# Weighted moving averages: the basics

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Moving averages can help you determine the direction of a current trend while minimising the impact of price volatility. But how much data vày you need to build a reliable picture of the trend? Let’s look here.

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A moving average is the average price of a security over a set period of time. By plotting the average price, sharp fluctuations are removed, & it is easier khổng lồ identify the true trend.

In simple terms, moving averages help technical traders smooth out some of the noise in the market. You can use them lớn identify current trends, trend reversals, & to phối up support and resistance levels.

There are several different ways of looking at moving averages with a variety of calculations. However, the interpretation of each moving average remains the same. The calculations only differ in regards to lớn the weighting that they place on the price data.

In moving averages, you shift from weighting each price point equally, to placing more weight on recent data. The most common types of moving averages are simple, exponential and weighted. Having a thorough understanding of the exact calculation isn’t generally required as most charting software will vì the calculation for you.

Simple Moving Average (SMA)

SMA is the most common method used lớn calculate the moving average of prices. Each point is calculated as the sum of all previous closing prices over the time period, divided by the number of prices used in the calculation.

For example, a 21 day SMA, uses the last 21 closing prices added together & divides it by 21.

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Weighted Moving Average (WMA)

The Weighted Moving Average is used to lớn address the problem of equal weighting. It’s calculated by taking the sum of all the closing prices over a specific time period, multiplying them by the position of the data point, và then dividing by the sum of the number of periods. This is also referred khổng lồ as “linear weighted,” as the decline in weighting is done on a linear basis.

Exponential Moving Average (EMA)

The Exponential Moving Average calculation uses a smoothing factor lớn give a higher weighting to lớn recent data points. The difference with the weighted moving average is that the weighting decreases on an exponential basis (as opposed to lớn a linear basis with the WMA).

The most important factor lớn remember here is that the EMA is more responsive to lớn new information relative lớn the SMA. This responsiveness is one of the key reasons why it is the moving average of choice for many technical traders. It is generally considered much more efficient than the WMA.

Figure 1: Simple, Weighted and Exponential Moving Averages on GBP/USD ## Which Moving Averages Should I Use?

Moving averages are effectively an indicator of trend. Therefore, in the same way, as you can look at trends of different time horizons, you can look at a different number of periods for moving averages.

There is no hard-and-fast rule for which moving averages you should use. On daily charts, some traders like to use round numbers, such as 20, 50, 90 và 200-day moving averages, while others may use Fibonacci numbers, such as 21, 55, 89 & 144-day moving averages.

As a general rule, a 200-day moving average is thought khổng lồ be a good measure of a long term trend, a 90-day moving average of a medium- khổng lồ long-term trend, a 50-day moving average the medium-term trend, and a 20-day moving average of a short term trend.

You should also understand that moving averages work differently at different times and in different markets. Some moving averages may work very well for one instrument but not so well for another. So it is crucial to have a range of moving averages on charts.

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It is a case of horses for courses as there is rarely a one-size-fits-all option. And a moving average that worked well six months ago may not be such a good indicator now.