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as we possibly can without all the extras hype. Currency knowledge
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Moving averages come in various forms, but their underlying purpose remains the same: to help technical
traders track the trends of financial assets by smoothing out the day-to-day price fluctuations, or noise.
By identifying trends, moving averages allow traders to make those trends work in their favor and increase the
number of winning trades. Among the most popular technical indicators, moving averages are used to gauge the
direction of the current trend. Every type of moving average is a mathematical result that is calculated by averaging
a number of past data points. Once determined, the resulting average is then plotted onto a chart in order to allow
traders to look at smoothed data rather than focusing on the day-to-day price fluctuations that are inherent in all
financial markets.
The simplest form of a moving average, appropriately known as a simple moving average (SMA), is calculated by
taking the arithmetic mean of a given set of values. For example, to calculate a basic 10-day moving average you
would add up the closing prices from the past 10 days and then divide the result by 10. In Figure 1, the sum of the
prices for the past 10 days (110) is divided by the number of days (10) to arrive at the 10-day average. If a trader
wishes to see a 50-day average instead, the same type of calculation would be made, but it would include the prices
over the past 50 days. The resulting average below (11) takes into account the past 10 data points in order to give
traders an idea of how an asset is priced relative to the past 10 days.
Figure 1
Perhaps you're wondering why technical traders call this tool a "moving" average and not just a regular mean? The
answer is that as new values become available, the oldest data points must be dropped from the set and new data
points must come in to replace them. Thus, the data set is constantly "moving" to account for new data as it
becomes available. This method of calculation ensures that only the current information is being accounted for. In
Figure 2, once the new value of 5 is added to the set, the red box (representing the past 10 data points) moves to
the right and the last value of 15 is dropped from the calculation. Because the relatively small value of 5 replaces the
high value of 15, you would expect to see the average of the data set decrease, which it does, in this case from 11
to 10.
Figure 2
What Do Moving Averages Look Like?
Once the values of the MA have been calculated, they are plotted onto a chart and then connected to create a
moving average line. These curving lines are common on the charts of technical traders, but how they are used can
vary drastically (more on this later). As you can see in Figure 3, it is possible to add more than one moving average
to any chart by adjusting the number of time periods used in the calculation. These curving lines may seem
distracting or confusing at first, but you'll grow accustomed to them as time goes on. The red line is simply the
average price over the past 50 days, while the blue line is the average price over the past 100 days.
Figure 3
Now that you understand what a moving average is and what it looks like, we'll introduce a different type of moving
average and examine how it differs from the previously mentioned simple moving average.
The simple moving average is extremely popular among traders, but like all technical indicators, it does have its
critics. Many individuals argue that the usefulness of the SMA is limited because each point in the data series is
weighted the same, regardless of where it occurs in the sequence. Critics argue that the most recent data is more
significant than the older data and should have a greater influence on the final result. In response to this criticism,
traders started to give more weight to recent data, which has since led to the invention of various types of new
averages, the most popular of which is the exponential moving average (EMA).
Exponential Moving Average
The exponential moving average is a type of moving average that gives more weight to recent prices in an attempt to
make it more responsive to new
information. Learning the somewhat complicated equation for calculating an EMA may be unnecessary for many
traders, since nearly all charting packages do the calculations for you. However, for you math geeks out there, here
is the EMA equation:
When using the formula to calculate the first point of the EMA, you may notice that there is no value available to use
as the previous EMA. This small problem can be solved by starting the calculation with a simple moving average and
continuing on with the above formula from there. We have provided you with a sample spreadsheet that includes
real-life examples of how to calculate both a simple moving average and an exponential moving average.
The Difference Between the EMA and SMA
Now that you have a better understanding of how the SMA and the EMA are calculated, let's take a look at how
these averages differ. By looking at the calculation of the EMA, you will notice that more emphasis is placed on the
recent data points, making it a type of weighted average. In Figure 5, the numbers of time periods used in each
average is identical (15), but the EMA responds more quickly to the changing prices. Notice how the EMA has a
higher value when the price is rising, and falls faster than the SMA when the price is declining. This responsiveness
is the main reason why many traders prefer to use the EMA over the SMA.
Figure 5
What Do the Different Days Mean?
Moving averages are a totally customizable indicator, which means that the user can freely choose whatever time
frame they want when creating the average. The most common time periods used in moving averages are 15, 20,
30, 50, 100 and 200 days. The shorter the time span used to create the average, the more sensitive it will be to
price changes. The longer the time span, the less sensitive, or more smoothed out, the average will be. There is no
"right" time frame to use when setting up your moving averages. The best way to figure out which one works best for
you is to experiment with a number of different time periods until you find one that fits your strategy.
