An Intro to Moving Averages: Popular Technical Indicators
Over the last few articles, we have covered many of the basics of technical analysis, mainly chart types and pattern recognition. Having laid the foundation, it is time to move on to a more involved discussion and delve into the core of technical analysis—indicators—and how they are used in the analysis process and in the development of systematic trading strategies. To get things started, we will begin with one of the more basic, yet quite popular, indicators—moving averages.
In this article
- Moving averages
- price cycles
- price inputs
- simple moving average
- weighted averages
- Exponential averages
- Percentage = 2 ÷ (Time Period + 1)
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Moving averages are among the oldest and most widely used technical analysis tools. Due to the relative ease with which they are calculated, moving averages are the preferred tools of newcomers to technical analysis. They have also found favor among some fundamental analysts who make decisions on fundamental factors such as earnings and sales but use moving averages to time buy and sell decisions. With the wide availability of computers and their increased use in financial analysis, you can now create moving averages covering several decades worth of data in a matter of seconds.
A moving average is defined as the average price of a security over a set time period. In essence, moving averages are “bending trendlines.” Remember that a trendline is typically drawn between two or more peaksor troughs in the price movement of a security. Over time, both trendlines and moving averages can be used to establish points of resistance or support for the price. However, moving averages overcome some of the criticisms of trendlines—mainly that they are subjective in their construction. While moving averages can be customized to meet individual needs, they are still based on cold, hard mathematical calculations. In addition, whereas straight-line trendlines are static in nature, moving averages portray dynamic levels of support or resistance as prices move.
Moving averages, by their very nature, smooth data. In other words, they tend to eliminate—or at least lesson the impact of—“blips” or outliers in price data. Moving averages show trends in price, but their nature is to represent the trend in a smoothed fashion.
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