What is a Moving Average?
A Moving Average is a price-based lagging indicator that shows the average price of a security over a certain period of time. Moving averages are an effective way to measure momentum, confirm trends, and define support and resistance levels.
Moving averages essentially smooth out the “noise” that comes from price and volume fluctuations. Since moving averages are lagging indicators, reacting to events that have already occurred, they can only be used to predict future price movements to a limited extent.
Moving averages form the basis for several well-known technical indicators. These include not only the Bollinger Bands, but also the MACD indicator. There are various types of moving averages, all of which are based on the same principle and differ only in details. The most important ones are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA), which will be described in more detail below.
What is the Simple Moving Average (SMA)?
The Simple Moving Average (SMA) is a pre-set number of periods and a selected stock that calculates average values. The period length determines how many previous values are included in the calculation. For this purpose, the respective values are added up and divided by the number (period length). This results in a new value for each day, which is then visually connected.
The period length is typically named with the indicator, so for example, we can talk about the SMA 200. Thus, the last 200 closing prices are included in the calculation for the SMA 200. For the SMA 50, it would be the last 50 closing prices, and so on.
At the same time, the SMA 200 is the most commonly used simple moving average. Since many institutional traders use it as a trend line, it has a certain relevance in the market. Therefore, the SMA 200 often serves as a support or resistance line. At the same time, trading signals can be derived from the interaction between the price and the SMA. For example, a crossing of the SMA from bottom to top is often considered an indication of a rising price, and a crossing from top to bottom is accordingly interpreted as a sell signal.
What is the Exponential Moving Average (EMA)?
The Exponential Moving Average (EMA) calculates a moving average based on the preset period length, just like the SMA. However, unlike the SMA, not all closing prices of the period length are weighted equally in the EMA. Instead, more recent closing prices are given a higher weight than older ones. As a result, the EMA reacts more sensitively and quickly to price changes than the SMA. Due to this property, the EMA runs closer to the actual price, as the current values have a higher value.
Just like the SMA, the period length of the indicator can be customized. The EMA 12 or EMA 26 are often used, which then have a period length of 12 or 26, respectively.
There are several ways to integrate the EMA into your trading. On the one hand, like with the SMA, the EMA can be interpreted as a support and resistance line. On the other hand, the crossing of two or more EMA can be used as a trading signal. For example, an EMA 50 and an EMA 200 are used for this purpose. The crossing of the longer-term EMA 200 with the shorter-term EMA 50 can be interpreted as an indication of a trend reversal.
What is better: SMA or EMA?
Moving averages are among the most popular indicators in the trading world. The most well-known of these are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA). They differ primarily in the weighting of the closing prices included in the calculation.
Therefore, the question naturally arises as to which of the two is better and which should be used in trading. The SMA is easier to calculate, but all closing prices are weighted equally, which is not the case with the EMA. Therefore, the EMA runs closer to the actual price and reacts faster to price changes, generating trading signals earlier.
However, indicators should never be used as the sole criterion for trading decisions. This, of course, also applies to these two moving averages. Indicators should therefore adapt to your tested strategy and support it to increase the probability of entry, and should never serve as the sole signal for decisions.