How To Use Them
Some of the primary functions of a moving average are to identify trends and reversals, measure the strength of an
asset's momentum and determine potential areas where an asset will find support or resistance. In this section we
will point out how different time periods can monitor momentum and how moving averages can be beneficial in
setting stop-losses. Furthermore, we will address some of the capabilities and limitations of moving averages that
one should consider when using them as part of a trading routine.
Trend
Identifying trends is one of the key functions of moving averages, which are used by most traders who seek to "make
the trend their friend". Moving averages are lagging indicators, which means that they do not predict new trends, but
confirm trends once they have been established. As you can see in Figure 1, a stock is deemed to be in an uptrend
when the price is above a moving average and the average is sloping upward. Conversely, a trader will use a price
below a downward sloping average to confirm a downtrend. Many traders will only consider holding a long position in
an asset when the price is trading above a moving average. This simple rule can help ensure that the trend works in
the traders' favor.
Figure 1
Momentum
Many beginner traders ask how it is possible to measure momentum and how moving averages can be used to
tackle such a feat. The simple answer is to pay close attention to the time periods used in creating the average, as
each time period can provide valuable insight into different types of momentum. In general, short-term momentum
can be gauged by looking at moving averages that focus on time periods of 20 days or less. Looking at moving
averages that are created with a period of 20 to 100 days is generally regarded as a good measure of medium-term
momentum. Finally, any moving average that uses 100 days or more in the calculation can be used as a measure of
long-term momentum. Common sense should tell you that a 15-day moving average is a more appropriate measure
of short-term momentum than a 200-day moving average.
One of the best methods to determine the strength and direction of an asset's momentum is to place three moving
averages onto a chart and then pay close attention to how they stack up in relation to one another. The three
moving averages that are generally used have varying time frames in an attempt to represent short-term, medium-
term and long-term price movements. In Figure 2, strong upward momentum is seen when shorter-term averages
are located above longer-term averages and the two averages are diverging. Conversely, when the shorter-term
averages are located below the longer-term averages, the momentum is in the downward direction.
Figure 2
Support
Another common use of moving averages is in determining potential price supports. It does not take much
experience in dealing with moving averages to notice that the falling price of an asset will often stop and reverse
direction at the same level as an important average. For example, in Figure 3 you can see that the 200-day moving
average was able to prop up the price of the stock after it fell from its high near $32. Many traders will anticipate a
bounce off of major moving averages and will use other technical indicators as confirmation of the expected move.
Figure 3
Resistance
Once the price of an asset falls below an influential level of support, such as the 200-day moving average, it is not
uncommon to see the average act as a strong barrier that prevents investors from pushing the price back above
that average. As you can see from the chart below, this resistance is often used by traders as a sign to take profits
or to close out any existing long positions. Many short sellers will also use these averages as entry points because
the price often bounces off the resistance and continues its move lower. If you are an investor who is holding a long
position in an asset that is trading below major moving averages, it may
be in your best interest to watch these levels closely because they can greatly affect the value of your investment.
Figure 4
Stop-Losses
The support and resistance characteristics of moving averages make them a great tool for managing risk. The ability
of moving averages to identify strategic places to set stop-loss orders allows traders to cut off losing positions before
they can grow any larger. As you can see in Figure 5, traders who hold a long position in a stock and set their stop-
loss orders below influential averages can save themselves a lot of money. Using moving averages to set stop-loss
orders is key to any successful trading strategy.
Figure 5
Factors To Consider
Data Used in Calculation
Most moving averages take the closing prices of a given asset and factor them into the calculation. We thought it
would be important to note that this does not always need to be the case. It is possible to calculate a moving
average by using the open, close, high, low or even the median. Even though there is little difference between these
calculations when plotted on a chart, the slight difference could still impact your analysis.
Finding an Appropriate Time Periods
Because most MAs represent the average of all the applicable daily prices, it should be noted that the time frame
does not always need to be in days. Moving averages can also be calculated using minutes, hours, weeks, months,
quarters, years etc. Why would a day trader care about how a 50-day moving average will affect the price over the
upcoming weeks? On the other hand, a day trader would want to pay attention to a 50-minute average to get an
idea of the relative cost of the security compared to the past hour. Some traders may even use the average price
over the past three minutes to gauge an uptake in short-term momentum.
