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.
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.
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.