Simple Moving Average (SMA): What It Is and the Formula

What Is a Simple Moving Average (SMA)?

A simple moving average (SMA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.

Key Takeaways

  • Simple moving averages calculate the average of a range of prices by the number of periods within that range.
  • A simple moving average is a technical indicator that can aid in determining if an asset price will continue or if it will reverse a bull or bear trend.
  • A simple moving average can be enhanced as an exponential moving average (EMA) that is more heavily weighted on recent price action.

Understanding Simple Moving Average (SMA)

A simple moving average (SMA) is an arithmetic moving average calculated by adding recent prices and then dividing that figure by the number of time periods in the calculation average. For example, one could add the closing price of a security for a number of time periods and then divide this total by that same number of periods. Short-term averages respond quickly to changes in the price of the underlying security, while long-term averages are slower to react. There are other types of moving averages, including the exponential moving average (EMA) and the weighted moving average (WMA).

Image

Investopedia / Sabrina Jiang

The formula for SMA is:

SMA = A 1 + A 2 + . . . + A n n where: A n = the price of an asset at period  n n = the number of total periods \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+...+Anwhere:An=the price of an asset at period nn=the number of total periods

For example, this is how you would calculate the simple moving average of a security with the following closing prices over a 15-day period.

Week One (5 days): 20, 22, 24, 25, 23

Week Two (5 days): 26, 28, 26, 29, 27

Week Three (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, then 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 because it can be calculated for different numbers of time periods. This is done 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.

One of the most popular simple moving averages is the 200-day SMA. However, there is a danger to following the crowd. As The Wall Street Journal explains, since thousands of traders base their strategies around the 200-day SMA, there is a chance that these predictions could become self-fulfilling and limit price growth.

Special Considerations

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 use of an SMA in technical analysis is using it to quickly determine if an asset is in an uptrend or downtrend.

Another popular, albeit slightly more complex, analytical use 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, if the long-term average is above a shorter-term average then a downtrend might be the expected outcome.

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 SMA crosses below the 200-day SMA. This is considered a bearish signal, indicating that further losses are in store. The golden cross occurs when a short-term SMA breaks above a long-term SMA. Reinforced by high trading volumes, this can signal further gains are in store.

Simple Moving Average vs. Exponential Moving Average

The major difference between an exponential moving average (EMA) 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 an 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.

Simple Moving Average (SMA)

Investopedia / Michela Buttignol

Limitations of Simple Moving Average

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. At the same time, other traders feel that privileging certain dates over others will bias the trend. Therefore, the SMA may rely too heavily on outdated data since it treats the 10th or 200th day's impact the same as the first or second day's.

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.

How Are Simple Moving Averages Used in Technical Analysis?

Traders use simple moving averages (SMAs) to chart the long-term trajectory of a stock or other security, while ignoring the noise of day-to-day price movements. This allows traders to compare medium- and long-term trends over a larger time horizon. For example, if the 200-day SMA of a security falls below its 50-day SMA, this is usually interpreted as a bearish death cross pattern and a signal of further declines. The opposite pattern, the golden cross, indicates potential for a market rally.

How Do You Calculate a Simple Moving Average?

To calculate a simple moving average, the number of prices within a time period is divided by the number of total periods. For instance, consider shares of Tesla closed at $10, $11, $12, $11, $14 over a five day period. The simple moving average of Tesla’s shares would equal $10 + $11 + $12 + $11 + $14 divided by 5, equaling $11.6.

What Is the Difference Between a Simple Moving Average and an Exponential Moving Average?

While a simple moving average gives equal weight to each of the values within a time period, an exponential moving average places greater weight on recent prices. Exponential moving averages are typically seen as a more timely indicator of a price trend, and because of this, many traders prefer using this over a simple moving average. Common short-term exponential moving averages include the 12-day and 26-day. The 50-day and 200-day exponential moving averages are used to indicate long-term trends.

Article Sources
Investopedia requires writers to use primary sources to support their work. These include white papers, government data, original reporting, and interviews with industry experts. We also reference original research from other reputable publishers where appropriate. You can learn more about the standards we follow in producing accurate, unbiased content in our editorial policy.
  1. The Wall Street Journal. "Does Chart Analysis Really Work?" Accessed Feb. 1, 2022.

Open a New Bank Account
×
The offers that appear in this table are from partnerships from which Investopedia receives compensation. This compensation may impact how and where listings appear. Investopedia does not include all offers available in the marketplace.
Sponsor
Name
Description
Take the Next Step to Invest
×
The offers that appear in this table are from partnerships from which Investopedia receives compensation. This compensation may impact how and where listings appear. Investopedia does not include all offers available in the marketplace.