No Average is Foolproof
As you know, nothing in the financial markets is for certain - certainly not when it comes to using technical indicators.
If a stock bounced off the support of a major average every time it came close, we would all be rich. One of the major
disadvantages of using moving averages is that they are relatively useless when an asset is trending sideways,
compared to the times when a strong trend is present. As you can see in Figure 1, the price of an asset can pass
through a moving average many times when the trend is moving sideways, making it difficult to decide how to trade.
This chart is a good example of how the support and resistance characteristics of moving averages are not always
present.
Figure 1
Responsiveness to Price Action
Traders who use moving averages in their trading will quickly admit that there is a battle between trying to make a
moving average responsive to changes in trend while not allowing it to be so sensitive that it causes a trader to
prematurely enter or exit a position. Short-term moving averages can be useful in identifying changing trends before
a large move occurs, but the downside is that this technique can also lead to being whipsawed in and out of a
position because these averages respond very quickly to changing prices. Because the quality of the transaction
signals can vary drastically depending on the time periods used in the calculation, it is highly recommended to look
at other technical indicators for confirmation of any move predicted by a moving average.
Beware of the Lag
Because moving averages are a lagging indicator, transaction signals will always occur after the price has moved
enough in one direction to cause the moving average to respond. This lagging characteristic can often work against
a trader and cause him or her to enter into a position at the least opportune time. For example, the only way for a
short-term moving average to cross above a long-term moving average is for the price to have recently moved
higher - many traders will use this bullish crossover as a buy signal. One major problem that often arises is that the
price may have already experienced a large increase before the transaction signal is presented. As you can see in
Figure 2, the large price gap creates a buy signal in late August, but this signal is too late because the price has
already moved up by more than 25% over the past 12 days and is becoming exhausted. In this case, the lagging
aspect of a moving average would work against the trader and likely result in a losing trade.
Figure 2
Strategies
Different investors use moving averages for different reasons. Some use them as their primary analytical tool, while
others simply use them as a confidence builder to back up their investment decisions.
Crossovers
A crossover is the most basic type of signal and is favored among many traders because it removes all emotion. The
most basic type of crossover is when the price of an asset moves from one side of a moving average and closes on
the other. Price crossovers are used by traders to identify shifts in momentum and can be used as a basic entry or
exit strategy. As you can see in Figure 1, a cross below a moving average can signal the beginning of a downtrend
and would likely be used by traders as a signal to close out any existing long positions.
Conversely, a close above a moving average from below may suggest the beginning of a new uptrend.
Figure 1
The second type of crossover occurs when a short-term average crosses through a long-term average. This signal
is used by traders to identify that momentum is shifting in one direction and that a strong move is likely approaching.
A buy signal is generated when the short-term average crosses above the long-term average, while a sell signal is
triggered by a short-term average crossing below a long-term average. As you can see from the chart below, this
signal is very objective, which is why it's so popular.
Figure 2
Triple Crossover and the Moving Average Ribbon
Additional moving averages may be added to the chart to increase the validity of the signal. Many traders will place
the five-, 10-, and 20-day moving averages
onto a chart and wait until the five-day average crosses up through the others – this is generally the primary buy
sign. Waiting for the10-day average to cross above the 20-day average is often used as confirmation, a tactic that
often reduces the number of false signals. Increasing the number of moving averages, as seen in the triple
crossover method, is one of the best ways to gauge the strength of a trend and the likelihood that the trend will
continue.
This begs the question: What would happen if you kept adding moving averages? Some people argue that if one
moving average is useful, then 10 or more must be even better. This leads us to a technique known as the moving
average ribbon. As you can see from the chart below, many moving averages are placed onto the same chart and
are used to judge the strength of the current trend. When all the moving averages are moving in the same direction,
the trend is said to be strong. Reversals are confirmed when the averages cross over and head in the opposite
direction.
Figure 3
Responsiveness to changing conditions is accounted for by the number of time periods used in the moving
averages. The shorter the time periods used in the calculations, the more sensitive the average is to slight price
changes. One of the most common ribbons starts with a 50-day moving average and adds averages in 10-day
increments up to the final average of 200. This type of average is good at identifying long-term trends/reversals.
Filters
A filter is any technique used in technical analysis to increase one's confidence
about a certain trade. For example, many investors may choose to wait until a security 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've "missed the boat". 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 invest 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 25-day 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.
Figure 4
traders track the trends of financial assets by smoothing out the day-to-day price fluctuations, or noise.
