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Moving
Averages
Technical
analysis that uses different chart
patterns, trend lines and channels is hard enough
because it is almost impossible to automate it and
computerize. That is why many traders tend to use
indicators that are easier to use, since it is possible
to compute them and automate. One of such indicators is
moving average. Signal of moving averages are
unequivocal and accurate. Although, it is still remains
one of the main question for technical
analysts on what level those signals should be
trusted.
There
was always one major problem with moving averages  to
choose correct period for a particular time frame. Due
to this problem there were made extensive researches,
calculations, many scientific papers were written. If we
think about it, moving averages, if correctly used, can
be very powerful and substitute many other indicators
and technical analysis tools.
One of
the characteristics of any moving average is some
segment of time called period. Moving average can be
calculated for anything; usually technical analysts do
it for some price values. Depending on the time frame
(hourly, daily, monthly) an average closing price for
hours, days or months is taken for calculations. Some
analysts think that closing price is not unbiased enough
and take an average of averaged price values for a
minute, hour or day. There are other possibilities.
Sometimes, moving averages are created for trading
volumes or some other technical indicators. In any case,
moving average is always behind the market movements
because it is comprised of data for some past period of
time.
There are 3 main types of
moving averages: Simple
Moving Average, Weighted
Moving Average, and Exponential
Moving Average. Simple
moving averages are pretty simple as you can note it
from the name. A simple moving average is formed by
computing the average (mean) price of a currency pair
over a specified number of periods. While it is possible
to create moving averages from the Open, the High, and
the Low data points, most moving averages are created
using the closing price. For example: a 5day simple
moving average is calculated by adding the closing
prices for the last 5 days and dividing the total by 5.
12+13+20+10+15=70
60/5=14
The
same calculations we would need to do for each price bar
on the chart. The averages are then joined to form a
smooth curving line  the
moving
average line. Continuing our example, if the next
closing price in the average is 10, then this new period
would be added and the oldest day, which is 12, would be
dropped. The new 5day simple moving average would be
calculated as follows:
13+20+10+15+10
= 68
68/5=
13.6
Over
the last 2 days, the SMA moved from 14 to 13.6. As new
days are added, the old days will be subtracted and the
moving average will continue to move over time.
Here
is the formula for calculating simple moving average:
Also,
let us see how simple moving average looks on a chart:
In
order to reduce the lag in simple moving averages,
technicians often use exponential moving averages (also called exponentially weighted
moving averages). EMA's reduce the lag by applying more
weight to recent prices relative to older prices. The
weighting applied to the most recent price depends on
the specified period of the moving average. The shorter
the EMA's period, the more weight that will be applied
to the most recent price. For example: a 10period
exponential moving average weighs the most recent price
18.18% while a 20period EMA weighs the most recent
price 9.52%. As we'll see, the calculating and EMA is
much harder than calculating an SMA. The important thing
to remember is that the exponential moving average puts
more weight on recent prices. As such, it will react
quicker to recent price changes than a simple moving
average. Here's the calculation formula.
Exponential
Moving Averages can be specified in two ways  as a
percentbased EMA or as a periodbased EMA. A
percentbased EMA has a percentage as it's single
parameter while a periodbased EMA has a parameter that
represents the duration of the EMA.
The
formula for an exponential moving average is:
For
a percentagebased EMA, "Multiplier" is equal
to the EMA's specified percentage. For a periodbased
EMA, "Multiplier" is equal to 2 / (1 + N)
where N is the specified number of periods.
For
example, a 10period EMA's Multiplier is calculated like
this:
(2
/ (Time periods+1)) = (2/10+1)) = 0.1818 (18.18%)
This
means that a 10period EMA is equivalent to an 18.18%
EMA.
Note
that, in theory, every previous closing price in the
data set is used in the calculation of each EMA that
makes up the EMA line. While the impact of older data
points diminishes over time, it never fully disappears.
This is true regardless of the EMA's specified period.
The effects of older data diminish rapidly for shorter
EMA's. than for longer ones but, again, they never
completely disappear.
