Technical analysis (TA) is not a new concept in the world of trading and investing. From traditional investment portfolios to cryptocurrencies like Bitcoin and Ethereum, the use of TA metrics is all about one simple goal: use existing data to make better-informed decisions and achieve better outcomes. 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).

Although there are many different kinds of moving averages, their fundamental purpose is to create an easily recognizable trend indicator by flattening the pattern, thereby increasing the clarity of the trading chart. Since these moving averages rely on past data, they are considered lagging or trend-following indicators. Nonetheless, these moving average indicators are still effective at removing noise and helping to gauge market direction.

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Different Kinds of Moving Averages

A wide variety of moving averages is used not only in day trading and swing trading but also in long-term setups. Although there are many types, MAs are generally divided into two broad categories: Simple Moving Averages (SMAs) and Exponential Moving Averages (EMAs). Depending on market conditions and expected outcomes, traders can choose which indicator is most likely to benefit their setup.

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Simple moving average

SMA takes data from a set time period, resulting in the average price of its asset. The difference between SMA and the basic average price is that with 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 continuously updated and only the most recent 10 days are included.

It is important to note that whenever data is entered into the system, it is considered equally weighted in SMA. Traders who feel that the data is more recent and more relevant (in relation to market conditions) often say that equal weighting of SMAs is detrimental to technical analysis. Therefore, Exponential Moving Average (EMA) was created to solve this problem.

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Exponential Moving Average

EMAs are similar to SMAs in that they provide technical analysis based on past price movements. However, the equation is more complicated because the EMA assigns more weight and value to the most recent price input. Although both averages are valuable and widely used, EMAs are more sensitive to sudden price swings and reversals.

Since 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, and to adjust the settings accordingly.

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How to use moving averages

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

Depending on the trading strategy setup, both can be beneficial. Larger datasets are good for long-term investors, as they are less likely to change with one or two big swings. Short-term traders generally prefer smaller datasets that favor more responsive trades.

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

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Cross signal

Intuitively, a rising MA indicates an uptrend and a falling MA indicates a downtrend. However, looking at moving averages alone is not a really reliable and strong indicator. Therefore, bullish and bearish crossover signals are always used with MA.

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

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Other factors that should be considered

The examples so far have been in days, but this is not required when analyzing MAs. A person who is a day trader may be interested in how the price of an asset has changed over the past two or three hours rather than two or three months. Different time units can be used in the equation for calculating moving averages, and (results) data can be useful as long as these time frames are consistent with the trading strategy.

A major disadvantage of MA is its lag time. Since the MA is a lagging indicator that takes into account previous price action, the signal is usually too late. For example, a bullish crossover may suggest buying, but it only happens after a significant price increase. 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 can cause traders to buy at the relative highs ahead of price declines (these fake buy signals are often referred to as bull traps).

Moving averages are a powerful TA indicator and one of the most widely used. It analyzes market trends in a data-driven manner and possesses powerful insights into market performance. But it should be remembered that MA and crossover signals should not be used alone, and it is safer to combine different technical analysis indicators to avoid false signals.

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