Moving averages explained
Technical analysis (TA) is nothing new in the world of trading and investing. From traditional investment portfolios to cryptocurrencies like Bitcoin and Ethereum, the use of TA indicators serves a simple purpose: to use existing data to make decisions that are likely to lead to desired results. As markets have become increasingly complex, the past decades have seen the creation of hundreds of different types of TA indicators, but the moving average (MA) is the most commonly used.
Although there are different variations of moving averages, their basic purpose is to make trading charts clear. This is done by smoothing the graphs to create a trend indicator that can be easily interpreted. Because moving averages are based on past data, they are considered lagging indicators - in other words, they only show changes that have already occurred. Even so, it still has a significant effect and helps determine market trends.
Types of moving averages
There are different types of moving averages that can be used by traders not only in day trading and swing trading but also in long-term setups. Although there are different types, MAs are often divided into two distinct types: Simple moving averages (SMA) and exponential moving averages (EMA). Depending on the market and desired outcome, traders can choose which index is most likely to favor their setup.
Simple moving average
SMA takes data from a period of time and calculates the average price of the security from the data set taken. The difference between SMA and a basic average of past prices is that with SMA, as soon as a new data set is entered, the oldest data set is ignored. So, if a simple moving average calculates the average based on 10 days of data, the entire data set will be continuously updated to include only the past 10 days.
It is important to note that all data inputs in an SMA are assigned equal weighting, regardless of the time they were entered. For traders, who believe that using the latest data better represents relevant information, it is often considered that the equal weighting of the SMA is detrimental to technical analysis. That's why the exponential moving average (EMA) was created.
Exponential moving average
Similar to the SMA, the EMA provides technical analysis based on past price movements. However, it has a slightly more complicated equation because the EMA assigns more weight and value to the most recent price inputs. While both moving averages are valuable and widely used, the EMA reacts more quickly to unusual price movements and reversals.
Since the EMA is capable of predicting price reversals faster than the SMA, it is often used by traders making short-term trades. It is important for traders or investors to choose the type of moving average according to their strategy and personal goals to adjust the settings accordingly.
How to use moving averages
Because MA uses historical price data instead of current prices, it has a certain time lag. The larger the data set, the greater the latency. For example, a moving average that analyzes the past 100 days will react more slowly to new information than an MA that only looks at the past 10 days. This is understandable because entering new data into a much larger data set will not change the total much.
Both come in handy depending on the trading setup. MAs based on large data sets are beneficial to long-term investors because they are less likely to change much due to one or two big swings. On the contrary, short-term traders often prefer using smaller data sets because it will help them be more sensitive to fluctuations.
In traditional markets, MA with 50, 100 and 200 day data sets are most commonly used. The 50-day and 200-day moving averages are closely watched by stock traders, and any breaks above or below these lines are often considered important trading signals, especially when they are followed. followed by intersection points. The same applies to cryptocurrency trading but due to 24/7 market volatility, MA settings and trading strategies may vary from trader to trader.
Crossover point signal
Obviously, an increasing MA indicates an uptrend and a decreasing MA indicates a downtrend. However, moving averages alone are not a truly reliable and robust indicator. Therefore, MA is used in combination with crossover signals in bullish and bearish trends.
A crossover signal is created when two different MAs cross each other on the chart. A bullish crossover (also known as a golden cross) occurs when the short-term MA crosses above the long-term line, indicating the start of an uptrend. Conversely, a bearish crossover (or death cross) occurs when the short-term MA crosses below the long-term one, indicating the start of a downtrend.
Other factors to consider
The above examples are all about daily data, but that is not a necessary requirement when analyzing MA. Day traders may be more interested in a stock's movements over the past two or three hours, not two or three months. Different time frames can be included in the equations used to calculate moving averages. As long as the timeframes included match the trading strategy, the data can be useful.
One main disadvantage of MA is the lag time. Since MA is a trailing indicator that considers previous price movements, the signals are often delayed. For example, a bullish crossover may suggest buying, but this only occurs after a significant price increase. This means that even if the uptrend continues, potential profits may have been lost between the price increase and the crossover signal. Or even worse, a false golden cross signal could cause the trader to buy the peak just before the decline (these false buy signals are often called bull traps).
Moving averages are powerful TA indicators and one of the most widely used. The ability to analyze data-driven market trends gives insight into how the market is performing. However, please note that MA and crossover signals should not be used alone but should be combined with different TA indicators to avoid false signals.
