6 Types of Moving Averages that Traders Should Know

Traders can rely on a wide range of technical indicators to decipher price movements and make smart trading decisions. Among these many indicators are moving averages (MAs), which range from simple averages to complex, weighted metrics. Different types of moving averages serve different purposes and you can use any of them or a combination of various MAs to chart out your trading plan. 

However, if you are a beginner to trading, you may be unsure of what moving averages are and why they are useful for timing your trade entry and exit. In this article, we delve into the meaning of MAs and discover what the different types of averages are. 

What is a Moving Average?

An average is a statistical measure that best represents a specific set of data. It is the arithmetic mean of a group of data points, which is calculated by summing up those data points and dividing the result by the total number of values considered. 

For example, say you want to compute the average of the numbers from 1 to 10. The average for this data set comes out to be 5.5 (i.e. sum of 1 to 10 divided by 10). 

In a moving average, however, the data set is not fixed. It varies from one iteration to the next, so the average also changes as the data points change — leading to a changing or ‘moving’ average. Moving averages are particularly useful in the stock market, where you can compute the average price of a security over a given period continuously. 

For instance, you can calculate the average 10-day price of a security today. Then, at the end of tomorrow’s trading session, you can again compute this metric by taking tomorrow’s price into account and eliminating the original day 1’s price. This leaves you with 10 price points and an average value that is different from yesterday’s. 

6 Types of Moving Averages for Traders

While the fundamental concept of moving averages may be simple at first glance, technical analysis of stock prices is much more complicated than simple division. This is why we have different types of moving averages, as outlined below. 

1. Simple Moving Average (SMA) 

The simple moving average is a fundamental technical analysis tool that gives you the simple arithmetic mean of price data over a defined period. It calculates the average closing price of a security over a given number of periods, such as 10, 20 or 50 days. The SMA, when plotted on a chart, can help you identify trends by filtering out short-term price fluctuations. 

It is also easy to calculate, so it is widely used by traders and analysts to determine potential entry and exit points in the market. When the price is above the SMA, it may indicate an uptrend (and vice versa). 

2. Exponential Moving Average (EMA) 

The EMA helps tackle the issue of latency in SMA and ensures that the price does not lag too much. This is done by giving more weightage to recent prices than to older prices in the defined period being considered. As a result, it is more responsive to price changes compared to a simple moving average. 

To calculate the EMA, you need to use a smoothing factor on the previous EMA and the prevailing price, thereby giving more weight to recent prices while still including older prices. This provides a clearer picture of the current trend. If the EMA line crosses above the price chart, it indicates a potential buy signal (and vice versa). 

3. Double Exponential Moving Average (DEMA) 

This moving average is a sophisticated version of the EMA. It aims to reduce the lag typically present in other basic moving averages. To achieve this, double smoothing is applied to price data, resulting in a DEMA line that reacts more quickly to price changes. 

What this means is that the DEMA is calculated using two EMAs of the price data — with the first EMA providing a preliminary value that is then smoothed again to generate the final DEMA line. 

4. Triple Exponential Moving Average (TEMA) 

Like the DEMA, the Triple Exponential Moving Average (TEMA) also uses multiple degrees of price smoothing. As an advanced type of moving average, the TEMA seeks to reduce lag and provide more accurate trend signals than even the DEMA. It accomplishes this by applying triple smoothing to the price data. 

Essentially, to find the TEMA, you need to first calculate a single EMA of the price data, then compute a second EMA of the first EMA, and finally, a third EMA of the second EMA. To use this technical indicator, watch for the TEMA line to cross above (or below) the price chart as it may indicate potential buy (or sell) signals. 

5. Weighted Moving Average (WMA) 

The Weighted Moving Average (WMA) is a type of moving average that assigns a higher weight to certain data points, unlike the SMA, which gives equal weight to all data points. The weighting factor increases linearly (and not exponentially like it does in EMA). So, the most recent data point receives the highest weight. 

This makes the WMA more responsive to recent price changes, enabling traders to identify trends more quickly. To calculate the WMA, you need to multiply each data point by its corresponding weight, then add these values and finally divide the result by the sum of the weights.

6. Kaufman’s Adaptive Moving Average (KAMA)

Kaufman's Adaptive Moving Average (KAMA) is a unique type of moving average designed to adapt to market conditions. Unlike traditional moving averages, KAMA adjusts its sensitivity based on market volatility. During volatile periods, KAMA reacts more quickly to price changes, while during quieter periods, it slows down to avoid false signals. 

This adaptive nature helps you capitalise on trends longer and avoid whipsaw trades. KAMA is calculated using efficiency ratios that compare the price change to the asset's volatility, so it remains responsive yet smooth.

Conclusion

With so many moving averages available to analyse and factor in, you may find it overwhelming to compute and compare the required data. Fortunately, most leading trading platforms offer data about essential moving averages, so you can find this information at your fingertips. 

On the Motilal Oswal Research 360 platform, for instance, you can find crucial information about the SMA and EMA values for all listed stocks. The platform does not merely show you these metrics, but also goes a step further and presents data related to moving averages on a scale ranging from bearish to bullish market behaviour. The location of the needle tells you if a stock’s price is currently bullish or bearish, so you can plan your trades accordingly. What’s more, on the Research 360 platform, you can even find MAs for six different periods — namely, 5, 10, 20, 50, 100 and 200 days.