Technical Indicators

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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 5-day 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 5-day 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 10-period exponential moving average weighs the most recent price 18.18% while a 20-period 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 percent-based EMA or as a period-based EMA. A percent-based EMA has a percentage as it's single parameter while a period-based EMA has a parameter that represents the duration of the EMA.

The formula for an exponential moving average is:

For a percentage-based EMA, "Multiplier" is equal to the EMA's specified percentage. For a period-based EMA, "Multiplier" is equal to 2 / (1 + N) where N is the specified number of periods.

For example, a 10-period EMA's Multiplier is calculated like this:

(2 / (Time periods+1)) = (2/10+1)) = 0.1818 (18.18%)

This means that a 10-period 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 long-term analysis, then the period of your moving average should be higher compared to short-term 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 200-Day SMAs on non-Daily 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 10-day moving average line on an hourly chart, you would need a 240-hour SMA (that is 10-day 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 short-term 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 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.

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:

1. 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.
2. 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.
3. 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 rate-of-change 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 period-over-period 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 real-time 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: zero-line crossings, trendline violations, and extreme values.

Zero-line crossings

Although the long-term 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 long-term 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 9-day RSI is not nearly as significant as an RSI for a 12-month 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 trend-reversal signals offered by the price itself.

RSI can be plotted for any time span. Wilder originally recommended using a 14-day RSI. Since then, the 9, 10 and 25-day RSIs have also become popular. The shorter the time period, the more sensitive the oscillator becomes. If the user is trading short-term 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 over-bought or over-sold area's, however the presence in over-bought and over-sold 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 re-entry into the mid-zone for the indicator after being in over-bought 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 trend-following 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 26-day and 12-day 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 12-day EMA is the faster and the 26-day EMA is the slower. Closing prices are used to form the moving averages. Usually, a 9-day 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 9-day EMA and a bearish crossover occurs when MACD moves below the 9-day EMA. For analysis purposes on the Merrill Lynch chart, MACD was plotted as the blue histogram and the 9-day EMA of MACD has been left off.

MACD measures the difference between two moving averages. A positive MACD indicates that the 12-day EMA is trading above the 26-day EMA. A negative MACD indicates that the 12-day EMA is trading below the 26-day EMA. If MACD is positive and rising, then the gap between the 12-day EMA and the 26-day EMA is widening. This indicates that the rate-of-change of the faster moving average is higher than the rate-of-change 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:

1. Positive divergence
2. Bullish moving average crossover
3. 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 9-day 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 9-day 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.

Topics Related to Technical Indicators:

Home: Fully Automated Forex Trading Systems with Automated Trade Execution on 300+ Forex Trading Strategies

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