Forex Trading

Moving Average Convergence Divergence – MACD

MACD, which stands for Moving Average Convergence Divergence, is a trend-following momentum indicator that shows the relationship between two moving averages of prices. Developed by Gerald Appel, MACD is one of the simplest and most reliable indicators available. This tool is used to identify moving average which indicate a new trend, regardless of whether it is bullish or bearish. After all, the most important priority in trading is to find a trend, because the most money revolves around it.



With MACD chart, you'll usually see three numbers that are used to configure it:
1. First is the number of periods that is used to calculate the faster moving average
2. Second is the number of periods that is used to calculate the slower moving average
3. Third is the number of candles that are used to calculate the moving average of the difference between faster and slower moving average

The lines on MACD charts are often misunderstood, two lines that are drawn are not the moving average of prices. They are the moving average of the difference between the two moving average.

In our example, the faster moving average is the moving average of the difference between 12 and 26 periods of moving average. Slower moving average outlines a previous average of MACD lines. We calculate the average of the last 9 periods of faster MACD line, and outline it as a slower moving average. This moderates the original lines, giving us a more accurate chart.

Histogram outlines the difference between faster and slower moving average. If you look at the above chart you will see that when the two moving averages separate, histogram becomes greater. This is called divergence, because the faster moving average is diverging from the slower moving average.

When the moving average lines come closer together, histogram becomes smaller. This is called convergence, because faster moving average is converging, coming closer to slower moving average. This is why this indicator is called the Moving Average Convergence Divergence.

MACD Formula

The most popular formula for the "standard" MACD is the difference between 26-day and 12-day Exponential Moving Averages (EMAs). This is the formula that is used in many popular technical analysis programs and quoted in most technical analysis books. 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.

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 along side to act as a trigger line. A bullish crossover occurs when MACD moves above its 9-day EMA, and a bearish crossover occurs when MACD moves below its 9-day EMA. The histogram represents the difference between MACD and its 9-day EMA. The histogram is positive when MACD is above its 9-day EMA and negative when MACD is below its 9-day EMA.

MACD Bullish Signals

MACD generates bullish signals from three main sources:
1. Positive Divergence
2. Bullish Moving Average Crossover
3. Bullish Centerline Crossover

Positive Divergence

A Positive Divergence occurs when MACD begins to advance and the currency 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.

Bullish Moving Average Crossover

A Bullish Moving Average Crossover occurs when MACD moves above its 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. Bullish Moving Average Crossovers are used occasionally to confirm a positive divergence. A positive divergence can be considered valid when a Bullish Moving Average Crossover occurs after the MACD Line makes its second "higher Low".
Sometimes it is prudent to apply a price filter to the Bullish Moving Average Crossover 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.

Bullish Centerline Crossover

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 Centerline Crossover, the Bullish Centerline Crossover can act as a confirmation signal. Of the three signals, moving average crossover are probably the second most common signals.

Bearish Signals

MACD generates bearish signals from three main sources. These signals are mirror reflections of the bullish signals:
1. Negative Divergence
2. Bearish Moving Average Crossover
3. Bearish Centerline Crossover

Negative Divergence

A Negative Divergence forms when the currency advances or moves sideways, and the MACD declines. The Negative Divergence in MACD can take the form of either a lower High or a straight decline. Negative Divergences are probably the least common of the three signals, but are usually the most reliable, and can warn of an impending peak.

Thee are two possible means of confirming a Negative Divergence. First, the indicator can form a lower Low. This is traditional peak-and-trough analysis applied to an indicator. With the lower High and subsequent lower Low, the uptrend for MACD has changed from bullish to bearish. Second, a Bearish Moving Average Crossover (which is explained below) can act to confirm a negative divergence. As long as MACD is trading above its 9-day EMA, or trigger line, it has not turned down and the lower High is difficult to confirm. When MACD breaks below its 9-day EMA, it signals that the short-term trend for the indicator is weakening, and a possible interim peak has formed.

