A moving average is simply a way to smooth out price action over time. By “moving average”, we mean that you are taking the average closing price of a currency pair for the last ‘X’ number of periods. On a chart, it would look like this:
What Are Moving Averages?
Like every indicator, a moving average indicator is used to help us forecast future prices. By looking at the slope of the moving average, you can better determine the potential direction of market prices.
As we said, moving averages smooth out price action.
There are different types of moving averages and each of them has their own level of “smoothness”.
Generally, the smoother the moving average, the slower it is to react to the price movement.
The choppier the moving average, the quicker it is to react to the price movement. To make a moving average smoother, you should get the average closing prices over a longer time period.
Now, you’re probably thinking, “C’mon, let’s get to the good stuff. How can I use this to trade?”
In this section, we first need to explain to you the two major types of moving averages:
We’ll also teach you how to calculate them and give the pros and cons of each. Just like in every other lesson in the BabyPips.com School of Pipsology, you need to know the basics first!
After you’ve got that on lockdown like Argentinian soccer player Lionel Messi’s ball-handling skills, we’ll teach you the different ways to use moving averages and how to incorporate them into your trading strategy.
By the end of this lesson, you’ll be just as smooth as Messi’s!
Are you ready?
If you are, give us a “Heck yeah!”
If not, go back and reread the intro.
Once you’re pumped and ready to go, head to the next page.
Simple Moving Average (SMA) Explained
A simple moving average (SMA) is the simplest type of moving average in forex analysis (DUH!). Basically, a simple moving average is calculated by adding up the last “X” period’s closing prices and then dividing that number by X.
Don’t worry, we’ll make it crystal clear.
Calculating the Simple Moving Average (SMA)
If you plotted a 5 period simple moving average on a 1-hour chart, you would add up the closing prices for the last 5 hours, and then divide that number by 5. Voila! You have the average closing price over the last five hours! String those average prices together and you get a moving average!
If you were to plot a 5-period simple moving average on a 10-minute currency chart, you would add up the closing prices of the last 50 minutes and then divide that number by 5.
If you were to plot a 5 period simple moving average on a 30 minute chart, you would add up the closing prices of the last 150 minutes and then divide that number by 5.
If you were to plot the 5 period simple moving average on the 4 hr. chart… Okay, okay, we know, we know. You get the picture!
Most charting packages will do all the calculations for you. The reason we just bored you (yawn!) with a “how to” on calculating simple moving averages is because it’s important to understand so that you know how to edit and tweak the indicator.
Understanding how an indicator works means you can adjust and create different strategies as the market environment changes.
Now, as with almost any other forex indicator out there, moving averages operate with a delay. Because you are taking the averages of past price history, you are really only seeing the general path of the recent past and the general direction of “future” short term price action.
Here is an example of how moving averages smooth out the price action.
On chart above, we’ve plotted three different SMAs on the 1-hour chart of USD/CHF. As you can see, the longer the SMA period is, the more it lags behind the price.
Notice how the 62 SMA is farther away from the current price than the 30 and 5 SMAs.
This is because the 62 SMA adds up the closing prices of the last 62 periods and divides it by 62. The longer period you use for the SMA, the slower it is to react to the price movement.
The SMAs in this chart show you the overall sentiment of the market at this point in time. Here, we can see that the pair is trending.
Instead of just looking at the current price of the market, the moving averages give us a broader view, and we can now gauge the general direction of its future price. With the use of SMAs, we can tell whether a pair is trending up, trending down, or just ranging.
There is one problem with the simple moving average: they are susceptible to spikes. When this happens, this can give us false signals. We might think that a new currency trend may be developing but in reality, nothing changed.
In the next lesson, we will show you what we mean, and also introduce you to another type of moving average to avoid this problem.
Exponential Moving Average (EMA) Explained
As we said in the previous lesson, simple moving averages can be distorted by spikes. We’ll start with an example.
Let’s say we plot a 5-period SMA on the daily chart of EUR/USD.
The closing prices for the last 5 days are as follows:
Day 1: 1.3172
Day 2: 1.3231
Day 3: 1.3164
Day 4: 1.3186
Day 5: 1.3293
The simple moving average would be calculated as follows:
(1.3172 + 1.3231 + 1.3164 + 1.3186 + 1.3293) / 5 = 1.3209
Simple enough, right?
Well what if there was a news report on Day 2 that causes the euro to drop across the board. This causes EUR/USD to plunge and close at 1.3000. Let’s see what effect this would have on the 5 period SMA.
Day 1: 1.3172
Day 2: 1.3000
What you just saw was a classic Bollinger Bounce. The reason these bounces occur is because Bollinger bands act like dynamic support and resistance levels.
The longer the time frame you are in, the stronger these bands tend to be. Many traders have developed systems that thrive on these bounces and this strategy is best used when the market is ranging and there is no clear trend.
Now let’s look at a way to use Bollinger Bands when the market does trend.
The Bollinger Squeeze is pretty self-explanatory. When the bands squeeze together, it usually means that a breakout is getting ready to happen.
If the candles start to break out above the top band, then the move will usually continue to go up. If the candles start to break out below the lower band, then price will usually continue to go down.
Looking at the chart above, you can see the bands squeezing together. The price has just started to break out of the top band. Based on this information, where do you think the price will go?
With an MACD chart, you will usually see three numbers that are used for its settings.
- The first is the number of periods that is used to calculate the faster moving average.
- The second is the number of periods that is used in the slower moving average.
- And the third is the number of bars that is used to calculate the moving average of the difference between the faster and slower moving averages.
For example, if you were to see “12, 26, 9″ as the MACD parameters (which is usually the default setting for most charting packages), this is how you would interpret it:
- The 12 represents the previous 12 bars of the faster moving average.
- The 26 represents the previous 26 bars of the slower moving average.
- The 9 represents the previous 9 bars of the difference between the two moving averages. This is plotted by vertical lines called a histogram (the green lines in the chart above).
There is a common misconception when it comes to the lines of the MACD. The two lines that are drawn are NOT moving averages of the price. Instead, they are the moving averages of the DIFFERENCE between two moving averages.
In our example above, the faster moving average is the moving average of the difference between the 12 and 26-period moving averages. The slower moving average plots the average of the previous MACD line. Once again, from our example above, this would be a 9-period moving average.
This means that we are taking the average of the last 9 periods of the faster MACD line and plotting it as our slower moving average. This smoothens out the original line even more, which gives us a more accurate line.
The histogram simply plots the difference between the fast and slow moving average. If you look at our original chart, you can see that, as the two moving averages separate, the histogram gets bigger.
This is called divergence because the faster moving average is “diverging” or moving away from the slower moving average.
As the moving averages get closer to each other, the histogram gets smaller. This is called convergence because the faster moving average is “converging” or getting closer to the slower moving average.
And that, my friend, is how you get the name, Moving Average Convergence Divergence! Whew, we need to crack our knuckles after that one!