By identifying trends, moving averages allow traders to make those trends work in their favor and increase the
number of winning trades. Among the most popular technical indicators, moving averages are used to gauge the
direction of the current trend. Every type of moving average is a mathematical result that is calculated by averaging
a number of past data points. Once determined, the resulting average is then plotted onto a chart in order to allow
traders to look at smoothed data rather than focusing on the day-to-day price fluctuations that are inherent in all
financial markets.
The simplest form of a moving average, appropriately known as a simple moving average (SMA), is calculated by
taking the arithmetic mean of a given set of values. For example, to calculate a basic 10-day moving average you
would add up the closing prices from the past 10 days and then divide the result by 10. In Figure 1, the sum of the
prices for the past 10 days (110) is divided by the number of days (10) to arrive at the 10-day average. If a trader
wishes to see a 50-day average instead, the same type of calculation would be made, but it would include the prices
over the past 50 days. The resulting average below (11) takes into account the past 10 data points in order to give
traders an idea of how an asset is priced relative to the past 10 days.
Figure 1
Perhaps you're wondering why technical traders call this tool a "moving" average and not just a regular mean? The
answer is that as new values become available, the oldest data points must be dropped from the set and new data
points must come in to replace them. Thus, the data set is constantly "moving" to account for new data as it
becomes available. This method of calculation ensures that only the current information is being accounted for. In
Figure 2, once the new value of 5 is added to the set, the red box (representing the past 10 data points) moves to
the right and the last value of 15 is dropped from the calculation. Because the relatively small value of 5 replaces the
high value of 15, you would expect to see the average of the data set decrease, which it does, in this case from 11
to 10.
Figure 2
What Do Moving Averages Look Like?
Once the values of the MA have been calculated, they are plotted onto a chart and then connected to create a
moving average line. These curving lines are common on the charts of technical traders, but how they are used can
vary drastically (more on this later). As you can see in Figure 3, it is possible to add more than one moving average
to any chart by adjusting the number of time periods used in the calculation. These curving lines may seem
distracting or confusing at first, but you'll grow accustomed to them as time goes on. The red line is simply the
average price over the past 50 days, while the blue line is the average price over the past 100 days.
Figure 3
Now that you understand what a moving average is and what it looks like, we'll introduce a different type of moving
average and examine how it differs from the previously mentioned simple moving average.
The simple moving average is extremely popular among traders, but like all technical indicators, it does have its
critics. Many individuals argue that the usefulness of the SMA is limited because each point in the data series is
weighted the same, regardless of where it occurs in the sequence. Critics argue that the most recent data is more
significant than the older data and should have a greater influence on the final result. In response to this criticism,
traders started to give more weight to recent data, which has since led to the invention of various types of new
averages, the most popular of which is the exponential moving average (EMA).
Exponential Moving Average
The exponential moving average is a type of moving average that gives more weight to recent prices in an attempt to
make it more responsive to new
information. Learning the somewhat complicated equation for calculating an EMA may be unnecessary for many
traders, since nearly all charting packages do the calculations for you. However, for you math geeks out there, here
is the EMA equation:
When using the formula to calculate the first point of the EMA, you may notice that there is no value available to use
as the previous EMA. This small problem can be solved by starting the calculation with a simple moving average and
continuing on with the above formula from there. We have provided you with a sample spreadsheet that includes
real-life examples of how to calculate both a simple moving average and an exponential moving average.
The Difference Between the EMA and SMA
Now that you have a better understanding of how the SMA and the EMA are calculated, let's take a look at how
these averages differ. By looking at the calculation of the EMA, you will notice that more emphasis is placed on the
recent data points, making it a type of weighted average. In Figure 5, the numbers of time periods used in each
average is identical (15), but the EMA responds more quickly to the changing prices. Notice how the EMA has a
higher value when the price is rising, and falls faster than the SMA when the price is declining. This responsiveness
is the main reason why many traders prefer to use the EMA over the SMA.
Figure 5
What Do the Different Days Mean?
Moving averages are a totally customizable indicator, which means that the user can freely choose whatever time
frame they want when creating the average. The most common time periods used in moving averages are 15, 20,
30, 50, 100 and 200 days. The shorter the time span used to create the average, the more sensitive it will be to
price changes. The longer the time span, the less sensitive, or more smoothed out, the average will be. There is no
"right" time frame to use when setting up your moving averages. The best way to figure out which one works best for
you is to experiment with a number of different time periods until you find one that fits your strategy.