Bearish Moving Average Crossover

The most common signal for MACD is the moving average crossover. A Bearish Moving Average Crossover occurs when MACD declines below its 9-day EMA. Not only are these signals the most common, but they also produce the most false signals. As such, moving average crossovers should be confirmed with other signals to avoid whipsaws and false readings.

Sometimes a currency can be in a strong uptrend, and MACD will remain above its trigger line for a sustained period of time. In this case, it is unlikely that a Negative Divergence will develop and a different signal is needed to identify a potential change in momentum.

Bearish Centerline Crossover

A Bearish Centerline Crossover occurs when MACD moves below zero and into negative territory. This is a clear indication that momentum has changed from positive to negative, or from bullish to bearish. The centerline crossover can act as an independent signal, or confirm a prior signal such as a moving average crossover or negative divergence. Once MACD crosses into negative territory, momentum, at least for the short term, has turned bearish.

The significance of the centerline crossover will depend on the previous movements of MACD as well. If MACD is positive for many weeks, begins to trend down, and then crosses into negative territory, it would be bearish. However, if MACD has been negative for a few months, breaks above zero, and then back below, it might be a correction. In order to judge the significance of a centerline crossover, traditional technical analysis can be applied to see if there has been a change in trend, higher High or lower Low.

Using a Combination of Signals

Even though some traders may use only one of the above signals to form a buy or a sell signal, using a combination can generate more robust signals which will increase your chances of catching a trend and generating a profit.



MACD-Histogram

In 1986, Thomas Aspray developed the MACD-Histogram. Some of his findings were presented in a series of articles for Technical Analysis of Stocks and Commodities. Aspray noted that MACD's lag would sometimes miss important moves, especially when applied to weekly charts. He first experimented by changing the moving averages and found that shorter moving averages did indeed speed up the signals. However, he was looking for a means to anticipate MACD crossovers. One of the answers he came up with was the MACD-Histogram.



Definition and Construction

The MACD-Histogram represents the difference between the MACD and its trigger line, the 9-day EMA of MACD. The plot of this difference is presented as a histogram, making centerline crossovers and divergences easily identifiable. A centerline crossover for the MACD-Histogram is the same as a moving average crossover for MACD. If you will recall, a moving average crossover occurs when MACD moves above or below the trigger line.

If the value of MACD is larger than the value of its 9-day EMA, then the value on the MACD-Histogram will be positive. Conversely, if the value of MACD is less than its 9-day EMA, then the value on the MACD-Histogram will be negative.

Further increases or decreases in the gap between MACD and its trigger line will be reflected in the MACD-Histogram. Sharp increases in the MACD-Histogram indicate that MACD is rising faster than its 9-day EMA and bullish momentum is strengthening. Sharp declines in the MACD-Histogram indicate that MACD is falling faster than its 9-day EMA and bearish momentum is increasing.



On the chart above, we can see that the MACD-Histogram movements are relatively independent of the actual MACD. Sometimes the MACD is rising while the MACD-Histogram is falling. At other times, the MACD is falling while the MACD-Histogram is rising. The MACD-Histogram does not reflect the absolute value of the MACD, but rather the value of the MACD relative to its 9-day EMA. Usually, but not always, a move in the MACD is preceded by a corresponding divergence in the MACD-Histogram.

1. The first point shows a sharp positive divergence in the MACD-Histogram that preceded a Bullish Moving Average Crossover.
2. On the second point, the MACD continued to new Highs but the MACD-Histogram formed two equal Highs. Although not a textbook case of Positive Divergence, the equal High failed to confirm the strength seen in the MACD.
3. A Positive Divergence formed when the MACD-Histogram formed a higher Low and the MACD continued lower.
4. A Negative Divergence formed when the MACD-Histogram formed a lower High and the MACD continued higher.The first point shows a sharp positive divergence in the MACD-Histogram that preceded a Bullish Moving Average Crossover.

