] Academics such as Eugene Fama say the evidence for technical analysis is sparse and
is refuted by the efficient market hypothesis,[4][5] yet some Federal Reserve and academic studies include evidence that supports technical
analysis.[6][7][8] MIT finance professor Andrew Lo argues that "several academic studies suggest that…technical analysis may well be an
effective means for extracting useful information from market prices."[9] But as Burton Malkiel argues, "Technical analysis is anathema to the
academic world."[10]
Contents [hide]1 General description 2 History 3 Principles of technical analysis 3.1 Market action discounts everything 3.2 Prices move in trends 3.3 History tends to repeat itself 4 Criticism 4.1 Lack of evidence 4.1.1 Efficient market hypothesis 4.1.2 Random walk hypothesis 5 Industry 6 Use of technical analysis 7 Systematic trading and technical analysis 7.1 Neural networks 7.2 Rule-based trading 8 Combining Technical Analysis with other Market Forecast Methods 9 Charting terms and indicators 10 Books 11 Notes 12 See also 13 External links
General descriptionTechnical analysts (or technicians) identify non-random price patterns and trends in financial markets and attempt to exploit those patterns.[1]
While technicians use various methods and tools, the study of price charts is primary. Technicians especially search for archetypal patterns, such
as the well-known head and shoulders reversal pattern, and also study such indicators as price, volume, and moving averages of the price. Many
technical analysts also follow indicators of investor psychology (market sentiment).
Technicians seek to forecast price movements such that large gains from successful trades exceed more numerous but smaller losing trades,
producing positive returns in the long run through proper risk control and money management.
There are several schools of technical analysis. Adherents of different schools (for example, candlestick charting, Dow Theory, and Elliott wave
theory) may ignore the other approaches, yet many traders combine elements from more than one school. Technical analysts use judgment gained
from experience to decide which pattern a particular instrument reflects at a given time, and what the interpretation of that pattern should be.
Technical analysts may disagree among themselves over the interpretation of a given chart.
Technical analysis is frequently contrasted with fundamental analysis, the study of economic factors that some analysts say can influence prices in
financial markets. Pure technical analysis holds that prices already reflect all such influences before investors are aware of them, hence the study
of price action alone. Some traders use technical or fundamental analysis exclusively, while others use both types to make trading decisions.
HistoryThe principles of technical analysis derive from the observation of financial markets over hundreds of years.[citation needed] The oldest known
example of technical analysis was a method used by Japanese traders as early as the 18th century,[citation needed] which evolved into the use of
candlestick techniques, and is today a main charting tool.[11][12]
Dow Theory is based on the collected writings of Dow Jones co-founder and editor Charles Dow, and inspired the use and development of modern
technical analysis from the end of the 19th century. Modern technical analysis considers Dow Theory its cornerstone.[13]
Many more technical tools and theories have been developed and enhanced in recent decades, with an increasing emphasis on computer-assisted
techniques.
Principles of technical analysisTechnicians say that a market's price reflects all relevant information, so their analysis looks more at "internals" than at "externals" such as news
events. Price action also tends to repeat itself because investors collectively tend toward patterned behavior -- hence technicians' focus on
identifiable trends and conditions.
Market action discounts everythingBased on the premise that all relevant information is already reflected by prices, technical analysts believe it is redundant to do fundamental
analysis -- they say news and news events do not significantly influence price, and cite supporting research such as the study by Cutler, Poterba,
and Summers titled "What Moves Stock Prices?"
On most of the sizable return days [large market moves]…the information that the press cites as the cause of the market move is not particularly
important. Press reports on adjacent days also fail to reveal any convincing accounts of why future profits or discount rates might have changed.