Here
is an example of how EMA looks on a real chart:
An
average in which each quantity to be averaged is
assigned a weight. These weightings determine the
relative importance of each quantity on the average.
Weightings are the equivalent of having that many like
items with the same value involved in the average.
To
demonstrate, let's take the value of letter tiles in the
popular game Scrabble.
Value: 10
8 5 4
3 2 1
0
Occurrences: 2 2 1 10
8 7 68 2
To average these values, do a weighted average using the
number of occurrences of each value as the weight. To
calculate a weighted average:
1. Multiply each value by its weight. (20, 16, 5,
40, 24, 14, 68, and 0)
2. Add up the products of value times weight to get
the total value. ( Sum=187)
3. Add the weight themselves to get the total
weight. (Sum=100)
4. Divide the total value by the total weight.
Here is
the calculation formula:
And
here is how it looks on real charts:
Although
it looks like the second and the third methods are more
advantageous, most analysts use simple moving averages
in their technical analysis. Some attribute this to
higher reliability of results, others think that this
method is simpler and because of this is more natural.
We think that this is just a matter of taste.
As you
can see from above chart examples, moving average lines
are drawn right on the charts. You can use any chart
type but mostly analysts try to use bar charts. As the
period (number of days) of the moving average increases,
it is tends to get more behind the actual price
movements and looks more smoothed out and away from the
price movements chart.
This is
why, it is necessary to pay great attention to choosing
appropriate period for your moving average. If you are
trying to do longterm analysis, then the period of your
moving average should be higher compared to shortterm
analysis. It is important to keep in mind that moving
averages with lower periods will give a lot of false
signals and moving averages with higher periods will
have lower sensitivity, i.e. will provide less signals.
There are 2 ways to handle these problems: you either
have to choose appropriate period for any particular
case, or you can use at the same time couple different
moving averages.
There
are certain recommended combination of periods and
moving averages types that should be used in particular
time frames and with particular currency pairs. In
general, it would be a good hint to use periods that are
characterized by Fibonacci
numbers (5,8,14,21, etc).
So what
kind of signals do they generate and how do moving
averages provide them. General principals are formulated
as this: if the moving average line is below a price
movement chart, then the trend is bullish, and if above,
then the trend is bearish. When the price crosses the
moving average the trend changes its direction. In other
words, moving averages are more complicated type of
trend lines  support and resistance. That is why, you
can use general principles formulated for trend lines
with moving averages.
The
most commonly used time frames for moving averages are
10, 20, 50, and 200 periods on a daily chart. As always,
the longer the time frame, the more reliable the study.
However shorter term moving averages will react more
quickly to the market's movements and will provide
earlier trading signals.
10,
20, 50 and 200Day SMAs on nonDaily Charts
Also note that as you change your time frame in the
chart (say, changing a daily chart into an hourly), the
moving average will need to change too. If you want a
10day moving average line on an hourly chart, you would
need a 240hour SMA (that is 10day times 24 hours).
As
you can see on the picture below, when 10 and 20 SMA are
crossing the 50 SMA there is always a trend reversal. We
are using two lower period SMAs to confirm the trend
reversal and use 200 SMA to establish solid support
level in bullish market. 50 SMA is playing here the role
of a key shortterm support and resistance levels.
How
to Use Moving Averages in Trading
.
Enter when a strong trend pulls back to a moving average
line
. Enter on a moving average crossover
Gauge
overall trend.
Moving averages display a smoothed out line of the
overall trend. The longer the term of the moving
average, the smoother the line will be. In order to
gauge the strength of a trend in a market, plot the 10,
20, 50 and 200 day SMA's. In an uptrend, the shorter
term averages should be above the longer term ones, and
the current price should be above the 10 day SMA. A
trader's bias in this case should be to the upside,
looking for opportunities to buy when the price moves
lower rather than taking a short position.
