Technical analysis (TA) is not a new concept in the world of trading and investing. From traditional portfolios to cryptocurrencies such as Bitcoin and Ethereum, the use of TA indicators is for a simple goal: to make smarter decisions with existing data and get better results. As the market has become more complex, hundreds of different types of TA indicators have emerged in the past few decades, and few of them can achieve the popularity and consistency of the moving average (MA).

Although there are many different kinds of moving averages, their fundamental goal is to improve the clarity of your trading charts by smoothing out the pattern to create an easily recognizable trend indicator. Because these moving averages rely on past data, they are considered lagging or trend-following indicators. Despite this, these moving average indicators can still effectively eliminate noise and help determine market direction.

Different Types of Moving Averages

There are a variety of moving averages that are useful not only in day trading and swing trading, but can also be used in long-term setups. Despite the numerous types, MAs are generally divided into two categories: simple moving average (SMA) and exponential moving average (EMA). Depending on market conditions and expected results, traders can choose which indicator is most likely to benefit their setup.

Simple Moving Average

The SMA takes data from a set period of time to come up with the average price of its asset. The difference between an SMA and a basic average price is that with an SMA, once a new data set is entered, the previous data set is ignored. So, if a simple moving average is calculated based on 10 days of data, the entire data set is constantly updated and only includes the most recent 10 days.

It is important to note that no matter when the data was entered into the system, it is considered equally weighted in the SMA. Traders who believe that the more recent the data, the more relevant it is often say that the equal weighting of the SMA is detrimental to technical analysis. Therefore, 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 fluctuations. However, the equation is more complex because EMAs assign more weight and value to recent price inputs. While both averages have value and are widely used, EMAs are more responsive to sudden price swings and reversals.

Since EMAs are more likely to predict price reversals sooner than SMAs, they are often particularly favored by short-term traders. It is extremely important for a trader or investor to choose the type of moving average based on his personal strategy and goals, and adjust the settings accordingly.

How to Use Moving Averages

Because MAs use past prices instead of current prices, they have a certain lag. The larger the data set, the greater the lag. For example, a moving average that analyzes the past 100 days will respond slower to new information than an MA that only considers the past 10 days. This is simply because new data has less impact on a larger data set than a smaller one.

Depending on the trading strategy setup, both can be advantageous. Larger data sets are advantageous to long-term investors because they are less likely to change based on one or two large moves. Short-term traders generally prefer smaller data sets that are advantageous for more reactive trading.

In traditional markets, the 50, 100, and 200-day MAs are the most commonly used. Stock traders closely watch the 50-day and 200-day MAs, and any breakouts above or below these lines are often 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 settings and trading strategies may vary depending on the trader's veteran strategy.

Cross signal

Intuitively, a rising MA indicates an uptrend and a falling MA indicates a downtrend. However, looking at the moving average alone is not a truly reliable and strong indicator. Therefore, bullish and bearish crossover signals have been used along with the MA.

A crossover signal is created when two different MAs cross over in a chart. A bullish crossover (also called a golden crossover) occurs when the short-term MA crosses above the long-term MA, signaling the start of an uptrend. Conversely, a bearish crossover (or death crossover) occurs when the short-term MA crosses below the long-term moving average, signaling the start of a downtrend.

Other factors to consider

The examples so far have been based on days, but this is not necessary when analyzing MAs. Someone who is engaged in day trading may be interested in the price changes of an asset in the past two or three hours, rather than two or three months. Different time units can be used in the equation to calculate the moving average, and as long as these time frames are consistent with the trading strategy, the (resulting) data will be useful.

One major drawback of MAs is their lag time. Since MAs are lagging indicators that take into account previous price action, the signals are often too late. For example, a bullish crossover may suggest buying, but it only occurs after a significant price increase. This means that even if the uptrend continues, potential profits may be lost in the time between the price increase and the crossover signal. Or worse, a false golden crossover signal may cause traders to buy at a relative high before prices fall (these false buy signals are often called bull traps).

Moving average is a powerful TA indicator and one of the most widely used indicators. It analyzes market trends in a data-driven way and has a strong insight into market performance. But it should be remembered that MA and crossover signals should not be used alone, and combining different technical analysis indicators can avoid false signals and be safer.