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, using TA indicators serves one simple goal: use 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 can achieve the popularity and consistency of the Moving Average (MA).

Although there are many different varieties of moving averages, their fundamental goal is to create an easily identifiable trend indicator by flattening the graph, thereby increasing the clarity of the trading chart. Because these moving averages rely on past data, they are considered lagging or trend following indicators. Still, these moving average indicators can effectively cut through the noise and help determine market direction.

Different types of moving averages

Various types of moving averages Not only suitable for day trading and swing trading, but can also be used in long-term setups. Although there are many types, MAs are usually divided into two broad categories: simple moving averages (SMA) and exponential moving averages (EMA). Depending on market conditions and expected results, traders can choose which indicator is most likely to benefit their setup.

Simple Moving Average

SMA obtains data from the set time period, This yields the average price of its assets. The difference between an SMA and a basic price average is that with an SMA, once a new data set is entered, the previous data set is ignored. So if you calculate a simple moving average 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 data is entered into the system, it is considered equally weighted in SMA. Traders who believe that newer data is more relevant (to market conditions) often say that the equal weighting of SMAs is detrimental to technical analysis. Therefore, the exponential moving average (EMA) was created to solve this problem.

Exponential Moving Average

EMA is similar to SMA in that they are based on past Technical analysis is provided on price movements. However, the equation is more complex because the EMA assigns more weight and value to recent price inputs. While both averages have value and are widely used, the EMA is more responsive to sudden price swings and reversals.

Because EMAs are more likely to predict price reversals faster than SMAs, they are often particularly popular among 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 to adjust the settings accordingly.

How to use moving averages

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

Depending on different trading strategy settings, both may be beneficial. Larger data sets benefit 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 favor more contingent trading.

In the traditional market, the 50, 100 and 200-day MAs are the most commonly used. Stock traders pay close attention to 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 strategy.

Crossover signal

Intuitively speaking, a rising MA indicates an uptrend, a falling MA The MA indicates a downtrend. However, looking at moving averages alone is not a truly reliable and powerful indicator. Therefore, bullish and bearish crossover signals have always been used with MAs.

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

Other factors that should be considered

The examples so far are based on The unit is days, but this is not necessary when analyzing MA. Someone who day trades may be interested in how an asset's price 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 as long as these time frames are consistent with the trading strategy, the (resulting) data will be useful.

A major disadvantage of MA is its lag time. Since MA is a lagging indicator that takes into account previous price action, the signal usually comes too late. For example, a bullish crossover may signal 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 period between the price increase and the crossover signal. Or worse, a false golden cross signal can cause traders to buy at a relative high before the price drops (these false buying 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 manner and has powerful insights into market performance. But what needs to be remembered is that MA and cross signals should not be used alone, and combining different technical analysis indicators can avoid false signals and will be safer.