Confirmation
of price action. As
always, traders should look at candlestick patterns and
other indicators to see what is really going on in the
market at the time. The chart above points out the
Bullish Engulfing pattern that occurs just as the pair
bounces off the 20 day EMA. Hitting the 20 day EMA, in
conjunction with the candlestick pattern, suggests a
bullish trend. Traders should enter once the Bullish
Engulfing candle is cleared.
Crossovers.
When a shorter moving average crosses a longer one (i.e.
if the 20 day EMA crossed below the 200 day EMA), this
may be seen as an indication that the pair will move in
the direction of the shorter MA (so, in the
aforementioned example, it would move down).
Accordingly, should the short EMA crosses back above the
longer EMA (i.e. the 20 day EMA crossed above the 200
day EMA), this may be viewed as a possible change in the
trend (so, in the aforementioned example, it would move
up). Historically, moving average crossovers tend to
'lag' the current market action. The reason being is
that the moving averages give us an 'average' price
over a given period of time.
Therefore
the moving averages tend to reflect the market's
action, only after at least some time has past. As the
short moving average crosses over and above the longer
moving average, this can be interpreted as a change in
trend to the upside. The opposite also holds true, as
the short moving average crosses down and below the long
moving average, a new downtrend may emerge in the near
future.
Moving
average crossovers tend to generate more reliable
results in a trending market that tends to accomplish
either new highs or new lows. In a range bound market
environment, the moving averages may cross one another
many times, and may tend to give us false trading
signals. It is important for this reason, that we first
identify the market as either trending or range bound.
Filters
A
filter is any technique used in technical analysis
to increase one's confidence about a certain trade. For
example, many traders may choose to wait until a price
crosses above a moving average and is at least 10% above
the average before placing an order. This is an attempt
to make sure the crossover is valid and to reduce the
number of false signals. The downside about relying on
filters too much is that some of the gain is given up
and it could lead to feeling like you have missed on
some profits. These negative feelings will decrease over
time as you constantly adjust the criteria used for your
filter. There are no set rules or things to look out for
when filtering; it's simply an additional tool that will
allow you to trade with confidence.
Moving
Average Envelope
Another
strategy that incorporates the use of moving averages is
known as an envelope. This strategy involves plotting
two bands around a moving average, staggered by a
specific percentage rate. For example, in the chart
below, a 5% envelope is placed around a 25day moving
average. Traders will watch these bands to see if they
act as strong areas of support or resistance. Notice how
the move often reverses direction after approaching one
of the levels. A price move beyond the band can signal a
period of exhaustion, and traders will watch for a
reversal toward the center average.
With
the help of moving averages it is possible to determine
the length of the period for a market cycle. Also,
moving averages can be used to create oscillators. One
of such methods is convergence divergence (MACD),
which is very popular nowadays. We will cover this
method in oscillators chapter.
Now
that we have some basic understanding of how moving
averages work we should formalize what we have learned
and write up some simple hints that anyone who uses
moving averages should follow:
 Trader
or analyst that plans to use moving averages in
his/her trading needs to be familiar with trend line
trading strategy because entering short or long
positions based on moving average is very similar to
entering positions using trend lines.
 Using
moving averages is most effective in trending
markets (bullish or bearish). This is the main
difference between usage of moving averages and
oscillators. Moving averages work very well in
trending markets but they do not indicate the high
or low of the market. That is why during sideways
moving market delays in signals given by moving
averages will make them absolutely useless, and
sometimes can even lead to losses.
 For
these reasons, moving averages should be used only
in trending market and you have to remember that
they are always behind the actual market price so
there is always a possibility of getting false
signals. Maybe, if there are too many false signals,
we can say that the market is changed into sideways
movement.
You
should certainly use moving averages in your analysis
and trading but you should not overuse them. As all
other computerized methods, moving averages are some
type of approximation and do not really determine
anything by themselves. They only allow us to compare
price curve with itself.
Oscillators
Using
oscillators in technical analysis is one of the most
simple and yet reliable methods of getting forecasts for
future price movements. Compared to moving averages,
oscillators are very useful in sideways markets. During
range trading or sideways market prices change so
frequently that it is hard to catch the beginning and
the end of these short up and down movements.