Usage

Thomas Aspray designed the MACD-Histogram as a tool to anticipate a moving average crossover in the MACD. Divergences between MACD and the MACD-Histogram are the main tool used to anticipate moving average crossovers. A Positive Divergence in the MACD-Histogram indicates that the MACD is strengthening and could be on the verge of a Bullish Moving Average Crossover. A Negative Divergence in the MACD-Histogram indicates that the MACD is weakening, and it foreshadows a Bearish Moving Average Crossover in the MACD.

The best use for the MACD-Histogram is in identifying periods when the gap between the MACD and its 9-day EMA is either widening or shrinking. Broadly speaking, a widening gap indicates strengthening momentum and a shrinking gap indicates weakening momentum. Usually a change in the MACD-Histogram will precede any changes in the MACD.

Signals

The main signal generated by the MACD-Histogram is a divergence followed by a moving average crossover. A bullish signal is generated when a Positive Divergence forms and there is a Bullish Centerline Crossover. A bearish signal is generated when there is a Negative Divergence and a Bearish Centerline Crossover. Keep in mind that a centerline crossover for the MACD-Histogram represents a moving average crossover for the MACD.

Divergences can take many forms and varying degrees. Generally speaking, two types of divergences have been identified: the slant divergence and the peak-trough divergence.

Slant Divergence

A Slant Divergence forms when there is a continuous and relatively smooth move in one direction (up or down) to form the divergence. Slant Divergences generally cover a shorter time frame than divergences formed with two peaks or two troughs. A Slant Divergence can contain some small bumps (peaks or troughs) along the way. The world of technical analysis is not perfect and there are exceptions to most rules and hybrids for many signals.

Peak-Trough Divergence

A peak-trough divergence occurs when at least two peaks or two troughs develop in one direction to form the divergence. A series of two or more rising troughs (higher lows) can form a Positive Divergence and a series of two or more declining peaks (lower highs) can form a Negative Divergence. Peak-trough Divergences usually cover a longer time frame than slant divergences. On a daily chart, a peak-trough divergence can cover a time frame as short as two weeks or as long as several months.

Usually, the longer and sharper the divergence is, the better any ensuing signal will be. Short and shallow divergences can lead to false signals and whipsaws. In addition, it would appear that Peak-trough Divergences are a bit more reliable than Slant Divergences. Peak-trough Divergences tend to be sharper and cover a longer time frame than Slant Divergences.

Conclusion

One of the primary benefits of MACD is that it incorporates aspects of both momentum and trend in one indicator. As a trend-following indicator, it will not be wrong for very long. The use of moving averages ensures that the indicator will eventually follow the movements of the underlying security. By using Exponential Moving Averages (EMAs), as opposed to Simple Moving Averages (SMAs), some of the lag has been taken out.

As a momentum indicator, MACD has the ability to foreshadow moves in the underlying currency. MACD divergences can be key factors in predicting a trend change. A Negative Divergence signals that bullish momentum is waning, and there could be a potential change in trend from bullish to bearish. This can serve as an alert for traders to take some profits in long positions, or for aggressive traders to consider initiating a short position.

One of the beneficial aspects of the MACD is also one of its drawbacks. Moving averages, be they simple, exponential or weighted, are lagging indicators. Even though MACD represents the difference between two moving averages, there can still be some lag in the indicator itself. This is more likely to be the case with weekly charts than daily charts. One solution to this problem is the use of the MACD-Histogram.

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.

With the emergence of computerized analysis, it has become highly unreliable in the modern era, and standard MACD based trade execution now produces a greater distribution of losing trades. Some additions have been made to MACD over the years but even with the addition of the MACD-Histogram, it remains a lagging indicator. It has often been criticized for failing to respond in mild/volatile market conditions. Since the crash of the market in 2000, most strategies no longer recommend using MACD as the primary method of analysis, but instead believe it should be used as a monitoring tool only. It is prone to whipsaw, and if a trader is not careful it is possible that they might suffer substantial loss, especially if they are leveraged or trading options. Since Gerald Appel developed the MACD, there have been hundreds of new indicators introduced to technical analysis. While many indicators have come and gone, the MACD has stood the test of time.

