Explanation of moving averages

Technical analysis (TA) is nothing new in the world of trading and investing. From bonds to cryptocurrencies like Bitcoin and Ethereum, the use of technical analysis indicators has the simple goal of using available data to make better decisions that are more likely to lead to desired results/gains. As markets have become increasingly complex, recent decades have produced hundreds of different types of technical analysis indicators, but only a few have seen the popularity and use of moving averages in analysis.

Although there are different variations of moving averages, their primary purpose is to increase clarity in trading charts. This is done by simplifying the charts to easily create a trend indicator. Since these moving averages are based on previous data, they are considered lagging or trend following indicators. But regardless of that, it still has the ability to increase focus and help determine where the market may be headed.

Different types of moving averages

There are various different types of moving averages that can be used by traders not only in day trading or volatility/swing trading but also in long-term trades. Although there are different types, moving averages are mostly divided into two separate categories:

Simple moving averages (SMA) and Exponential moving averages (EMA). Traders can choose which indicator they are most likely to benefit from based on the market and desired results.

Simple Moving Average (SMA)

A simple moving average takes data from a specific time period and produces an average price for the asset for that data. The difference between a simple moving average and a traditional moving average of past prices is that with a simple moving average as soon as a new data set is entered the oldest data set is discarded. That is, if the SMA calculates the average based on 10 days of data, the entire data set will be updated to include only the last 10 days.

It is important to note that all data inputs into the simple moving average are weighted equally regardless of when they were entered even if they are from recently. Traders who believe there is a correlation with the latest available data often point out that moving average weighting is detrimental to technical analysis. The Exponential Moving Average (EMA) was created to solve this problem.

Exponential Moving Average (EMA)

The Exponential Moving Average (EMA) is similar to the Simple Moving Average (SMA) in that it provides technical analysis based on past price fluctuations. However, the equation is a bit more complicated since the EMA assigns more weight and value to more recent price inputs. Although both averages have value and are widely used, the EMA is more responsive to sudden price fluctuations and reversals/reversals.

Since EMAs are more likely to display price reversals faster than SMAs they are often particularly favored by traders who engage in short-term trading. It is important for the trader or investor to choose the type of moving average according to his or her personal strategies and goals and to adjust the settings accordingly.

How to use moving averages

Moving averages use previous prices rather than current prices and for this reason they have a certain lag time. The wider/expansive the data set, the greater the delay. For example, a moving average that analyzes the past 100 days will respond more slowly to new information than a moving average that analyzes the past 10 days. This is simply because adding data to a large data set has less impact on the overall numbers.

Both can be useful depending on your trading settings.

Large data sets benefit long-term investors because they are less likely to change dramatically when exposed to one or two large fluctuations. But short-term traders often prefer a smaller data set because it allows for more reactionary trading.

In traditional markets, 50-, 100- and 200-day moving averages are normal and most commonly used. The 50- and 200-day moving averages are closely watched by stock traders and any breaks above or below these lines are usually considered important trading signals. , especially when followed by an intersection. The same applies to digital currency trading, but given that the markets are volatile 24/7, the average trading settings and strategies may vary according to the trader’s activity.

Crossover signals

Normally, a high moving average indicates an uptrend and a low indicates a downtrend. But the moving average alone is not a strong and reliable indicator. Therefore, moving averages are used in a group on an ongoing basis to determine bullish and bearish crossover signals.

A crossover signal is generated when two moving averages intersect in a chart (or histogram). A bull cross (also known as a golden cross) occurs when a short-term moving average crosses above a longer-term one, indicating the beginning of an uptrend. Conversely, a bear cross (also called a death cross) occurs when a short-term moving average crosses below another long-term moving average indicating the beginning of a downtrend.

Other important factors

All examples so far have been based on number of days but this is not a necessary requirement when analyzing arithmetic averages. People who engage in day trading may be more interested in how an asset/security has performed over the past two or three hours rather than two or three months. All different time frames can be used in the equations used to calculate moving averages. As long as these time frames are consistent with the trading strategy, the data can be useful.

One downside of arithmetic averages is the time lag (or lag).

Since moving averages are lagging indicators and take into account previous price action, the signals are often too late. For example, a bullish crossover may indicate buying, but this only happens after a significant rise in price. This means that even if the uptrend continues, potential profits may have been lost in the period between the price rise and the crossover signal. Or even worse, a false golden cross signal may lead a trader to buy the top (the highest price) before prices fall (such false signals are commonly referred to as a bull trap).

Moving averages are powerful technical analysis indicators and are considered one of the most widely used indicators. The ability to analyze market trends in a data-driven manner provides insight into market performance. However, it should be kept in mind that moving average signals and crossover signals should not be used alone and that it is always better to combine different technical analysis indicators together to avoid false signals.