In this
situation trading, especially speculative trading, can
become so damaging that technical analysis specialists
often recommend to stay away from the market at such
times and not to trade at all. Just recall the triangle
formation: very hard to trade and better to stay away.
Thanks
to oscillators, now we can trade during such market
conditions and not loose our time and potential profits.
As statistics shows, it takes 30% of time to develop a
trend; all other time is spent on corrections.
Distinctive feature of oscillators is that they foresee
future developments and signal the reversal beforehand.
This separates them from moving averages, which as we
remember, always lag from real time developments.
Oscillators also could be useful in developed trending
markets  for market reversal signals.
All
oscillator based methods are more or less similar to
each other. In their foundation lies different formulas
which, in turn, could be applied to different periods.
In the beginning oscillators were created for daily
price fluctuations: today, they are used in any time
frames  minutes, hourly, weekly and even monthly.
Most of the times oscillator charts are placed under the
price charts. Oscillator value could be measured in
percentages, or in relative or absolute units.
Overbought
and Oversold market conditions are taken as basis for
the oscillator methods. There is an overbought market
condition when the price is at its highest level, i.e.
further increase is impossible. An oversold market
condition is present when the price is at its lowest
level and further decrease is impossible.
To
determine whether market is in oversold or overbought
conditions, for each oscillator particular levels are
set. When the oscillator's value comes close to such
levels, but or sell signals are generated. Another
important indicator is divergence between price
direction and oscillator direction. Divergence is a
reversal signal. This property, for some reason, is used
less frequently than oversold or overbought property of
oscillators.
In this
chapter we will look at most frequently used and
important oscillators. We will cover Momentum, RSI,
Stochastic and MACD oscillators. Almost all other
oscillators that we will not cover here are based on
already used formulas, methods, techniques of above
mentioned main oscillators. So if you will understand
how those 4 main oscillators work, then you will be able
to understand more or less the work of other
oscillators.
Momentum
Many
leading indicators come in the form of momentum
oscillators. Generally speaking, momentum measures
the rateofchange of a currency pair's price. As the
price of a currency pair rises, price momentum
increases. The faster the currency pair rises (the
greater the periodoverperiod price change), the larger
the increase in momentum. Once this rise begins to slow,
momentum will also slow. As a currency pair begins to
trade flat, momentum starts to actually decline from
previous high levels. However, declining momentum in the
face of sideways trading is not always a bearish signal.
It simply means that momentum is returning to a more
median level.
Here
is how it looks on realtime chart:
Interpretation
A
strongly trending market acts like a pendulum; the move
begins at a fast pace, with strong momentum. It
gradually slows down, or loses momentum, stops, and
reverses course.
The
momentum line is always a step ahead of the price
movement. It leads the advance or decline in prices and
levels off while the current price trend is still in
effect. It then begins to move in the opposite direction
as prices begin to level off.
The
14 day momentum line fluctuates on an open scale around
a zero line. When the latest closing price is higher
than that of 14 days ago, a positive value is plotted
above the zero line. If the latest close is lower than
14 days previous, a negative value is plotted.
Ten
days or periods are usually used in calculating
momentum, but any time period can be employed. The
shorter the time frame used the more sensitive momentum
becomes to short term fluctuations with more marked
oscillations. Oscillator swings are smoother and more
stable when a longer number of days are used.
Upward
Momentum
When
an uptrending momentum line begins to flatten out it
means that the new gains being achieved by the latest
closing prices are the same as the gains 14 days
earlier. The rate of upward momentum has leveled off
even though prices may still be advancing. When the
momentum line begins to drop further, below the zero
line, the uptrend in prices could still be in force, but
the last price gains are less than those of 14 days ago.
The uptrend is losing momentum.
Downward
momentum
When
the momentum line moves below the zero line, the latest
close is now under the close of 10 days ago and a short
term downtrend is in effect. As momentum continues to
drop farther below the zero line, the downtrend gains
momentum. The downtrend decelerates when the line begins
to turn around.
