UNDERSTANDING
TECHNICAL ANALYSIS
Moving
Average
A Moving Average is a moving mean of data.
In other words, Moving Averages perform a
mathematical function where data within a
selected period is averaged and the average
‘moves’ as new data is included
in the calculation while older data is removed
or lessened. Moving Averages essentially smooth
data by removing ‘noise’. This
smoothing of data makes Moving Averages popular
tools in identifying price trends and trend
reversals.
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Simple Moving Average
Simple Moving Averages are the most common and popular
form of moving average. The primary reason for this
is the relative ease with which Simple Moving Averages
are calculated.A Simple Moving Average is calculated
by adding values over a set number of periods and
then dividing the sum by the total number of values.
As with other types of moving averages, Simple Moving
Averages smooth the data by removing ‘noise’
over the selected period. The ability to smooth data
makes them a useful tool in identifying price trends
and trend reversals.
Exponential
Moving Average
The Exponential Moving Average is similar to the Weighted
Moving Average in that they both assign greater weight
to the most recent data. Where they differ is that
instead of dropping off the oldest data point in the
selected period of the moving average, the Exponential
Moving Average continues to maintain all the data.
In other words, a 5 day Exponential Moving Average
will contain more than 5 pieces of data information.
Each observation becomes progressively less significant
but still includes in its calculation all the price
data in the life of the instrument.
The
Exponential Moving Average is another method of weighting
a moving average.
Weighted
Moving Average
As with Simple Moving Averages, Weighted Moving Averages
smooth the data by removing ‘noise’ over
the selected period. However a Weighted Moving Average
will be more sensitive to recent changes in data.
This is because a Simple Moving Average gives all
observations equal emphasis in its calculation, but
a Weighted Moving Average assigns a greater weight
to the most recent observations.
In
this example you can see the three types of Moving
Average, simple, weighted and exponential. For this
analysis each moving average is using 14 as the averaging
period.
In this example a Moving Average is being used to
generate buy and sell signals. A close above the Moving
Average is a buy signal and a close below the Moving
Average is a sell signal. Note that this technique
would have been most profitable in the second half
of the analysis when the market was trending down.
In
this example the 100period Moving Average is used
to identify the trend and the 15period and 30period
Moving Averages are used to give crossover buy and
sell signals in the direction of the trend.
The
100 days Moving Average is sloping up and below prices
indicating an up trend, for this reason only long
positions are taken. For example when the 15 period
Moving Average crosses above the 30 period Moving
Average you would take a long position in the market,
when the 15period Moving Average crosses below 30period
Moving Average you would exit the long position but
not enter a short position.
Open interest
Open Interest is the number of outstanding futures
contracts that have not been offset by an opposite
transaction.
In
this example the volume and open interest are increasing
in the first half of the analysis while the prices
are decreasing, in the second half of the analysis
the prices are increasing while the volume and open
interest are decreasing. From this you could expect
the market to turn and continue moving down as the
up-move is losing momentum.
Parabolic
Time Price
Developed by J. Welles Wilder and introduced in his
book New Concepts in Technical Trading Systems, Parabolic
Time Price is a system that always has a position
in the market, either long or short. You would close
out the current position and enter a reverse position
when the price crosses the current Stop And Reverse
(SAR) point. The SAR points resemble a parabolic curve
as they begin to tighten and close in on prices once
prices begin to trend, this explains the name - Parabolic
Time Price.
Parabolic
Time Price is usually charted with a bar analysis
so that the stop and reverse points are easily identified.
If you are long, the SAR points will be below the
prices and the signal to go short will be when prices
cross the current SAR point from above. If you are
short, the SAR points will be above the prices and
the signal to go long will be when prices cross the
current SAR point from below.
When
a new position is entered the SAR points will be positioned
far enough away from the prices to permit some contra-trend
price movement. As the market begins to trend the
SAR points will move with prices and progressively
tighten as the trend continues. This is accomplished
by the use of an acceleration factor that increases
up to a given limit each time a new extreme in the
direction of the trend is reached.
In
this analysis you can see the Parabolic Time Price
SAR points plotted above and below the prices. The
first buy and sell signals are marked on the chart.
You can see that Parabolic Time Price would have been
most effective when the market was in a trending phase,
either to generate buy signals in the direction of
the trend or to identify levels at which to place
a trailing stop if you had a long position in the
market.
Relative
Strength Index (RSI)
Developed by J. Welles Wilder and introduced in his
book New Concepts in Technical Trading Systems.
RSI
calculates the difference in values between the closes
over the Observation Period. These values are averaged,
with an up-average, being calculated for periods with
higher closes and a down-average being calculated
for periods with lower closes. The up average is divided
by the down average to create the Relative Strength.
Finally, the Relative Strength is put into the Relative
Strength Index formula to produce an oscillator that
fluctuates between 0 and 100.
