Introduction to Moving Averages

Moving averages are among the most popular and widely used indicators. Moving averages are a method of smoothing price data and removing noise to visually depict and measure a trend. Moving averages are the basis of many technical trend following systems. The moving average is a trend following, lagging indicator – as the moving average always lags price action – they serve to confirm trends once they have begun. Comparing moving averages of different time periods can also depict market momentum.

A moving average is an average of a given body of data. A moving average uses information, for example the closing price, over a given period of time, for example the previous 10 trading days. In this example, the moving average adds the closing prices over the previous 10 trading days and divides them by 10 to produce an average.

Moving averages are normally a trend following tool. Moving averages are a lagging indicator in that they can tell us that a trend has started by only after the fact.

The closing price is considered the most important price level of the trading day and is the figure most commonly used in calculating a moving average. A midpoint can also be used. Some technicians use an average of the high low and closing prices. Price bands can also be created by averaging the high and low prices separately.

Simple Moving Average (SMA)

The Simple Moving Average uses the arithmetic mean of a given set of values. The average is ‘moving’ as when new data becomes available the oldest data points are replaced by the new values. The drawback of this type of moving average is that it only takes the given time period into account. It also gives each day an equal weighting in the average, and some techicians feel that more recent price data should receive more weight.

Simple Moving Average

Chart courtesy of Prophet Financial Systems

Linearly Weighted Moving Average (WMA)

The linearly weighted moving average addresses the weighting issue by giving greater weight to more recent prices. For example, using a day 10 moving average the 10th day would be multiplied by 10, the 9th day by 9 and so on. The weighted moving average is most sensitive to recent price moves.

Exponentially Smoothed Moving Average (EMA)

This is the most popular of all the versions. The exponentially smoothed moving average gives greater weight to recent price data and also includes all the data in the life of the security. The EMA will respond to price changes faster than the SMA.

Time Periods

The most commonly used time periods in moving averages are 10, 15, 20, 30, 50, 100 and 200 days. The shorter the time frame, the more sensitive the average will be to price changes.

Interpretation of Moving Averages

Moving Averages can give signals in a number of different ways. They can identify trends, reversal points, measure market momentum and show support and resistance levels.

Moving Averages as Support and Resistance

Moving Averages often act as support and resistance levels, with prices stopping and reversing when they hit the moving average line.

Trend Confirmation

Moving Averages can be used as confirmation of a trend. For example, when the price is above the moving average and the average is in sloping upwards, this confirms that the market is in an uptrend and that the trader should be positioning their trades on the long side of the market.

Moving Average Level

When the moving average is lower than the previous day this signals the end of an uptrend. When the moving average is higher than the previous day this signals the end of a downtrend.

Moving Averages and Momentum

Market momentum can be measured by using multiple moving averages of different time periods and looking at the divergence between them. For example, in an uptrend, if the shorter term moving avergage is diverging from the longer term average – this confirms that the trend is gaining momentum.

Crossover Rule

The closing price moving above the moving average is interpreted as a buy signal. A closing price moving below the moving average is interpreted as a sell signal. This is known as the crossover rule. The moving average itself moving in the direction of the price as it crosses the moving average is confirmation of the signal.

Bear in mind that when a crossover occurs, the price does not always stay above (or below) the moving average, in an upward (or downward) crossover outliers and false signals will occur.

In the case of short time periods (such as 5 or 10 days) the MA will hug the price closer and there will be more crossings.

While the shorter time frame will produce more signals and more false signals, it will give trend signals earlier.

Note: the signals from longer term moving averages work better while a trend is still in effect  – but in the event of a trend reversal a shorter term MA will work better while the price is in the process of reversing.

A trader can improve performance and avoid getting whipsawed when using the crossover rule by using additional filters. For example looking for the close to remain above or below the moving average for an additonal x number of periods after the crossover occured.  Other filtering tools are considering the extent that the price went through the moving average, and looking at the volume present with the crossover taking place.

Using Two Moving Averages: The Double Crossover Method

In using multiple Moving Averages a trader can determine the momentum characteristics of the market. The Double Crossover Method desribes the interpretation of the shorter moving average crossing over the longer moving average as a trading signal. Two popular combinations are the 5 and 20 days moving averages and the 10 and 50 day moving averages.

The signal is generated when the shorter term moving average crosses above the longer term moving average generating a buy signal when the short average crosses above the longer, and a sell signal when the shorter average moves below the longer. The more space there is between the two moving averages, the better the signal. The divergence between the shorter term moving average from the longer term average of signals increasing market momentum – momentum to the upside, when the shorter term average is above the longer term average, momentum to the downside when the shorter term moving average is below the longer term average.

The Triple Crossover Method

The triple crossover method was popularized by R.C. Allen in the early 1970’s. This method gives fewer signals, but prevents you from getting whipsawed in a sideways market.

The most commonly used triple crossover combination is the 4-9-18 day moving average combination. This combination is a variation of the commonly used 5, 10 and 20 day moving average numbers and is used primarily in futures trading.

The 4 day average will follow the trend most closely, then the 9 and then the 18. In an  uptrend the 4 day should be above the 9 day which should be above the 18 day. In a downtrend the 4 day should be closest to the price trend followed by the 9 and then the 18 day averages.

A buy signal is generated when, in a downtrend, the 4 day crosses above both the 9 and 18 day averages.

A sell signal is generated when, in an uptrend, the 4 day moving average crosses below both the 9 and 18 day moving averages.

Moving Average Envelopes

Percentage envelopes indicate when a market has become over extended, when they have deviated too far from the moving average line. Envelopes are placed at fixed percentages above and below the moving averages.

Short term traders commonly use a 3% envelope around a 21 day moving average. Longer term traders commonly use a 5% envelope around a 10 week average. When the price moves outside the envelope this is an indication that the market is overextended.

Bollinger Bands®

Similar to moving average envelopes, Bollinger Bands are placed two standard deviations above and below the moving average, normally a 20 day average. Standard deviation is measure of the dispersion of a set of data from its mean, in this case the moving average.

Using two standard deviation ensures that the price will remain within the bands 95% of the time.

Prices touching the upper band signals overbought market conditions, prices touching the lower band signals oversold conditions.

The upper and lower bands can also be used as price targets. In an uptrend the price will likely move between the 20 day moving average and the upper band. When the prices crosses below the 20 day moving average this indicates possible trend reveral and would make the lower band a price target.

Bollinger Bands differ from Moving Average Envelopes in that instead of staying a constant width apart, they expand and contract based on the volatility over the time period of the moving average such as 20 days. When volatility is rising the distance between the bands will expand, and when volatility is low, the bands will contract.  When the bands are unusually far apart, this signals that the existing trend may be ending. When the bands are very close togethe, this signals that a new trend may be beginning.

Bollinger Bands work well in conjunction with momentum oscillators such as RSI.

Moving Average Convergence/Divergence (MACD)

MACD combines trend following and momentum characteristics. By comparing moving averages, MACD illustrates trend following characteristics, and by tracking the difference of the moving averages as an oscillator, MACD displays momentum. characteristics.

The MACD line is calculated by subtracting a 26 day exponential moving average from a 12 day exponential moving average. When MACD has a positive value, this means that the shorter term average (the 12 day) is above the longer (26) day average. This indicates rising momentum.

The slower line, called the signal line, is a 9 day exponential moving average of the MACD line.

When two moving averages converge this indicates a possible end to the existing trend. When the moving averages diverge – ie there is alot of space between them – this suggests that the trend is still healthy.

Moving Average work best in trending markets. Oscillators work better in sideways markets. MACD combines trend following and momentum in one indicator.