Our inability to identify the fundamental shocks that accounted for these significant market moves is difficult to reconcile with the view that such
shocks account for most of the variation in stock returns. [14]
Prices move in trendsSee also: Market Trend Technical analysts believe that prices trend. Technicians say that markets trend up, down, or sideways (flat). This basic definition of price trends is
the one put forward by Dow Theory.[1]
AOL TimeWarner price action.An example of a security that had an apparent trend is AOL from November 2001 through August 2002. A technical
analyst or trend follower recognizing this trend would look for opportunities to sell this security. AOL consistently moves downward in price. Each
time the stock rose, sellers would enter the market and sell the stock; hence the "zig-zag" movement in the price. The series of "lower highs" and
"lower lows" is a tell tale sign of a stock in a down trend.[15] In other words, each time the stock edged lower, it fell below its previous relative
low price. Each time the stock moved higher, it could not reach the level of its previous relative high price.
Note that the sequence of lower lows and lower highs did not begin until August. Then AOL makes a low price that doesn't pierce the relative low
set earlier in the month. Later in the same month, the stock makes a relative high equal to the most recent relative high. In this a technician sees
strong indications that the down trend is at least pausing and possibly ending, and would likely stop actively selling the stock at that point.
History tends to repeat itselfTechnical analysts believe that investors collectively repeat the behavior of the investors that preceded them. "Everyone wants in on the next
Microsoft," "If this stock ever gets to $50 again, I will buy it," "This company's technology will revolutionize its industry, therefore this stock will
skyrocket" -- these are all examples of investor sentiment repeating itself. To a technician, the emotions in the market may be irrational, but they
exist. Because investor behavior does repeat itself so often, technicians believe that recognizable (and predictable) price patterns will develop on a
chart.[1]
Technical analysis is not limited to charting, yet is always concerned with price trends. For example, many technicians monitor surveys of investor
sentiment. These surveys gauge the attitude of market participants, specifically whether they are bearish or bullish. Technicians use these surveys
to help determine whether a trend will continue or if a reversal could develop; they are most likely to anticipate a change when the surveys report
extreme investor sentiment. Surveys that show overwhelming bullishness, for example, are evidence that an uptrend may reverse -- the premise
being that if most investors are bullish they have already bought the market (anticipating higher prices). And because most investors are bullish and
invested, one assumes that few buyers remain. This leaves more potential sellers than buyers, despite the bullish sentiment. This suggests that
prices will trend down, and is an example of contrarian trading.
CriticismThe Wall Street Journal Europe states "Whether technical analysis is really useful ... is a matter of some dispute on Wall Street. Some investors
believe that it is impossible to forecast the market's ups and downs. Academic studies have shown that when most people, professionals and
amateurs alike, try to move money in and out of stocks to beat market flucuations, they tend to wind up with losses."[16] The same article shows
how several technical analysts can simultaneously make contradictory predictions.
Lack of evidenceCritics of technical analysis include well known fundamental analysts. For example, Peter Lynch once commented, "Charts are great for predicting
the past." Warren Buffett has said, "I realized technical analysis didn't work when I turned the charts upside down and didn't get a different answer"
and "If past history was all there was to the game, the richest people would be librarians."[1]
Some academic studies say technical analysis has little predictive power, but other studies say it may produce excess returns. For example,
measurable forms of technical analysis, such as non-linear prediction using neural networks, have been shown to occasionally produce statistically
significant prediction results.[17] A Federal Reserve working paper[7] regarding support and resistance levels in short-term foreign exchange rates
"offers strong evidence that the levels help to predict intraday trend interruptions," although the "predictive power" of those levels was "found to
vary across the exchange rates and firms examined."
Cheol-Ho Park and Scott H. Irwin reviewed 95 modern studies on the profitability of technical analysis and said 56 of them find positive results, 20
obtain negative results, and 19 indicate mixed results: "Despite the positive evidence...most empirical studies are subject to various problems in
their testing procedures, e.g., data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and
transaction costs. Future research must address these deficiencies in testing in order to provide conclusive evidence on the profitability of technical
trading strategies."[18]
However, a comprehensive study of the question by Amsterdam economist Gerwin Griffioen concludes that: "for the U.S., Japanese and most
Western European stock market indices the recursive out-of-sample forecasting procedure does not show to be profitable, after implementing little
transaction costs. Moreover, for sufficiently high transaction costs it is found, by estimating CAPMs, that technical trading shows no statistically
significant risk-corrected out-of-sample forecasting power for almost all of the stock market indices."[5]
Efficient market hypothesisThe efficient market hypothesis (EMH) contradicts the basic tenets of technical analysis, by stating that past prices cannot be used to profitably
predict future prices. Thus it holds that technical analysis cannot be effective. Economist Eugene Fama published the seminal paper on the EMH in
the Journal of Finance in 1970, and said "In short, the evidence in support of the efficient markets model is extensive, and (somewhat uniquely in
economics) contradictory evidence is sparse." [19] EMH advocates say that if prices quickly reflect all relevant information, no method (including
technical analysis) can "beat the market." Developments which influence prices occur randomly and are unknowable in advance.