What is Moving Average?

Moving average is one of the most popular and easy to use tools available for doing technical analysis. It means the average price of a currency over a specified time period (the most common being 20, 30, 50, 100 and 200 days), used in order to spot pricing trends by flattening out large fluctuations. Moving average data is used to create charts that show whether a currency’s price is trending up or down. They can be used to track daily, weekly, or monthly patterns. Each new day's (or week's or month's) numbers are added to the average and the oldest numbers are dropped, thus, the average "moves" over time. In general, the shorter the time frame used, the more volatile the prices will appear, so, for example, 20 day moving average lines tend to move up and down more than 200 day moving average lines. There are four different types of moving averages: Simple (also referred to as Arithmetic), Exponential, Smoothed and Linear Weighted. Moving averages may be calculated for any sequential data set, including opening and closing prices, highest and lowest prices, trading volume or any other indicators. It is often the case when double moving averages are used.



The only thing where moving averages of different types diverge considerably from each other is when weight coefficients, which are assigned to the latest data, are different. In case we are talking of simple moving average, all prices of the time period in question are equal in value. Exponential and Linear Weighted Moving Averages attach more value to the latest prices. The most common way to interpreting the price moving average is to compare its dynamics to the price action. When the instrument price rises above its moving average, a buy signal appears, if the price falls below its moving average, what we have is a sell signal. This trading system, which is based on the moving average, is not designed to provide entrance into the market right in its lowest point, and its exit right on the peak. It allows acting according to the following trend: to buy soon after the prices reach the bottom, and to sell soon after the prices have reached their peak. Moving averages may also be applied to indicators. That is where the interpretation of indicator moving averages is similar to the interpretation of price moving averages: if the indicator rises above its moving average, that means that the ascending indicator movement is likely to continue: if the indicator falls below its moving average, this means that it is likely to continue going downward.

Simple Moving Average (SMA)

Simple Moving Average is the simplest type of moving averages. Basically, SMA is calculated by adding the last number in the period from the closing price, and then dividing that number with a period. Let me explain in example, if you select SMA 5 on a 1 hour graph, add the closing prices for the last 5 hours, and then divide that number by 5. If you select SMA 5 on a 30 minute graph, you will add the closing prices for the past 150 minutes (30*5), and then divide that number by 5. In the same way you can calculate SMA for any time period.

Most of the trading platforms will make all these calculations for you. The reason why I am bothering you with this component of technical analysis is because it is extremely important to understand how to calculate the moving average. If you understand how every moving average is calculated, you can make your own decision, which type is the best for you.

Like any other indicator, SMA works with a delay. Because you observe the average price, you are actually looking at the "forecast" of future prices, not the concrete future. Here's an example of how moving averages reduce the price activity:



On the previous chart you can see 3 different SMA. As you can see, the bigger period SMA you take, the more it stays behind the more prices. You probably noticed that the 62 SMA is much further away from current prices then 30 and 5 SMA. This is because with 62 SMA you are adding closing prices from the last 62 periods and dividing it with 62. The higher the number of periods that you are using, the slower is reaction to the movement of prices. SMA on this graph shows the overall sentiment in the market in a given period. Instead of just looking at the current price on the market, moving averages provide a broader view, and give us the general prediction of prices in the future.

SMA = SUM (CLOSE, N)/N ; Where:
N = number of calculation periods

Exponential Moving Average (EMA)

Although SMA is an excellent tool, one major problem is associated with it: SMA is very sensitive to sudden jumps (spikes). By looking at the next example you will better understand what I mean:
Suppose that we draw a 5 SMA on the daily chart of EUR / USD and the closing prices for the last 5 days are as follows: 1st day - 1.2345, 2nd day - 1.2350, 3rd day - 1.2360, 4th day - 1.2365, 5th day - 1.2370. SMA would be calculated as: (1.2345+1.2350+1.2360+1.2365+1.2370)/5 = 1.2358. But what if the 2nd day price was 1.2300? SMA result would be much lower and you get the impression that the price is going down, when in reality, 2nd day may perhaps have been only one remote event (for example, reduction of the interest rate).

