Simple Moving Average (SMA) is a technical analysis tool that denotes average price of an asset during a specific time period. The figure is calculated by aggregating the closing price of the asset over a particular period of time and then dividing the difference by the total time period. Short time period SMAs reflects changes in prices over short term duration, while the long time period. Note that equal weighting is given to the prices when calculating the metric.
Explanation of Simple Moving Average – SMA
Traders look at SMA of an asset to make investment decisions. More specifically, traders use the technical analysis tool to estimate price trends. Generally, a start of an uptrend is signaled when the short term SMA move above long term averages. The short term average price reflects the support levels when the prices are declining, which means that the price is expected to remain above that level during a particular period.
Usually the term moving average refers to simple moving average. Apart from estimating the prices trends, traders also use the technical tool to determine the momentum or rate of the price changes. The formula of calculating simple moving average is given below.
SMA = Sum of closing prices / No. of periods
Suppose that the closing prices of an asset from May 26 to 30 were $50, $51, $53, $52, and $56. The SMA can be calculated as $50+ $51+ $53+ $52+$56)/5 that equals $52. This price level is the average price in the past five days, which in itself will offer no meaningful information. Investors compare the short term period SMAs with long term period SMAs to predict future price trends. This information is useful in making informed financial decisions.
An advantage of using SMAs is that it eliminates the effect of strong price volatility. However, a drawback of the tool is that it does not differentiate in different period data points. For instance, the earlier closing prices are equally weighted as the recent price of an asset. This results in an incorrect estimation of the current price levels. The shortcomings of the simple moving average are eliminated by using weighted moving average (WMA) that gives different weights to different period data points.
Further Reading
- Is smarter better? A comparison of adaptive, and simple moving average trading strategies – www.sciencedirect.com [PDF]
- Moving average rules, volume and the predictability of security returns with feedforward networks – onlinelibrary.wiley.com [PDF]
- Are moving average trading rules profitable? Evidence from the European stock markets – www.tandfonline.com [PDF]
- Applying a combined max-min simple moving average trading strategy to market indexes – www.ceeol.com [PDF]
- Chasing trends: recursive moving average trading rules and internet stocks – www.sciencedirect.com [PDF]
- An empirical comparison of moving average envelopes and Bollinger Bands – www.tandfonline.com [PDF]