If
loss of momentum is experienced in a market at the same
time as selling resistance is met or when buying power
is temporarily exhausted, momentum and price peak
simultaneously.
Trade
Signals
Momentum
is a basic application of oscillator analysis, designed
to measure the rate of price change, not the actual
price level. Three common signals are generated by the
momentum oscillator: zeroline crossings, trendline
violations, and extreme values.
Zeroline
crossings
Although
the longterm price trend is still the overriding
consideration, a crossing above the zero line could be a
buy signal if the price trend is up and a crossing below
the zero line, a sell signal, if the price trend is
down.
Using
Trendlines
The
trendlines on the momentum chart are broken sooner than
those on the price chart. The value of the momentum
indicator is that it turns sooner than the market
itself, making it a leading indicator.
Extreme
Values
One
of the benefits of oscillator analysis is being able to
determine when markets are in extreme areas. At extreme
positive values, momentum implies an overbought
position; at extreme negative values, an oversold
position
The
absence of a fixed upper and lower boundary presents a
difficulty with the momentum line. To help solve this
problem look at the longterm history of the momentum
line and draw horizontal lines along its upper and lower
boundaries. Adjust these lines periodically, especially
after important trend changes.
RSI
(Relative Strength Index)
The RSI
is a momentum indicator, or oscillator, that measures
the relative internal strength of a market (not
against another market or index).
As with all oscillators, RSI can provide early
warning signals but should be used in conjunction with
other indicators. Divergences
are the most important signal provided by RSI.
The
Relative Strength Index (RSI) is a popular oscillator
developed by Welles Wilder, Jr. RSI measures the
relative changes between higher and lower closing
prices, and provides an indication of overbought and
oversold conditions.
The
term "Relative Strength" is slightly
misleading and often causes some confusion. Relative
strength generally means a comparison between two
different markets or indices. RSI, on the other hand,
looks at the internal strength of a single
market.
Interpretation
RSI
is plotted on a vertical scale of 0 to 100. The 70% and
30% levels are used as warning signals. An RSI above 70%
is considered overbought and below 30% is considered
oversold. The 80% and 20% levels are preferred by some
traders. The significance depends upon the time frame
being considered. An overbought reading in a 9day RSI
is not nearly as significant as an RSI for a 12month
period.
An
overbought or oversold condition merely indicates that
there is a high probability of a counter
reaction. It is an indication that there may be an
opportunity to buy or sell, but does not provide
the final signal. RSI signals should always be used in
conjunction with trendreversal signals offered by the
price itself.
RSI
can be plotted for any time span. Wilder originally
recommended using a 14day RSI. Since then, the 9, 10
and 25day RSIs have also become popular. The shorter
the time period, the more sensitive the oscillator
becomes. If the user is trading shortterm moves, the
time period can be shortened. Lengthening the time
period makes the oscillator smoother and narrower in
amplitude.
In
using RSI, a crossover above the 70% level is a warning
signal to prepare to sell and, conversely, when the RSI
falls below 30% you have a notice to prepare to buy. The
actual buy and sell signals are given when the RSI
reverses (see below). RSI crossings through the 50%
level are also used as buy and sell signals by some
traders.
Trade
Signals:
Tops
& Bottoms, Failure Swings, Divergence
Traders
watch for double tops or what Wilder referred to as
"failure swings." If the RSI makes a double
top formation, with the first top above 70% and the
second top below the first, you get a sell
signal when the RSI falls below the level of the
dip. Conversely, a double bottom at or below 30% (with
the first low below 30% and the second at or above the
same level) gives you a buy
signal when the RSI breaks above the previous
peak.
These
failure swings can lead to divergences between the price
action and the RSI. For example, a divergence occurs
when a market makes a new high or low, but the RSI fails
to set a matching new high or low. A divergence can be
an indication of an impending reversal. In Wilder's
opinion, divergences are the most important signal provided by RSI.
Trendlines
RSI
trendlines can provide good signals, particularly when
used in conjunction with price patterns. When both price
and RSI trendlines are violated within a short period
you could have an important buy or sell signal.