What I am trying to indicate is that the SMA may sometimes be too simple. If there was only a way to filter the jumps so that we do not get the wrong picture and make the most out of moving averages. It exists and is called the Exponential Moving Average (EMA).

EMA is a type of moving average that is similar to Simple Moving Average, except that more weight is given to the latest data. The Exponential Moving Average is also known as "Exponentially Weighted Moving Average". This type of moving average reacts faster to recent price changes than a Simple Moving Average. In our example above, EMA would put more weight on the 3rd-5th day, which means that jump on the 2nd would have a lesser value and would not influence so much on the moving average. It would put more emphasis on what traders are doing right now. While trading, it is more important to see what merchants are doing right now, not what they were doing last week or last month.



EMA = (CLOSE(i)*P)+(EMA(i-1)*(100-P)) ; Where:
CLOSE(i) = the price of the current period closure
EMA(i-1) = Exponentially Moving Average of the previous period closure
P = the percentage of using the price value

Smoothed Moving Average (SMMA)

A Smoothed Moving Average is sort of a cross between a Simple Moving Average and an Exponential Moving Average, only with a longer period applied. The Smoothed Moving Average gives the recent prices an equal weighting to the historic ones. The calculation does not refer to a fixed period, but rather takes all available data series into account. This is achieved by subtracting yesterday’s Smoothed Moving Average from today’s price. Adding this result to yesterday’s Smoothed Moving Average, results in today’s moving average.

In a Simple Moving Average, the price data have an equal weight in the computation of the average. Also, in a Simple Moving Average, the oldest price data are removed from the moving average as a new price is added to the computation. The Smoothed Moving Average uses a longer period to determine the average, assigning a weight to the price data as the average is calculated. Thus, the oldest price data points in the Smoothed Moving Average are never removed, but they have only a minimal impact on the moving average, which is similar to how an Exponential Moving Average places more weight on the more recent data.

The first value of this smoothed moving average is calculated as the simple moving average (SMA):
SUM1 = SUM(CLOSE, N)
SMMA1 = SUM1/N

The second and succeeding moving averages are calculated according to this formula:
SMMA(i) = (SUM1-SMMA1+CLOSE(i))/N ; Where:
SUM1 = the total sum of closing prices for N periods
SMMA1 = the smoothed moving average of the first bar
SMMA(i) = the smoothed moving average of the current bar (except for the first one)
CLOSE(i) = the current closing price
N = the smoothing period



SMA versus EMA

If you want a moving average which will match the movement of prices quite quickly, then the EMA with a short period (eg. 3, 5, 8) is the best choice for you. This may help to ''hunt down'' the trend in the early stage, which will result in higher profits. Specifically, the earlier you have caught the trend, the more you can ''ride'' through it, and you can make more money. The pitfall is that while using this type of moving average you can get a false signal which you won’t recognize and lose your investment. Since the moving average quickly matches the price, you can even think that a new trend is forming, but in fact it is just an abrupt jump, which returns to the starting position (spike).

With SMA the situation is completely opposite. If you want the moving average to respond more precisely and slowly to the price changes, then the longer period SMA is the best choice for you. Although slow responding to the price changes will save you from many possible pitfalls, the smaller SMA may also result in too much delay and missing of a good trade.



Uses for Moving Averages

There are many uses for moving averages, but three basic uses stand out:
1. Trend identification/confirmation
2. Support and Resistance level identification/confirmation
3. Trading Systems

Which is better?

Which moving average you use will depend on your trading and investing style and preferences. The Simple Moving Average obviously has a lag, but the Exponential Moving Average may be prone to quicker breaks. Some traders prefer to use Exponential Moving Averages for shorter time periods to capture changes quicker, while others prefer Simple Moving Averages over long time periods to identify long-term trend changes. In addition, much will depend on the individual security in question. Moving average type and length of time will depend greatly on the individual security and how it has reacted in the past.