How To Use Them
Some of the primary functions of a moving average are to identify trends and reversals, measure the strength of an
asset's momentum and determine potential areas where an asset will find support or resistance. In this section we
will point out how different time periods can monitor momentum and how moving averages can be beneficial in
setting stop-losses. Furthermore, we will address some of the capabilities and limitations of moving averages that
one should consider when using them as part of a trading routine.
Trend
Identifying trends is one of the key functions of moving averages, which are used by most traders who seek to "make
the trend their friend". Moving averages are lagging indicators, which means that they do not predict new trends, but
confirm trends once they have been established. As you can see in Figure 1, a stock is deemed to be in an uptrend
when the price is above a moving average and the average is sloping upward. Conversely, a trader will use a price
below a downward sloping average to confirm a downtrend. Many traders will only consider holding a long position in
an asset when the price is trading above a moving average. This simple rule can help ensure that the trend works in
the traders' favor.
Figure 1
Momentum
Many beginner traders ask how it is possible to measure momentum and how moving averages can be used to
tackle such a feat. The simple answer is to pay close attention to the time periods used in creating the average, as
each time period can provide valuable insight into different types of momentum. In general, short-term momentum
can be gauged by looking at moving averages that focus on time periods of 20 days or less. Looking at moving
averages that are created with a period of 20 to 100 days is generally regarded as a good measure of medium-term
momentum. Finally, any moving average that uses 100 days or more in the calculation can be used as a measure of
long-term momentum. Common sense should tell you that a 15-day moving average is a more appropriate measure
of short-term momentum than a 200-day moving average.
One of the best methods to determine the strength and direction of an asset's momentum is to place three moving
averages onto a chart and then pay close attention to how they stack up in relation to one another. The three
moving averages that are generally used have varying time frames in an attempt to represent short-term, medium-
term and long-term price movements. In Figure 2, strong upward momentum is seen when shorter-term averages
are located above longer-term averages and the two averages are diverging. Conversely, when the shorter-term
averages are located below the longer-term averages, the momentum is in the downward direction.
Figure 2
Support
Another common use of moving averages is in determining potential price supports. It does not take much
experience in dealing with moving averages to notice that the falling price of an asset will often stop and reverse
direction at the same level as an important average. For example, in Figure 3 you can see that the 200-day moving
average was able to prop up the price of the stock after it fell from its high near $32. Many traders will anticipate a
bounce off of major moving averages and will use other technical indicators as confirmation of the expected move.
Figure 3
Resistance
Once the price of an asset falls below an influential level of support, such as the 200-day moving average, it is not
uncommon to see the average act as a strong barrier that prevents investors from pushing the price back above
that average. As you can see from the chart below, this resistance is often used by traders as a sign to take profits
or to close out any existing long positions. Many short sellers will also use these averages as entry points because
the price often bounces off the resistance and continues its move lower. If you are an investor who is holding a long
position in an asset that is trading below major moving averages, it may
be in your best interest to watch these levels closely because they can greatly affect the value of your investment.
Figure 4
Stop-Losses
The support and resistance characteristics of moving averages make them a great tool for managing risk. The ability
of moving averages to identify strategic places to set stop-loss orders allows traders to cut off losing positions before
they can grow any larger. As you can see in Figure 5, traders who hold a long position in a stock and set their stop-
loss orders below influential averages can save themselves a lot of money. Using moving averages to set stop-loss
orders is key to any successful trading strategy.
Figure 5
Factors To Consider
Data Used in Calculation
Most moving averages take the closing prices of a given asset and factor them into the calculation. We thought it
would be important to note that this does not always need to be the case. It is possible to calculate a moving
average by using the open, close, high, low or even the median. Even though there is little difference between these
calculations when plotted on a chart, the slight difference could still impact your analysis.
Finding an Appropriate Time Periods
Because most MAs represent the average of all the applicable daily prices, it should be noted that the time frame
does not always need to be in days. Moving averages can also be calculated using minutes, hours, weeks, months,
quarters, years etc. Why would a day trader care about how a 50-day moving average will affect the price over the
upcoming weeks? On the other hand, a day trader would want to pay attention to a 50-minute average to get an
idea of the relative cost of the security compared to the past hour. Some traders may even use the average price
over the past three minutes to gauge an uptake in short-term momentum.
No Average is Foolproof
As you know, nothing in the financial markets is for certain - certainly not when it comes to using technical indicators.
