Explanation of Moving Averages

 

Technical analysis (TA) is not a new concept in the world of trading and investing. From traditional portfolios to cryptocurrencies such as Bitcoin and Ether, TA indicators are used with one simple goal in mind: to utilize the available data to make smarter decisions and get better results. As markets have become more complex, hundreds of different types of TA indicators have emerged over the past few decades, few of which have achieved the popularity and consistency of moving averages (MAs).

While there are many different types of moving averages, their fundamental goal is to improve the clarity of trading charts by smoothing out the graphics to create an easily recognizable trend indicator. Because these moving averages rely on past data, they are recognized as lagging or trend following indicators. Nonetheless, these moving average indicators can still be effective in removing noise and help determine the direction of the market.

Different types of moving averages

The various types of moving averages are not only suitable for use in day trading and swing trading, but can also be used in long-term setups. Despite the many types, MAs are usually categorized into two main groups: simple moving averages (SMAs) and exponential moving averages (EMAs). Depending on market conditions and expected results, traders can choose which indicator is most likely to favor their setup.

simple moving average (in financial analysis)

SMAs take data from a set period of time to derive an average price for their assets.The difference between an SMA and a basic average price is that with an SMA, once a new dataset is entered, the previous dataset is ignored. Therefore, if a simple moving average is calculated based on 10 days of data, the entire dataset is constantly updated and includes only the most recent 10 days.

It is important to note that data is considered equally weighted in the SMA regardless of when it was entered into the system. Traders who believe that the newer the data, the more relevant (to market conditions) it is often stated that the equal weighting of the SMA is detrimental to technical analysis. As a result, the Exponential Moving Average (EMA) was created to address this issue.

exponential moving average (EMA)

EMAs are similar to SMAs in that they provide technical analysis based on past price movements. However, this equation is more complex because EMAs assign more weight and value to recent price inputs. While both averages are valuable and widely used, EMAs are more sensitive to sudden price fluctuations and reversal reactions.

Because EMAs are more likely to predict price reversals faster than SMAs, they are often especially favored by short-term traders. It is extremely important for a trader or investor to choose the type of moving average according to his personal strategy and goals, adjusting the settings accordingly.

How to use moving averages

Since MAs use past prices rather than current prices, they have a certain lag. （The larger the interval of the data set (used), the larger the lag period. For example, analyzing new information about a moving average for the past 100 days is slower to respond than considering only MAs for the past 10 days. This is simply because new data has less of an impact on larger data sets than smaller ones.

Depending on the trading strategy setup, both may be favorable. Larger data sets favor long-term investors because they are less likely to change due to one or two large swings. Short-term traders typically favor smaller data sets that favor more contingent trading.

In traditional markets, 50, 100 and 200 day MAs are the most commonly used. Stock traders pay close attention to the 50- and 200-day MAs, and any breakouts above or below these lines are usually considered important trading signals, especially when they occur after a crossover. The same applies to cryptocurrency trading, but due to its 24/7 volatile market, MA setups and trading strategies may vary depending on the trader’s senior strategy.

crossover signal

Intuitively, a rising MA indicates an uptrend and a falling MA indicates a downtrend. However, moving averages alone are not really a reliable and powerful indicator. Therefore, bullish and bearish crossover signals have been used alongside MAs.

A crossover signal is created when two different MAs cross in a chart. A bullish crossover (also known as a golden cross) occurs when the short-term MA exceeds the long-term MA, indicating the beginning of an uptrend. Conversely, a bearish crossover (or death cross) occurs when the short-term MA falls below the long-term moving average, which indicates the beginning of a downtrend.

Other factors to be considered

The examples so far are all in days, but this is not necessary when analyzing MAs. Those engaged in day trading may be interested in asset price changes over the last two or three hours, rather than two or three months. Different time units can be used in the equations used to calculate moving averages, and as long as these time frames are consistent with the trading strategy, the (resulting) data can be useful.

One of the main drawbacks of MA is its lag time. Since the MA is a lagging indicator that takes into account previous price behavior, signals that (appear) are usually too late. For example, a bullish crossover may suggest buying, but it only occurs after the price has risen sharply. This means that even if the uptrend continues, potential profits may be lost in the period between the price rise and the crossover signal. Or worse, a false golden cross signal could lead traders to buy at a relatively high point before the price falls (these false buy signals are often referred to as long traps).

The moving average is a powerful TA indicator and one of the most widely used. It takes a data-driven approach to analyzing market movements and possesses powerful insights into market performance. However, it is important to remember that MA and crossover signals should not be used in isolation and that a combination of different technical analysis indicators can avoid false signals and will be safer.

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