How to Use Moving Average for Crypto Trading

There are specific tools used to analyse market trends and charts to make predictions on the best time to enter and exit a market. These tools offer a guide to take calculated risks to minimise losses and maximise profits. Technical Analysis (TA) involves using indicators and oscillators, among other tools, to understand and explain the crypto market. Among such tools is the moving average, one of the most popular and most frequently used tools in the technical analysis of a market.

Moving average is a valuable tool that enables you to track the market's direction by observing trends and price movements (data) over a specific period of time. It focuses on calculating an asset's average price over a particular time frame as it moves along the chart. Moving averages are calculated just like any average: you add the price data over a period of time and calculate the mean.

For example, if a cryptocurrency price is currently below a moving average, then the trader notes that the trend has turned bearish; that is, the price and sentiment are moving downward. Similarly, prices above a moving average could signify that the price has gone bullish, meaning that the price is moving up. However, for the best result of the moving average, you should use the Moving Average with other indicators such as the Relative Strength Index (RSI) and Stochastic Oscillator.

The moving average can be used by short-term traders and even long-term traders. However, there are different types of moving averages that traders may use depending on the market and their trading goals. The types of moving average include:

Simple Moving Average (SMA)

Simple moving averages (SMA) take the price of an asset over a particular time to calculate an average. SMA is almost like any average; the only difference is that once there is new price data, the previous average is dismissed. In this regard, if a trader calculates the mean on 50 days’ worth of data, then subsequently, that data set would be moderated to only include data for the last 50 days.

SMAs are weighted equally regardless of the time frame in which they were inputted. However, some traders are of the opinion that the equal weighting of SMA might not attain the best result in technical analysis, which is why the exponential moving average (EMA) was developed to address this problem.

Exponential Moving Average (EMA)

The exponential moving average is designed similarly to the SMA as they both use price fluctuations in their analysis. However, for SMA, all price inputs are weighted equally, while EMA adds more value and weight to recent price inputs. Traders can use either of these moving averages; however, EMA is more effective in analyzing sudden price fluctuations or reversals.

Read also: What are technical indicators in trading?

When using moving averages, you may experience a lag because MAs focus on past prices, not present ones. This means that the larger a data set, the larger the lag. To this effect, a moving average of 50 days would experience a smaller lag than a moving average of 100 days. This is because new entries would have a minimal effect on the overall numbers in a large dataset.

Traders can use any moving average depending on their preference; however, long-term investors are more inclined towards using a larger data set. This is primarily because they aren’t easily moved by fluctuations. However, short-term traders may lean towards smaller data sets because price fluctuations are more clearly defined. The most commonly used MAs include 50, 100, and 200 days. The 50-day and 200-day MA is used often by stock traders and crypto traders as any significant break above the moving lines of a MA indicates a significant trading signal, especially when followed by a crossover. However, due to cryptocurrency volatility, the application and use may vary according to the trader’s preference.

The examples so far have all been in terms of days, but that's not a necessary requirement when analysing MAs. Those engaged in day trading may be much more interested in how an asset has performed over the past two or three hours, not two or three months. Different time frames can all be plugged into the equations used to calculate moving averages. As long as those time frames are consistent with the trading strategy, the data can be helpful.  Lags are the major downsides of Moving Averages; that is, the trader may receive signals a little too late because the MAs are focused on previous price action.

Often, MAs are used to denote an upward and downward trend; that is, for example, a rising MA indicates an upward trend. A moving average crossover is created when two or more different MAs crossover in a chart, signifying a significant change in the market trend. This may occur in situations where there are large shifts in price, thus pushing the lines to go upward and downward on the chart, causing them to cross paths.

Two types of crossovers may occur in a chart;

Golden cross

The golden cross may also be referred to as bullish crossover. A golden cross occurs when a shorter MA crosses above a longer MA. It signifies the start of an upward trend.

Death cross

The death cross, also known as a bearish crossover, is the direct opposite of a golden cross. It occurs where a shorter MA crosses below a longer MA. It signifies the start of a downward trend.

Crossover signals also experience a lag which may result in potential profit being lost. Some traders may also experience a loss when a fake golden cross signal happens. This is because a trader may buy crypto with the assumption that an upward trend is at its start and experience a price drop. Fake buy signals, that is, a fake golden cross, may also be referred to as a bull trap.

Moving averages are great indicators that can be used in your technical analysis and can help you to navigate the market based on data. However, MAs have a downside - lags. However, you should use them in conjunction with other technical analysis indicators and oscillators for the best result.