Using Moving Averages for Technical Analysis

Using Moving Averages for Technical Analysis

Technical and fundamental analysis are the two most commonly used methods of identifying entry and exit positions. Technical analysis uses past performance to give an indication of how the market will perform in future. On the other hand, fundamental analysis combines the past news and economic events with the present and future expectations. In the two, many models have been developed to help investors simplify their trading. Moving Averages (MA) are some of the most common technical indicators today.

Moving averages look at the past opening, closing, high, and low prices of an instrument such as a currency pair and then conducts an analysis into its average price in a particular time. The change in the instrument’s price will lead to a change in the moving average.

There are 5 main types of moving averages which include: simple moving average (SMA), exponential moving average (EMA), smoothed moving average, weighted moving average (WMA), and the triangular moving average (TMA). In addition, a moving average of a moving average can also be used.

While these moving averages are relatively similar, the key difference between them is the weight assigned to the most recent price data. SMA applies an even weight to all the prices while the exponential and weighted moving averages place more weight to the most recent data. On the other hand, the Triangular Moving Averages (TMA) apply more emphasis to the data in the middle of the data set. Finally, the variable moving average (VMA), presses more weight on the volatility of the price.

In the past, traders had to spend time calculating the moving averages. This was a tedious activity since moving averages are better used alongside other technical indicators. Today, this has changed with the introduction of automated trading systems which incorporate moving averages. The chart below shows a 15 minute EURUSD chart (red) analysed by exponential moving averages (blue), and the weighted moving averages (brown).


Time aspect in moving averages

The success or failure of using moving averages depend on a number of factors. For instance, since moving averages use past data to make judgement, it is impossible for it to forecast economic numbers. Therefore, when economic data is released, the chart will move either up or down despite what the moving average shows.

Another important aspect in moving averages is time. Traders who place intraday trades prefer to use short term moving averages while those who have a long time horizon prefer using the long term moving averages. The table below shows the main moving averages time frames.


Very short term (for intraday traders) 5-13 days
Short term 14-25
Minor intermediate 26-49
Intermediate 50-100
Long term 100-200


The chart below shows a 9, 15, and 50 day simple moving average for the EURUSD pair shown above.