Moving Averages – Technical Analysis
It is one of the most straightforward and widely used technical analysis tools available – but how much do you know about moving averages? Discover what you need to know as we walk you through the essentials, including what they are and how to use them.
We’ll take a closer look at moving averages in this handy guide, examining the various types of these tools that are easily accessible to traders of all experience levels, from beginners to advanced investors. Continue reading to learn more.
What Are Moving Averages?
Moving averages are a type of indicator that are frequently used in technical analysis to calculate and identify a stock’s trend direction, as well as its support and resistance levels.
They essentially represent the average price of an asset over a specified time period and serve as the foundation for other well-known technical indicators such as Bollinger Bands, Envelopes, Average Directional Movement Index (ADX), and MACD.
It is a completely customizable indicator, which means that an investor can choose any time period for calculating an average, with the most common time periods being 15, 20, 30, 50, 100, and 200 days.
Moving Averages of Various Types
Average of Simple Moving Average (SMA)
As the name implies, this is the simplest form of moving average, as it simply divides the average price of an asset by the number of time periods in the range by adding and then dividing a set of numbers by the number of prices in the set.
The SMA is calculated using the following formula:
A1 + A2 + … + An
S M A = ––––––––––––––––––––––
n
where:
a = Average in period n
n = Number of time periods
Moving Average Exponential (EMA)
This type of moving average places a higher premium on recent data points and is used to generate buy and sell signals based on crossovers and divergences from the historical average.
The EMA is calculated using the following formula:
E M At equals [Vt x (s / 1 + d)] x[1 – (s / 1 + d)] + E M Ay
where:
E M At = EMA in the present.
Vt = Today’s value
EMAy is an abbreviation for EMA yesterday.
Smoothing = s
d =Days
Moving Average with Weights (WMA)
This moving average indicator gives more weight to recent data points, as they are more relevant than data points from the distant past. When using WMA, the sum of the weightings should equal one (or 100 percent ).
The following formula is used to calculate the WMA:
Price1 x n + Price2 x (n – 1)+ … Pricen
W M A = –––––––––––––––––––––––––––––––––––
n x (n + 1)
————————
2
where:
n = Time period
Moving Average Smoothed (SMMA)
The purpose of this type of moving average is to reduce noise, not lag, and it is compared to the SMA indicator. The SMMA considers all prices and employs a longer lookback period. Price fluctuations are eliminated because the indicator eliminates noise and plots the prevailing trend, but historical prices remain in the calculation. This indicator is frequently used to confirm trends and establish support and resistance zones.
SMA vs. EMA comparison
When comparing the two primary moving average types, the primary distinction between SMA and EMA is that the latter moves at a much faster rate.
This is because the EMA places a higher premium on recent price action points, which means that when the direction of the price changes, it is able to recognize the change much sooner than the SMA, resulting in a faster turn when the price turns.
Regardless of the distinctions outlined above, moving averages are a simple yet effective tool in traders’ arsenals, as they enable them to visualize both where price has been and where it may be moving next.
How to Make the Most of Moving Averages
When day trading with moving averages, it is critical to keep in mind that the longer the time period, the greater the lag. For instance, a 100-day moving average will have a much greater lag than a 10-day moving average because it includes prices from the previous 100 days.
Additionally, moving averages calculated over a longer period of time incorporate more widely-used reference points, such as the 50-day and 200-day moving averages, which many investors regard as critical trading signals.
As a result, EMA is considered more accurate than SMA, as it accounts for the varying importance of the numbers in a recent data set. The EMA is a weighted average calculation that is frequently preferred by traders due to its increased responsiveness to price changes.
Concluding Remarks
While moving averages are simple to use, they are an effective tool for filtering out random fluctuations and smoothing out price action.
By developing a thorough understanding of moving averages and how they work, market participants can leverage this technical analysis tool to their advantage, identifying trends and price momentum with the end goal of increasing their return on investment.
