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Technical analysis (TA) is nothing new in the world of trading and investing. From traditional portfolios to cryptocurrencies such as Bitcoin and Etherium, the use of TA indicators has the simple goal of using existing data to make more informed decisions that are likely to lead to desired results. As markets have become increasingly complex, hundreds of different types of TA indicators have been produced in recent decades, but not many have earned the popularity that the MA has.
Although there are various variations of moving averages, their main purpose is to bring clarity to trading charts. This is done by smoothing out the charts to create an easily decipherable trend indicator. Because these moving averages are based on past data, and indicators are considered to be lagging or trend following. Despite this, they still have a great ability to overcome interference and help determine market movement.
Different types of moving averages
There are different types of moving averages, which can be used by traders not only for day trading and swing trading, but also for long-term installations. Despite the different types, MAs most often fall into two distinct categories: simple moving averages (SMAs) and exponential moving averages (EMAs).
SMA - Simple Moving Average
The SMA takes data for a specific time period and shows the average price of that asset for the data set. The difference between the SMA and the base average in past prices is that with the SMA, as soon as a new data set is entered, the oldest data set is ignored. Thus, if a simple moving average calculates an average based on 10 days of data, the entire data set is continually updated to include only the last 10 days.
It is important to note that all inputs to the SMA are evaluated the same way, regardless of when they were entered. Traders who believe there is more current available data often claim that equal weighting of the SMA is detrimental to technical analysis. The exponential moving average (EMA) was created to solve this problem.
Exponential Moving Average
EMAs are similar to SMAs in that they provide technical analysis based on past price swings. However, the formula is a bit more complicated because the EMA assigns more weight and value to recent price entries. While both averages have value and are widely used, the EMA responds more clearly to sudden price swings and reversals.
Because the EMA is more likely and faster to predict a price reversal than the SMA, it is accordingly chosen by traders for short-term trading. It is important for the trader or investor to choose the type of moving average according to their personal strategies and goals, adjusting the settings accordingly.
How to use moving averages
Because MAs use past prices instead of current prices, they have a certain lag period. The larger the amount of data, the longer the lag will be. For example, a moving average that analyzes the last 100 days will respond slower to new information than a moving average that only considers the last 10 days. This is simply because a new entry in a large amount of data will have less impact on the total number.
Both can be beneficial depending on trading setups. Large amounts of data benefit long-term investors because they are less likely to be greatly altered by one or two large swings. Short-term traders often prefer smaller volumes of data that account for more reactive trading.
Traditional markets most commonly use 50-day, 100-day and 200-day MAs. Exchange traders keep a close eye on the 50-day and 200-day moving averages, and any breakout above or below these lines is usually considered important trading signals, especially when followed by crossovers. The same applies to trading cryptocurrency, but because of its market volatility 24/7, MA settings and trading strategy can vary depending on the trader's profile.
Crossover Signals
Naturally, an uptrend MA indicates an uptrend and a downtrend MA indicates a downtrend. However, the moving average alone is not a really reliable and strong indicator. Thus, MAs are constantly used in combination to detect bullish and bearish crossover signals.
A crossover signal is created when two different MAs cross on a chart. A bullish crossover (also known as a golden cross) occurs when the short-term moving average crosses the long-term moving average, indicating the beginning of an uptrend. Conversely, a bearish crossover (or death crossover) occurs when the short-term moving average crosses the lower long-term moving average, indicating the beginning of a downtrend.
Other factors to consider
So far, the examples have been given in days, but that is not a requirement when analyzing MAs. Those involved in day trading may be much more interested in how the security has performed in the last two or three hours, rather than two or three months. All time frames can be included in the equations used to calculate moving averages, and if those time frames are consistent with the trading strategy, the data can be useful.
One of the main disadvantages of MAs is their lag time. Because moving averages are delayed indicators which take into account previous price behavior, signals are often late. For example, a bullish crossover may suggest a buy, but it does so only after a significant price rise. This means that even if the uptrend continues, potential profits could have been lost during that period, between the price rise and the crossover signal. Or, even worse, a false gold crossover signal could cause a trader to buy, just before the price falls (these false buy signals are commonly referred to as a bull trap).
To sum it up
Moving averages are good enough TA indicators and for this reason one of the most common. The ability to analyze market trends based on the data, allows you to better understand the market. However, it is important to understand that the MA and crossover signals should not be used separately, always combine the different TA indicators and if possible the FA to avoid false signals.
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Your M.J.
