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Spread bets and CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 69% of retail investor accounts lose money when trading spread bets and CFDs with this provider. You should consider whether you understand how spread bets and CFDs work, and whether you can afford to take the high risk of losing your money.

What is exponential moving average (EMA) and how to use it

Exponential moving average is perhaps one of the most common indicators used when it comes to trading. Understand what goes on behind the computation of this moving average to better complement your trading needs.

Trader Source: Bloomberg

What is exponential moving average (EMA)?

The exponential moving average (EMA) is a type of moving average that considers the weighted average of a series of recent data to reflect the ongoing trend in the market. The weight of the EMA is exponentially tilted towards more recent occurrences, giving the recent data greater influence over the reading.

This price-based indicator typically looks at the average closing price of a security over a specified number of periods, such as a 50-day, 100-day or longer 200-day EMAs, smoothing out short-term price fluctuations to provide a clearer image of the market trend.

As with other moving averages, this is a technical analysis tool that uses historical data to predict future price movements of a freely-traded market. Prices are viewed as a reflection of the real-time supply and demand interactions and thus investor sentiment.

The underlying assumption here is that price patterns tend to repeat over time and market technicians believe that humans often are irrational and emotional and thus tend to behave similarly in similar circumstances. EMA may be used by itself, but oftentimes in conjunction with other technical analysis tools or fundamental analysis for trading as well.

How to calculate exponential moving average

The computation of a security’s EMA is broadly straightforward. The exponential m-day moving average EMA with smoothing parameter k is defined as the below.

Exponential m-day moving average EMA with smoothing parameter k

The smoothing parameter k takes on a value of between 0 and 1, typically chosen as 2/(m+1). An example is shown below for the computation of EMA where m = 5 and therefore k = 1/3.

Price EMA (m=5)
Day one 102.4 102.4
Day two 103.6 102.8
Day three 103.5 103.0
Day four 101.2 102.4
Day five 100.0 101.6

Exponential moving average vs simple moving averages

As explained above, EMA as with simple moving averages (SMAs) are popular technical analysis tools. They are also very similar in measurement of trends. SMAs can be quite simply computed using the formula below for an m-day SMA.

Formula for computing SMAs

The difference, however, is that EMAs accord greater weightage to more recent information and will therefore be more sensitive towards the latest price changes than SMA. While this may matter very little for short-term trading, the difference becomes more apparent in the study of longer-term price trends. Recent data may be regarded as more telling of the latest market sentiment. This had also been why EMA presents itself as a popular choice of moving average between the two. In practice, both EMA and SMAs are commonly used by technical analysts and traders.

How to use exponential moving average in your trading

Both exponential and simple moving averages, while different in their computation of value, may be used in similar manners. A straightforward way to utilise moving averages in one’s trade is to use two moving averages of different time frames in conjunction.

A short-term moving average (stMA) is used to reflect the current impetus of the market while a longer-term moving average (ltMA) shows the broader trend of the market. When a stMA crosses over from underneath a ltMA, this serves as a bullish signal in the market and is commonly known as a golden cross. Conversely, the crossing over of an stMA from above a ltMA is considered bearish and is recognised as a death cross.

Using Apple, a popular US Fang index as an example, one can see that the crossover of the short-term 20-day MA above the longer-term 60-day MA as a bullish sign. Depending on one’s time frame of trade, the MAs of choice can also be adjusted correspondingly.

Apple chart Source: IG charts
Apple chart Source: IG charts

Exponential moving average limitations

Once again, the key trait of the EMA may also be its limitation. Given the greater influence that recent data has on the EMA, recency bias is present here. With the stock market, this can be dangerous when prices are at extremes. The EMA may fuel further buying interest in the market during a time when prices are already in extreme overbought condition, overdue for a pullback. It is important that one exercise their discretion when using any tools in their trading. Back testing would be one way to improve the validity of one’s trading strategy using tools such as the EMA. Using the EMA in conjunction with other analytical tools may also a way to improve one’s conviction in their trade.


This information has been prepared by IG, a trading name of IG Markets Limited. In addition to the disclaimer below, the material on this page does not contain a record of our trading prices, or an offer of, or solicitation for, a transaction in any financial instrument. IG accepts no responsibility for any use that may be made of these comments and for any consequences that result. No representation or warranty is given as to the accuracy or completeness of this information. Consequently any person acting on it does so entirely at their own risk. Any research provided does not have regard to the specific investment objectives, financial situation and needs of any specific person who may receive it. It has not been prepared in accordance with legal requirements designed to promote the independence of investment research and as such is considered to be a marketing communication. Although we are not specifically constrained from dealing ahead of our recommendations we do not seek to take advantage of them before they are provided to our clients. See full non-independent research disclaimer and quarterly summary.

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