Technical Analysis Course online. Training, Coaching and Mentoring for Traders / Investors.

Moving Averages in Technical Analysis


MOVING AVERAGES

Moving averages are one of the most popular and easy to use tools available to the technical analyst. They smooth a data series and make it easier to spot trends, something that is especially helpful in volatile markets. They also form the building blocks for many other technical indicators and overlays.

The two most popular types of moving averages are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA). They are described in more detail below.

 

Simple Moving Average (SMA)

A simple moving average is formed by computing the average (mean) price of a security 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 SMA is calculated by adding the closing prices for the last 5 days and dividing the total by 5.

(10+ 11 + 12 + 13 + 14 = 60)  ( (60 / 5) = 12)

The calculation is repeated 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 15, then this new period would be added and the oldest day, which is 10, would be dropped. The new 5-day SMA would be calculated as follows:

(11 + 12 + 13 + 14 +15 = 65)  ( (65 / 5) = 13)



Over the last 2 days, the SMA moved from 12 to 13. As new days are added, the old days will be subtracted and the moving average will continue to move over time. In this example , using closing prices , day 10 is the first day possible to calculate a 10-day SMA. As the calculation continues, the newest day is added and the oldest day is subtracted. The 10-day SMA for day 11 is calculated by adding the prices of day 2 through day 11 and dividing by 10. The averaging process then moves on to the next day where the 10-day SMA for day 12 is calculated by adding the prices of day 3 through day 12 and dividing by 10.The chart above is a plot that contains the data sequence in the table. The SMA begins on day 10 and continues.
This simple illustration highlights the fact that all moving averages are lagging indicators and will always be "behind" the price. The price is trending down, but the SMA, which is based on the previous 10 days of data, remains above the price. If the price were rising, the SMA would most likely be below. Because moving averages are lagging indicators, they fit in the category of trend following indicators. When prices are trending, moving averages work well. However, when prices are not trending, moving averages can give misleading signals.


Exponential Moving Average Calculation
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 its 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:

EMA(current) = ( (Price(current) - EMA(prev) ) x Multiplier) + EMA(prev)

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.

Below is a table with the results of an exponential moving average calculation for Eastman Kodak. For the first period's exponential moving average, the simple moving average was used as the previous period's exponential moving average (yellow highlight for the 10th period). From period 11 onward, the previous period's EMA was used. The calculation in period 11 breaks down as follows:

  1. (C - P) = (61.33 - 63.682) = -2.352
  2. (C - P) x K = -2.352 x .181818 = -0.4276
  3. ((C - P) x K) + P = -0.4276 + 63.682 = 63.254


*The 10-period simple moving average is used for the first calculation only. After that the previous period's EMA is used.


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 EMAs than for longer ones but, again, they never completely disappear.



Simple Versus Exponential

From afar, it would appear that the difference between an EMA and a SMA is minimal. For this example, which uses only 20 trading days, the difference is minimal, but a difference nonetheless. The EMA is consistently closer to the actual price. On average, the EMA is 3/8 of a point closer to the actual price than the SMA.

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 EMA may be prone to quicker breaks. Some traders prefer to use exponential moving averages for shorter time periods to capture changes quicker. Some investors 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 trade off 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.



When to Use MA
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.
Because moving averages follow the trend, they work best when a security is trending and are ineffective when a security moves in a trading range. With this in mind, investors and traders should first identify securities 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 security'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 security forms a series of higher highs and higher lows. A downtrend is established when a security forms a series of lower lows and lower highs. A trading range is established if a security 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 security 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 security'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. Stocks that do not exhibit strong characteristics of trend may also require longer moving averages. 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. Examine how the moving average fits with the price data. 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  SMA and EMA. EMA are usually best for short-term situations that require a responsive moving average. SMA work well for longer-term situations that do not require a lot of sensitivity.


Uses for Moving Averages

There are many uses for moving averages, but two basic uses stand out:-


Trend identification/confirmation

The first trend identification technique uses the direction of the MA to determine the trend. If the MA is rising, the trend is considered up. If the MA is declining, the trend is considered down. The direction of a MA can be determined simply by looking at a plot of the MA or by applying an indicator to the MA. In either case, we would not want to act on every subtle change, but rather look at general directional movement and changes.


The second technique for trend identification is price location. The location of the price relative to the MA can be used to determine the basic trend. If the price is above the MA, the trend is considered up. If the price is below the MA, the trend is considered down.


The third technique for trend identification is based on the location of the shorter MA relative to the longer MA. If the shorter MA is above the longer MA, the trend is considered up. If the shorter MA is below the longer MA, the trend is considered down.


Support and Resistance level identification/confirmation
Another use of MA is to identify support and resistance levels. This is usually accomplished with one MA and is based on historical precedent. As with trend identification, support and resistance level identification through MA works best in trending markets.

Conclusions
MA 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 securities that are suitable for analysis with MA 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 MA need to be weighed against the disadvantages. MA 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. MA will help ensure that a trader is in line with the current trend. However, markets, stocks and securities spend a great deal of time in trading ranges, which render MA ineffective. Once in a trend, MA will keep you in, but also give late signals. Don't expect to get out at the top and in at the bottom using MA. 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.