Understanding Moving Averages

In investing as well as trading in stocks, there are many tools that people can use to help them make calculated risks. One of them is the moving average. It is one of the more common technical indicators being used by both stock traders and stock investors. This tool is basically used by traders to measure momentum. Although there can be many forms of moving averages, they all serve the same purpose-  to smoothen out price data in order to determine whether there is a likelihood of a certain trade to continue.

Where Is It Used?

The primary use of moving averages it to help provide an insight as to the direction of a current trend. Although there are various types of moving averages, all of them are calculated as a result of averaging several past data points. Once a moving average is determined, it is then being plotted into a chart to allow traders to see a bigger picture of the collected past data rather than depending on the daily price changes in the markets.

Stock Trading And Investing Tool

Moving averages have become quite a popular trading tool that traders as well as investors commonly use. There are several other trading indicators developed and created to help traders. Some may be more popular than others. But only a few of such indicators tend to provide an objective, reliable and useful information such as moving averages.

Types Of Moving Averages

There are several types of moving averages that help users determine the direction of a current trend. The most basic type is called the simple moving average or SMA. It is calculated by taking the arithmetic mean of a given set of data values. A 10-day simple moving average can be calculated by adding up the closing prices of a certain stock for the past 10 days and then dividing the total by 10. The same process goes with a 50-day or 100-day simple moving average.

Another type of moving average is what is known as exponential moving average or EMA. This is a type of moving average that gives more importance or weight to recent data values as a means to keep the moving average more updated to recent changes. Its calculation may be more complex than what is used for the simple moving average. EMA’s become more sensitive to recent price changes and may be more responsive to new information as they come.