Simple Moving Average - SMA Definition

A simple moving average (SMA) is an arithmetic moving average calculated by adding recent closing prices and then dividing that by the number of time periods in the calculation average. A simple, or arithmetic, moving average that is calculated by adding the closing price of the security for a number of time periods and then dividing this total by that same number of periods. Short-term averages respond quickly to changes in the price of the underlying, while long-term averages are slow to react.

There are other types of moving averages, including the exponential moving average (EMA).

$\begin{aligned} &\text{SMA}=\dfrac{A_1 + A_2 + ... + A_n}{n} \\ &\textbf{where:}\\ &A_n=\text{the price of an asset at period } n\\ &n=\text{the number of total periods}\\ \end{aligned}$​SMA=nA1​+A2​+...+An​​where:An​=the price of an asset at period nn=the number of total periods​

Let's look at a simple example of how to calculate the simple moving average of a security with the following closing prices over 15 days:

Week 1 (5 days) – 20, 22, 24, 25, 23

Week 2 (5 days) – 26, 28, 26, 29, 27

Week 3 (5 days) – 28, 30, 27, 29, 28

A 10-day moving average would average out the closing prices for the first 10 days as the first data point. The next data point would drop the earliest price, add the price on day 11 and take the average, and so on. Likewise, a 50-day moving average would accumulate enough data to average 50 consecutive days of data on a rolling basis.

A simple moving average is customizable in that it can be calculated for a different number of time periods, simply by adding the closing price of the security for a number of time periods and then dividing this total by the number of time periods, which gives the average price of the security over the time period. A simple moving average smooths out volatility, and makes it easier to view the price trend of a security. If the simple moving average points up, this means that the security's price is increasing. If it is pointing down it means that the security's price is decreasing. The longer the time frame for the moving average, the smoother the simple moving average. A shorter-term moving average is more volatile, but its reading is closer to the source data.

Analytical Significance

Moving averages are an important analytical tool used to identify current price trends and the potential for a change in an established trend. The simplest form of using a simple moving average in analysis is using it to quickly identify if a security is in an uptrend or downtrend. Another popular, albeit slightly more complex analytical tool, is to compare a pair of simple moving averages with each covering different time frames. If a shorter-term simple moving average is above a longer-term average, an uptrend is expected. On the other hand, a long-term average above a shorter-term average signals a downward movement in the trend.

Popular Trading Patterns

Two popular trading patterns that use simple moving averages include the death cross and a golden cross. A death cross occurs when the 50-day simple moving average crosses below the 200-day moving average. This is considered a bearish signal, that further losses are in store. The golden cross occurs when a short-term moving average breaks above a long-term moving average. Reinforced by high trading volumes, this can signal further gains are in store.

The major difference between an exponential moving average and a simple moving average is the sensitivity each one shows to changes in the data used in its calculation.

More specifically, the EMA gives a higher weighting to recent prices, while the SMA assigns equal weighting to all values. The two averages are similar because they are interpreted in the same manner and are both commonly used by technical traders to smooth out price fluctuations. Since EMAs place a higher weighting on recent data than on older data, they are more reactive to the latest price changes than SMAs are, which makes the results from EMAs more timely and explains why the EMA is the preferred average among many traders.

It is unclear whether or not more emphasis should be placed on the most recent days in the time period or on more distant data. Many traders believe that new data will better reflect the current trend the security is moving with; meanwhile others feel that privileging certain dates than others will biases the trend. Therefore, the SMA may rely too heavily on outdated data since it treats the 10th or 200th day's impact just as much as the first or second.

Similarly, the SMA relies wholly on historical data. Many people (including economists) believe that markets are efficient - that is, that current market prices already reflect all available information. If markets are indeed efficient, using historical data should tell us nothing about the future direction of asset prices.

To dig deeper into the SMA and how it's put to use, you may want to read some of our other articles on the topic including: Why is the 50-day simple moving average so popular among traders and analysts? and  Simple Moving Averages Make Trends Stand Out.