Stochastic
Oscillator
The Stochastic Oscillator is a measure of the
relative momentum of current prices to previous closing
prices within a given interval. When it is
plotted, it is two lines that move within a range of 0
and 100. Values above 80 are considered to be in
overbought territory giving an indication that a
reversal in price is possible. Values below 20 are
considered oversold and again are an indication that a
reversal of the price trend is a higher risk. In a
strong trending environment, the Stochastic Oscillator
can stay in overbought or oversold territory for some
time while price continues in a single direction.
In relation to a longer term price trend environment,
the stochastic provides little interest. In its
construction it is meant to relate the current periods
momentum to the most recent previous periods of momentum
in price in an attempt to identify periods where
momentum may be easing or increasing. The easing
(at a top) or increase (at a bottom) of momentum occurs
at reversal points for the price trend being measured.
However changing momentum also occurs during times when
there is no change in the overall trend in prices and
should be understood as a period when a reversal in
price trend is possible but not guaranteed.
A shorter period Stochastic represents the
trend development for a shorter period of time.
Not always is a change in the price momentum also a
change in the price trend of a stock. For any
technical indications of potential future price trend
development, it is important to build a wide body of
evidence when developing an expectation for future
prices. At a reading of zero, the Stochastic
Oscillator implies that the securities close is at the
lowest price that it has traded during the preceding x
periods (x being defined as the number of periods in the
calculation). At a reading of 100, the Stochastic
Oscillator implies the securities close is at the
highest price it has traded during the period of the
calculation.
The
basis for interpreting the stochastic is the assumption
that prices tend to close near the upper part of a
trading range during an up trend and near the lower part
during a downtrend. In addition, extreme periods
are often followed by a reversal of price trend and so
are called overbought and oversold area's. Not
always will a reversal follow periods when the
Stochastic is in overbought or oversold area's,
however the presence in overbought and oversold alerts
a trader to look for further evidence that a price trend
reversal may be near.
The Stochastic is made up of two lines, the
dotted line is called the %D which is a moving average
of the %K which is a calculation of the securities
highest high minus the lowest low as the denominator and
the close of the current period minus the lowest low
computed as a ratio, converted to decimals and
multiplied by 100.
A buy signal is given when the oscillator falls
below 20 and then rises above 20, indicating a return of
interest in the stock. This type of interpretation
requires other supporting evidence to avoid whipsaws or
failed signals. A sell signal is given when the
oscillator rises above 80 and then falls below 80.
The signal is the reentry into the midzone for the
indicator after being in overbought or oversold
territory. This interpretation works poorly in a
strong trending environment. Traders also look for
crossovers of the fast stochastic (solid red) and the
smoothed (dotted lines) looking for confirming evidence
of a signal to buy or sell.
Other interpretive qualities of the Stochastic
Oscillator is the search for divergences between the
oscillator and price. A divergence of peaks is
often followed by a drop in price. A divergence of
troughs often precedes a rise in price. Notice
that divergences can go against the larger price trend
suggesting caution and lower price projections as each
new segment of price trend emerges. Divergences
also can continue for extended periods before any
evidence of price trend reversal occurs. A
divergence that occurs over a shorter period of time
would suggest a shorter term outlook on the reaction in
prices. A divergence that continues over a longer
period of time would represent a larger pool of activity
and would be expected to result in longer and larger
period of new price trend should a reversal in price
trend result after a long period of divergence between
and indicator and price.
MACD
(Moving Average Convergence/Divergence)
Developed by Gerald Appel, Moving Average
Convergence Divergence (MACD) is one of the simplest
and most reliable technical
indicators available. MACD uses moving averages,
which are lagging indicators, to include some
trendfollowing characteristics. These lagging
indicators are turned into a momentum oscillator by
subtracting the faster moving average from the slower
moving average. The resulting plot forms a line that
oscillates above and below zero, without any upper or
lower limits.
