How to use moving averages, SMA, EMA to trade cryptocurrency

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Moving averages smooth out recent price action to help the trader identify trends, asses trend strength and find support and resistance levels

A moving average is calculated by adding the closing prices from a specified number of trading periods and dividing the sum by the number of trading periods.

Simple Moving Average (SMA) or Exponential Moving Average (EMA) are two popular, but different, moving average indicators. They are often used in conjunction with other mathematical indicators and perform best in a trending market.

When using a moving average in cryptocurrency trading, you can select the length of the average which dictates the amount of periods that will be averaged. Popular periods include 21, 50, 100 and 200. For example, if you have a 21 EMA switched on and you are looking at the 1h chart, the EMA will average the last 21 hours of price movement. 


An EMA is a moving average with a different distribution curve that places more weight on recent trading periods.

As a result, EMAs react faster to sudden changes in price and are especially useful for trading breakouts.

Trend identification using EMA can be more reliable than with SMA as it is more sensitive to recent price changes, although high sensitivity to recent price changes can also result in more false trade signals.


The most common trading signals generated with moving averages when trading cryptocurrency is from watching the interaction between price and the moving average indicator.

A moving average is a trend indicator and can provide support or resistance. When the price crosses above the moving average, it is seen as a break above the trend, generating a buy signal. When the price crosses below the moving average, a sell signal is generated, as the trend is seen as broken to the downside.

Just like with other indicators, the longer the time frame you are using, the stronger the signal. Since moving averages are customisable, the time frame and the length of the moving average dictate the strength of the signal. 

Because of the delayed response to recent price movement, moving averages are known as trend-following indicators. The lagging nature of moving averages and their signals make trading off them relatively conservative, as price moves are largely completed by the time a moving average-based trading signal triggers.

Identify trends with moving averages


A trader may identify an existing trend through a visual inspection of the moving average. A rising moving average reflects a rising trend, while a falling moving average points to a falling trend. A generic trading rule is to buy as the moving average begins sloping up, and to sell as the slope of the moving average turns negative.

In the BTC/USD chart above, the most reliable moving average in anticipating the downturn from the beginning of 2018 was the 20-week EMA (the violet line).

However, even the 20 week EMA was a lagging indicator, as by the time it had begun sloping down, BTC/USD had already fallen significantly. Some longer term bulls may have ignored the 20-week EMA turning down, comforted with the 50-week EMA (the indigo line) and 100-week EMA (the light purple line) still sloping up, suggesting the longer-term uptrend remained intact.

As with other mathematical indicators, when there is less lag, there is a higher probability of false signals. Another challenge with trading based on changes in the slope of moving averages is identifying when that slope definitively changes from being positive to negative or vice versa.

As seen in the weekly chart above, the slope of a moving average may be close to zero for several weeks. During that time frame, the price may have moved significantly.


Another method of confirming a trend is by observing where a shorter (also known as “faster”) moving average is relative to a longer (or “slower”) moving average. A shorter moving average rising above the longer moving average (in the same way that the price going above a moving average) is generally bullish, while a shorter moving average going below the longer moving average is bearish.

As long as the shorter moving average remains above the longer moving average, the uptrend is considered intact. The trend is seen as down when the shorter moving average is below the longer moving average.

As can be seen in the chart above, similarly to monitoring the slope of moving averages, watching for moving average crossovers can generate lagging signals.

By the time the 20-day EMA crossed below the 50-day EMA in the chart above, BTC/USD would have fallen significantly. Waiting for the 50 day EMA to cross below the 150-day EMA would have produced an even more delayed sell signal.

Finding support and resistance

Moving averages can also help identify possible support and resistance levels. A market trading above an upward sloping moving average is considered in an uptrend and tends to find support at its moving average.

Similarly, a market priced below a downward sloping moving average is said to be in a downtrend and it tends to encounter resistance at the moving average.

As seen in the Ripple (XRP/USD) chart above, although support and resistance can often be found around widely followed moving averages, these lines tend to be more reliable indicators of support and resistance when trends have been intact for quite some time.

Exponential Moving Average (EMA)

The EMA’s greater sensitivity to recent price changes makes it better for the trader who wants a moving average to exhibit less lag to recent price movement.

The disadvantage of using the EMA is that because it produces more trading signals, the likelihood of false or premature trading signals increases.

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Sample EMA calculation

Initial SMA: 20-period sum / 20

Multiplier: (2 / (Time periods + 1) ) = (2 / (20 + 1) ) = 0.0952 (9.52%)

EMA: {Close - EMA(previous day)} x multiplier + EMA(previous day).

A 20-period EMA applies a 9.52% weighting to the most recent price. A 20-period EMA can also be called a 9.52% EMA. A 40-period EMA applies a 4.88% weighting to the most recent price (2/(40+1) = .0488). Notice that the weighting for the 20- period is nearly double that of the 40-period EMA.

Day #


5 day SMA

Multiplier 2/(5+1) 

5 Day EMA




























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Darren Chu, CFA

Darren Chu, CFA, is the founder of Tradable Patterns, publisher of daily technical analysis on Bloomberg, Thomson Reuters, Factset, Interactive Brokers, Inside Futures, and other partner websites. Before the launch of Tradable Patterns, Darren served as IntercontinentalExchange | NYSE Liffe's country manager for Australia, India, and the UAE, expanding his role to look after Liffe business development in APAC ex-Japan/Korea until his departure mid April 2014. Previously, Darren was with the TMX Group | Montreal Exchange, marketing Canadian futures and options across North America, London, Singapore and Hong Kong. Darren also launched and managed CMC Markets Canada's Chinese marketing and sales team, along with educational offering. Visit for more information.