Technicians say that EMH ignores the way markets work, in that many investors base their expectations on past earnings, track record, etc.
Because future stock prices can be strongly influenced by investor expectations, technicians claim it only follows that past prices influence future
prices.[20] They also point to research in the field of behavioral finance, specifically that people are not the rational participants EMH makes them
out to be. Technicians have long said that irrational human behavior influences stock prices, and that this behavior leads to predictable
outcomes.[21] Author David Aronson says that the theory of behavioral finance blends with the practice of technical analysis:
By considering the impact of emotions, cognitive errors, irrational preferences, and the dynamics of group behavior, behavioral finance offers
succinct explanations of excess market volatility as well as the excess returns earned by stale information strategies…. cognitive errors may also
explain the existence of market inefficiencies that spawn the systematic price movements that allow objective TA [technical analysis] methods to
work.[20]
EMH advocates reply that while individual market participants do not always act rationally (or have complete information), their aggregate decisions
balance each other, resulting in a rational outcome (optimists who buy stock and bid the price higher are countered by pessimists who sell their
stock, which keeps the price in equilibrium).[22] Likewise, complete information is reflected in the price because all market participants bring their
own individual, but incomplete, knowledge together in the market.[22]
Random walk hypothesisThe random walk hypothesis may be derived from the weak-form efficient markets hypothesis, which is based on the assumption that market
participants take full account of any information contained in past price movements (but not necessarily other public information). In his book A
Random Walk Down Wall Street, Princeton economist Burton Malkiel said that technical forecasting tools such as pattern analysis must ultimately
be self-defeating: "The problem is that once such a regularity is known to market participants, people will act in such a way that prevents it from
happening in the future." [23]
Technicians say the EMH and Random Walk theories both ignore the realities of markets, in that participants are not completely rational (they can
be greedy, overly risky, etc.) and that current price moves are not independent of previous moves (technicians point to charts similar to AOL
above.)[15][24] Critics reply that one can find virtually any chart pattern after the fact, but that this does not prove that such patterns are
predictable. Technicians maintain that both theories would also invalidate numerous other trading strategies such as index arbitrage, statistical
arbitrage and many other trading systems.[20]
IndustryGlobally, the industry is represented by The International Federation of Technical Analysts (IFTA). In the United States the industry is represented
by two national organizations: the Market Technicians Association (MTA), and the American Association of Professional Technical Analysts
(AAPTA). In Canada the industry is represented by the Canadian Society of Technical Analysts.
Use of technical analysisMany traders say that trading in the direction of the trend is the most effective means to be profitable in financial or commodities markets. John W.
Henry, Larry Hite, Ed Seykota, Richard Dennis, William Eckhardt, Victor Sperandeo, Michael Marcus and Paul Tudor Jones (some of the so-called
Market Wizards in the popular book of the same name by Jack D. Schwager) have each amassed massive fortunes via the use of technical
analysis and its concepts. George Lane, a technical analyst, coined one of the most popular phrases on Wall Street, "The trend is your friend!"
Many non-arbitrage algorithmic trading systems rely on the idea of trend-following, as do many hedge funds. A relatively recent trend, both in
research and industrial practice, has been the development of increasingly sophisticated automated trading strategies. These often rely on
underlying technical analysis principles (see algorithmic trading article for an overview).