The most popular formula
for the "standard" MACD is the difference
between a security's 26day and 12day exponential
moving averages. This is the formula that is used in
many popular technical analysis programs, and quoted in
most technical analysis books on the subject. Appel and
others have since tinkered with these original settings
to come up with a MACD that is better suited for faster
or slower securities. Using shorter moving averages will
produce a quicker, more responsive indicator, while
using longer moving averages will produce a slower
indicator, less prone to whipsaws. For our purposes in
this article, the traditional 12/26 MACD will be used
for explanations. Later in the indicator series, we will
address the use of different moving averages in
calculating MACD.
Of the two moving
averages that make up MACD, the 12day EMA is the faster
and the 26day EMA is the slower. Closing prices are
used to form the moving averages. Usually, a 9day EMA
of MACD is plotted as a dotted line along side the
indicator and acts as a trigger. A bullish crossover
occurs when MACD moves above the 9day EMA and a bearish
crossover occurs when MACD moves below the 9day EMA.
For analysis purposes on the Merrill Lynch chart, MACD
was plotted as the blue histogram and the 9day EMA of
MACD has been left off.
MACD measures the
difference between two moving averages. A positive MACD
indicates that the 12day EMA is trading above the
26day EMA. A negative MACD indicates that the 12day
EMA is trading below the 26day EMA. If MACD is positive
and rising, then the gap between the 12day EMA and the
26day EMA is widening. This indicates that the
rateofchange of the faster moving average is higher
than the rateofchange for the slower moving average.
Positive momentum is increasing and this would be
considered bullish. If MACD is negative and declining
further, then the negative gap between the faster moving
average and the slower moving average is expanding.
Downward momentum is accelerating and this would be
considered bearish. MACD centerline crossovers occur
when the faster moving average crosses the slower moving
average.
MACD generates bullish
signals from three main sources:
 Positive
divergence
 Bullish
moving average crossover
 Bullish
centerline crossover
A positive divergence
occurs when MACD begins to advance and the currency pair
is still in a downtrend and makes a lower reaction low.
MACD can either form as a series of higher lows or a
second low that is higher than the previous low.
Positive divergences are probably the least common of
the three signals, but are usually the most reliable and
lead to the biggest moves.
A bullish moving average
crossover occurs when MACD moves above the 9day EMA or
trigger line. Bullish moving average crossovers are
probably the most common signals and as such are the
least reliable. If not used in conjunction with other
technical analysis tools, these crossovers can lead to
whipsaws and many false signals. Moving average
crossovers are sometimes used to confirm a positive
divergence. The second low or higher low of a positive
divergence can be considered valid when it is followed
by a bullish moving average crossover.
Sometimes it is prudent
to apply a price filter to the moving average crossover
in order to ensure that it will hold. An example of a
price filter would be to buy if MACD breaks above the
9day EMA and remains above for three days. The buy
signal would then commence at the end of the third day.
A bullish centerline
crossover occurs when MACD moves above the zero line and
into positive territory. This is a clear indication that
momentum has changed from negative to positive or from
bearish to bullish. After a positive divergence and
bullish moving average crossover, the centerline
crossover can act as a confirmation signal. Of the three
signals, moving average crossover are probably the
second most common signals.
The same techniques could
be used for determining bearish signals but with
opposite sign/direction.
One
of the beneficial aspects of the MACD is also one of its
drawbacks. Moving averages, be they simple, exponential
or weighted, are lagging technical indicators.
Even though MACD represents the difference between two
moving averages, there can still be some lag in the
technical indicator itself. This is more likely to be
the case with weekly charts than daily charts.
MACD
is not particularly good for identifying overbought and
oversold levels. Even though it is possible to identify
levels that historically represent overbought and
oversold levels, MACD does not have any upper or lower
limits to bind its movement. MACD can continue to
overextend beyond historical extremes.
MACD
calculates the absolute difference between two moving
averages and not the percentage difference. MACD is
calculated by subtracting one moving average from the
other. As a currency pair increases in price, the
difference (both positive and negative) between the two
moving averages is destined to grow. This makes its
difficult to compare MACD levels over a long period of
time, especially for stocks that have grown
exponentially.
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