If a stock bounced off the support of a major average every time it came close, we would all be rich. One of the major
disadvantages of using moving averages is that they are relatively useless when an asset is trending sideways,
compared to the times when a strong trend is present. As you can see in Figure 1, the price of an asset can pass
through a moving average many times when the trend is moving sideways, making it difficult to decide how to trade.
This chart is a good example of how the support and resistance characteristics of moving averages are not always
present.
Figure 1
Responsiveness to Price Action
Traders who use moving averages in their trading will quickly admit that there is a battle between trying to make a
moving average responsive to changes in trend while not allowing it to be so sensitive that it causes a trader to
prematurely enter or exit a position. Short-term moving averages can be useful in identifying changing trends before
a large move occurs, but the downside is that this technique can also lead to being whipsawed in and out of a
position because these averages respond very quickly to changing prices. Because the quality of the transaction
signals can vary drastically depending on the time periods used in the calculation, it is highly recommended to look
at other technical indicators for confirmation of any move predicted by a moving average.
Beware of the Lag
Because moving averages are a lagging indicator, transaction signals will always occur after the price has moved
enough in one direction to cause the moving average to respond. This lagging characteristic can often work against
a trader and cause him or her to enter into a position at the least opportune time. For example, the only way for a
short-term moving average to cross above a long-term moving average is for the price to have recently moved
higher - many traders will use this bullish crossover as a buy signal. One major problem that often arises is that the
price may have already experienced a large increase before the transaction signal is presented. As you can see in
Figure 2, the large price gap creates a buy signal in late August, but this signal is too late because the price has
already moved up by more than 25% over the past 12 days and is becoming exhausted. In this case, the lagging
aspect of a moving average would work against the trader and likely result in a losing trade.
Figure 2
Strategies
Different investors use moving averages for different reasons. Some use them as their primary analytical tool, while
others simply use them as a confidence builder to back up their investment decisions.
Crossovers
A crossover is the most basic type of signal and is favored among many traders because it removes all emotion. The
most basic type of crossover is when the price of an asset moves from one side of a moving average and closes on
the other. Price crossovers are used by traders to identify shifts in momentum and can be used as a basic entry or
exit strategy. As you can see in Figure 1, a cross below a moving average can signal the beginning of a downtrend
and would likely be used by traders as a signal to close out any existing long positions.
Conversely, a close above a moving average from below may suggest the beginning of a new uptrend.
Figure 1
The second type of crossover occurs when a short-term average crosses through a long-term average. This signal
is used by traders to identify that momentum is shifting in one direction and that a strong move is likely approaching.
A buy signal is generated when the short-term average crosses above the long-term average, while a sell signal is
triggered by a short-term average crossing below a long-term average. As you can see from the chart below, this
signal is very objective, which is why it's so popular.
Figure 2
Triple Crossover and the Moving Average Ribbon
Additional moving averages may be added to the chart to increase the validity of the signal. Many traders will place
the five-, 10-, and 20-day moving averages
onto a chart and wait until the five-day average crosses up through the others – this is generally the primary buy
sign. Waiting for the10-day average to cross above the 20-day average is often used as confirmation, a tactic that
often reduces the number of false signals. Increasing the number of moving averages, as seen in the triple
crossover method, is one of the best ways to gauge the strength of a trend and the likelihood that the trend will
continue.
This begs the question: What would happen if you kept adding moving averages? Some people argue that if one
moving average is useful, then 10 or more must be even better. This leads us to a technique known as the moving
average ribbon. As you can see from the chart below, many moving averages are placed onto the same chart and
are used to judge the strength of the current trend. When all the moving averages are moving in the same direction,
the trend is said to be strong. Reversals are confirmed when the averages cross over and head in the opposite
direction.
Figure 3
Responsiveness to changing conditions is accounted for by the number of time periods used in the moving
averages. The shorter the time periods used in the calculations, the more sensitive the average is to slight price
changes. One of the most common ribbons starts with a 50-day moving average and adds averages in 10-day
increments up to the final average of 200. This type of average is good at identifying long-term trends/reversals.
Filters
A filter is any technique used in technical analysis to increase one's confidence
about a certain trade. For example, many investors may choose to wait until a security 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've "missed the boat". 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 invest 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 25-day 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.
Figure 4
EMA = (P x α) + (Previous EMA x (1 - α))
P = Current Price
α = Smoothing Factor = 2/1+N
N = Number of time periods
P = Current Price
α = Smoothing Factor = 2/1+N
N = Number of time periods
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