Simple Moving Average (SMA)

This is the most common method used to calculate the moving average of prices. It simply takes the sum of all of the past closing prices over the time period and divides the result by the number of prices used in the calculation. As you can see in the figure above, a trader is able to make the average less responsive to changing prices by increasing the number of periods used in the calculation. Increasing the number of time periods in the calculation is one of the best ways to gauge the strength of the long-term trend and the likelihood that it will reverse.

Simple moving averages became the preferred method for tracking market prices because they are quick to calculate and easy to understand. Early market practitioners operated without the use of the sophisticated chart metrics in use today, so they relied primarily on market prices as their sole guides. They calculated market prices by hand, and graphed those prices to denote trends and market direction. This process was quite tedious, but proved quite profitable with confirmation of further studies.

SMA Calculation

A simple moving average is formed by computing the average price of a security over a specific number of periods. Most moving averages are based on closing prices. A 5-day simple moving average is the five day sum of closing prices divided by five. As its name implies, a moving average is an average that moves. Old data is dropped as new data comes available. This causes the average to move along the time scale. Below is an example of a 5-day moving average evolving over three days.

Daily Closing Prices: 11,12,13,14,15,16,17

First day of 5-day SMA: (11 + 12 + 13 + 14 + 15) / 5 = 13

Second day of 5-day SMA: (12 + 13 + 14 + 15 + 16) / 5 = 14

Third day of 5-day SMA: (13 + 14 + 15 + 16 + 17) / 5 = 15

The first day of the moving average simply covers the last five days. The second day of the moving average drops the first data point (11) and adds the new data point (16). The third day of the moving average continues by dropping the first data point (12) and adding the new data point (17). In the example above, prices gradually increase from 11 to 17 over a total of seven days. Notice that the moving average also rises from 13 to 15 over a three day calculation period. Also notice that each moving average value is just below the last price. For example, the moving average for day one equals 13 and the last price is 15. Prices the prior four days were lower and this causes the moving average to lag.

Limitations of SMA

Many individuals argue that the usefulness of this type of average is limited because each point in the data series has the same impact on the result regardless of where it occurs in the sequence. The critics argue that the most recent data is more important and, therefore, it should also have a higher weighting. This type of criticism has been one of the main factors leading to the invention of other forms of moving averages.