Systematic trading and technical analysis
Neural networksSince the early 90's when the first practically usable types emerged, artificial neural networks (ANNs) have rapidly grown in popularity. They are
artificial intelligence adaptive software systems that have been inspired by how biological neural networks work. Their use comes in because they
can learn to detect complex patterns in data. In mathematical terms, they are universal non-linear function approximators[25] [26] meaning that
given the right data and configured correctly, they can capture and model any input-output relationships. This not only removes the need for human
interpretation of charts or the series of rules for generating entry/exit signals but also provides a bridge to fundamental analysis as the variables
used in fundamental analysis can be used as input.
In addition, as ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both mathematically and
empirically tested. In various studies neural networks used for generating trading signals have significantly outperformed buy-hold strategies as
well as traditional linear technical analysis methods.[27] [28] [29]
While the advanced mathematical nature of such adaptive systems have kept neural networks for financial analysis mostly within academic
research circles, in recent years more user friendly neural network software has made the technology more accessible to traders.
Rule-based tradingRule-based trading is an approach to make one's trading plans by strict and clear-cut rules. Unlike some other technical methods or most
fundamental analysis, it defines a set of rules that determines all trades, leaving minimal discretion.
For instance, a trader might make a set of rules stating that he will take a long position whenever the price of a particular instrument closes above
its 50-day moving average, and shorting it whenever it drops below.
Combining Technical Analysis with other Market Forecast MethodsAs defined by John Murphy in his book "Technical Analysis of the Financial Markets", technical analysis cares only about price, volume and open
interest. However, many market strategists extend their research beyond the limited confines of technical analysis to include fundamental analysis.
One such field, known of Fusion Analysis [[2]] argues that overlaying fundamentals with technicals can improve portfolio manager performance.
Another advocate for this is John Bollinger, who coined the term Rational Analysis as the intersection of technical analysis and fundamental
analysis, but considered it strictly within neither field [[3]].
Technical analysis is often seen as a subset or application of behavioral finance.This thinking is exemplified by Professor Hank Pruden of Golden
Gate University who notes, "Predictable human behavior can and does impact markets. One example is the "crowd psychology" or "bandwagon"
theory." Technicians typically claim that chart patterns are the result of market inefficiencies caused by hope, fear and greed. [[4]]
Technical analysts often look at sentiment indicators as well. Put/call ratios, for example, are used to measure whether speculation is in evidence
via extreme levels of put and call purchases and sales. These data, are classically technical analysis as they are based on market-produced
statistics. Other non-market based sentiment indicators would fall more properly into the fields of sentiment analysis or behavioral finance.
Similarly, some analysts may combine technical analysis with other methodologies including, but not limited to, quantitative analysis, economics,
and even financial astrology. For example recent issues of the magazine, Technical analysis of Stocks and Commodities [[5]] included articles on
combining technical and quantitative research using value at risk, as well as articles that cover how to combine fundamental analysis or even
financial astrology with technical methods.
Charting terms and indicatorsWidely-known technical analysis concepts include:
Accumulation/distribution index—based on the close within the day's range Average true range - averaged daily trading range Bollinger bands - a range of price volatility Breakout - when a price passes through and stays above an area of support or resistance Commodity Channel Index - identifies cyclical trends Elliott wave principle and the golden ratio to calculate successive price movements and retracements Hikkake Pattern - pattern for identifying reversals and continuations MACD - moving average convergence/divergence Momentum - the rate of price change Money Flow - the amount of stock traded on days the price went up Moving average - lags behind the price action On-balance volume - the momentum of buying and selling stocks PAC charts - two-dimensional method for charting volume by price level Parabolic SAR - Wilder's trailing stop based on prices tending to stay within a parabolic curve during a strong trend Pivot point - derived by calculating the numerical average of a particular currency's or stock's high, low and closing prices Point and figure charts - charts based on price without time Relative Strength Index (RSI) - oscillator showing price strength Resistance - an area that brings on increased selling Rahul Mohindar Oscillator - a trend indentifying indicator Stochastic oscillator, close position within recent trading range Support - an area that brings on increased buying Trend line - a sloping line of support or resistance Trix - an oscillator showing the slope of a triple-smoothed exponential moving average, developed in the 1980s by Jack Hutson
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