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Guide To Understanding Moving Averages In Technical Analysis

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Investors usually rely on fundamental analysis to assess security and its intrinsic value (and to analyze its future potential), while traders use technical analysis to maximize direct returns. Technical analysis studies chart patterns and indicators to detect trading opportunities and potentials earnings. The most common tools of this discipline include Moving averages, MACD, Relative strength index, Bollinger bands, and others.

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As far as useful technical analysis trading tools are concerned, one of the oldest and most popular is the moving average. It is an indicator that analyzes past and recent data (price in particular) by summing and averaging over different periods of time. It shows the mean values, and it is called “moving” as it is repeatedly recalculated as new data becomes available. As it progresses, it drops the oldest value and adds the latest value. This describes a process, called “smoothing” with which it reduces the effect of temporary data fluctuations, flattening it to a line, shows the trend more clearly and highlights values above and below.

Moving averages are trend following or lagging indicators, as they describe events which have already occurred. They are also used as a base for other indicators such as Moving Average Convergence Divergence (MACD), Bollinger Bands, Percentage Price Oscillator, and others. The usage of moving averages encompasses confirming a trend, determining its direction or its possible reversals, as well as identifying a flat market.

The primary parameter used to calculate a moving average is a period or a number of periods. Predominantly, Moving Averages are based on closing prices.

Types Of Moving Averages

A Simple Moving average is the most basic and probably most widely used form of Moving Averages. It is defined as the unweighted mean ( sum of values, divided by the number of values) of data over a fixed amount of time periods. When a new value enters the set in a new period, the oldest one drops out, and so a new calculation is required.

Exponential Moving Average

It uses a more complicated calculation than the simple moving average as it applies more weight to the latest data in the set of values and it computes the average out of all the historical analyzed data, without removing earlier entries when the most recent one becomes available. The weighting for each previous value decreases exponentially (the step is not a constant number).

Weighted Moving Average

It is an indicator which again highlights more recent price entries to ensure they have a more significant impact on the result than older entries. Each entry’s weight decreases in an arithmetical progression, which means the difference between the data points is fixed and 1 is the most commonly used number.

Tips For Interpreting Moving Averages

–    Consider the length of the periods you use. You should have a certain number of closing prices to calculate a moving average. This might be an issue for brand new assets.

–    Moving averages are lagging, trend following indicators, which means they are always a step behind. Whereas they ensure you are in line with the current trend, but there is still a risk of delayed signals. The longer the moving average, the larger the lag.

–    Moving averages can not only be calculated with closing prices but also with monthly prices, weekly prices, opening prices or even intraday prices.

–    Have in mind that the higher the price volatility, the bigger the chance of false signals. While moving averages are great for identifying major trends, it is possible to get several false signals or losing positions before that happens. Moving averages are essential for other tools, always combine tools for additional confirmation.

 

Want to learn more strategies in technical analysis? You can read our guide to trading pullbacks using RSI here.

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