The initial thought for some is that greater sensitivity and quicker signals are bound to be beneficial. This is not always true and brings up a great dilemma for the technical analyst: the tradeoff between sensitivity and reliability. The more sensitive an indicator is, the more signals that will be given. These signals may prove timely, but with increased sensitivity comes an increase in false signals. The less sensitive an indicator is, the fewer signals that will be given. However, less sensitivity leads to fewer and more reliable signals. Sometimes these signals can be late as well.

For moving averages, the same dilemma applies. Shorter moving averages will be more sensitive and generate more signals. The EMA, which is generally more sensitive than the SMA, will also be likely to generate more signals. However, there will also be an increase in the number of false signals and whipsaws. Longer moving averages will move slower and generate fewer signals. These signals will likely prove more reliable, but they also may come late. Each investor or trader should experiment with different moving average lengths and types to examine the trade-off between sensitivity and signal reliability.

Trend-Following Indicator

Moving averages smooth out a data series and make it easier to identify the direction of the trend. Because past price data is used to form moving averages, they are considered lagging, or trend following, indicators. Moving averages will not predict a change in trend, but rather follow behind the current trend. Therefore, they are best suited for trend identification and trend following purposes, not for prediction.

When to Use

Because moving averages follow the trend, they work best when a currency is trending and are ineffective when a currency moves in a trading range. With this in mind, investors and traders should first identify currencies that display some trending characteristics before attempting to analyze with moving averages. This process does not have to be a scientific examination. Usually, a simple visual assessment of the price chart can determine if a security exhibits characteristics of trend.

In its simplest form, a currency’s price can be doing only one of three things: trending up, trending down or trading in a range. An uptrend is established when a currency forms a series of higher highs and higher lows. A downtrend is established when a currency forms a series of lower lows and lower highs. A trading range is established if a currency cannot establish an uptrend or downtrend. If a security is in a trading range, an uptrend is started when the upper boundary of the range is broken and a downtrend begins when the lower boundary is broken.

Once a currency has been deemed to have enough characteristics of trend, the next task will be to select the number of moving average periods and type of moving average. The number of periods used in a moving average will vary according to the currency's volatility, trendiness and personal preferences. The more volatility there is, the more smoothing that will be required and hence the longer the moving average. There is no one set length, but some of the more popular lengths include 21, 50, 89, 150 and 200 days as well as 10, 30 and 40 weeks. Short-term traders may look for evidence of 2-3 week trends with a 21-day moving average, while longer-term investors may look for evidence of 3-4 month trends with a 40-week moving average. Trial and error is usually the best means for finding the best length. If there are too many breaks, lengthen the moving average to decrease its sensitivity. If the moving average is slow to react, shorten the moving average to increase its sensitivity. In addition, you may want to try using both Simple and Exponential Moving Averages. Exponential Moving Averages are usually best for short-term situations that require a responsive moving average. Simple Moving Averages work well for longer-term situations that do not require a lot of sensitivity.

Conclusions

Moving averages can be effective tools to identify and confirm trend, identify support and resistance levels, and develop trading systems. However, traders and investors should learn to identify currencies that are suitable for analysis with moving averages and how this analysis should be applied. Usually, an assessment can be made with a visual examination of the price chart, but sometimes it will require a more detailed approach.

The advantages of using moving averages need to be weighed against the disadvantages. Moving averages are trend following, or lagging, indicators that will always be a step behind. This is not necessarily a bad thing though. After all, the trend is your friend and it is best to trade in the direction of the trend. Moving averages will help ensure that a trader is in line with the current trend. However, markets, currencies spend a great deal of time in trading ranges, which render moving averages ineffective. Once in a trend, moving averages will keep you in, but also give late signals. Don't expect to get out at the top and in at the bottom using moving averages. As with most tools of technical analysis, moving averages should not be used on their own, but in conjunction with other tools that complement them. Using moving averages to confirm other indicators and analysis can greatly enhance technical analysis.