By
calculating the RSI in this way Wilder was able to
overcome two problems he had encountered with other
momentum oscillators. Firstly, the RSI should avoid
some of the erratic movements common to other momentum
oscillators by smoothing the points used to calculate
the oscillator. Secondly, the Y Axis scale for all
instruments should be the same, 0 to 100. This would
enable comparison between instruments and for objective
levels to be used for overbought and oversold readings.
In
this example the overbought and oversold zones are
marked, above 70 and below 30 respectively, as well
as examples of failure swings and bullish and bearish
divergence.
Stochastic
Stochastic are an oscillator developed by George Lane
and are based on the following observation:
As
prices increase - closing prices tend to be closer
to the upper end of the price range
As
prices decrease - closing prices tend to be closer
to the lower end of the price range
There
are two types of Stochastic:
Slow Stochastic
Fast Stochastic
Each
Stochastic uses two lines, %K and %D. The difference
between Fast and Slow Stochastic is in the calculation
of the %K and %D lines. Slow Stochastic is a slower
and smoother form of Fast Stochastic.
Slow
Stochastic
Slow Stochastic are based on Fast Stochastic but provides
a slower and smoother response to price movements.
It consists of two lines, %K and %D. The %K line in
Slow Stochastic is the same as the %D line in Fast
Stochastic and the %D line in Slow Stochastic is a
Simple Moving Average of %K Slow Stochastic. This
line is smoother than the %K and provides the signals
for an overbought/oversold market.
Fast
Stochastic
Fast Stochastic consists of two lines, %K and %D:
The %K line measures as a percentage where the current
close is in relation to the lowest low over the observation
period. This is shown on a scale of 0 to 100, where
0 is the observation period low and 100 is the observation
period high. The %D line is a Simple Moving Average
of the %K. This line is smoother than the %K and provides
the signals for an overbought / oversold market.
In
this chart both Fast and Slow Stochastic are charted,
you can see that Slow Stochastic are smoother and
slower to respond to price changes than Fast Stochastic.
In
this chart the overbought and oversold areas are indicated,
above 80 and below 20 respectively, also indicated
are examples of Stochastic buy and sell signals where
%K and %D have moved into the overbought or oversold
zones, crossed and then moved out of the overbought
or oversold zones.
This
chart has examples of bullish and bearish divergence.
Volume
Volume is the total number of shares or futures contracts
traded during the given period. Volume activity is
normally viewed in relation to price activity and
price range, where volume is used to confirm price
trends and to warn of any weakening or change in the
trend
This
analysis displays volume and a moving average of the
volume. The moving average of volume allows you to
see if volume is high or low relative to the moving
average. Point A on the analysis marks an attempt
by the market to move to new highs on low volume (volume
was below the moving average). You can see that the
market failed to hold these new highs and in fact
reversed to make new lows.At point B the market broke
to new highs on increasing volume suggesting that
this was a valid move and that the market would hold
these new levels.At point C there was a high volume
day with a strong close. This indicated that the market
was going to make new highs.
Moving
Average Convergence Divergence (MACD)
Moving
Average Convergence Divergence or MACD as it is more
commonly known, was developed by Gerald Appel to trade
26 and 12week cycles in the stock market. MACD is
a type of oscillator that can measure market momentum
as well as follow or indicate the trend.
MACD
consists of two lines, the MACD Line and the Signal
Line. The MACD Line measures the difference between
a short Exponential Moving Average and a long Exponential
Moving Average. The Signal Line is an Exponential
Moving Average of the MACD Line. MACD oscillates above
and below a zero line without upper and lower boundaries.
Buy
and sell signals are generated using MACD when the
MACD Line and Signal Lines cross, this occurred a
number of times on this chart, however the most effective
buy and sell signals will be after a divergence signal.
This chart has examples of both, bullish and bearish
divergences as well as the ensuing buy and sell signals.
Alpha-Beta
Trend analysis
Alpha-Beta Trend analysis was developed by Anthony
W Warren Ph.D. in 1984, and is an attempt to avoid
some of the false signals associated with crossing
moving averages. Three lines are plotted:
Upper trend channel line
Lower trend channel line
Trading filter
Together,
the upper and lower lines define the uncertainty channel
for trade decisions; the width of the channel varies
with volatility.
In
this example, the buy signal is given when the trading
filter crosses to below the lower band. For the duration
of the up-trend the trading filter is below the lower
band. The signal to exit the long position is when
the trading filter moves back within the bands.
Momentum
Momentum is an oscillator that measures the rate at
which prices are changing over the Observation Period.
It measures whether prices are rising or falling at
an increasing or decreasing rate. The Momentum calculation
subtracts the current price from the price a set number
of periods ago. This positive or negative difference
is plotted about a zero line.
In
this example the Momentum line indicates that the
market is overbought, this is followed by a bearish
divergence signal, which indicates a weakening up
trend. The confirmation that the trend has reversed
is the break of the trend line.
The
last signal from the Momentum line is that the market
is oversold, this situation is corrected when the
market rallies and the Momentum line moves back to
zero.
