The Moving Average is an indicator widely used in graphical analysis. It measures the average value of the price and its representation within the chart is usually shown by a line with the color of your preference set on the platform. It moves whenever the market starts a new movement.
With it you can identify bullish, bearish, and lateralizing trends on the chart. There are important differences between the Exponential Moving Average (EMA) and the Simple Moving Average (SMA).

What Is the Moving Average?

The Moving Average is an indicator that facilitates the general understanding of the data present in the chart, with a period-based calculation. It creates a line that indicates the trend of the analyzed asset chart, considering that the greater the number of periods used, the greater the analyzed time.

For example: An 200-average indicates longer periods on the chart and an 20-average will show shorter periods. In addition, Moving Averages help you filter out noises from the shorter-time charts that are characteristic of the fast oscillations on the market.

It is possible to observe that a moving average of 20 periods will follow the chart closely and that the crossing of the averages with the current prices of the chart may mean some trend reversals in the chart for the short or long term.

Moving Averages are considered lagging indicators, as they only show changes that have already happened in the graph and therefore need to be combined with other indicators to form an analysis.

Main Types of Moving Averages

Moving Averages are divided into:

Arithmetic or Simple Moving Average (SMA)

The Arithmetic Moving Average shows the average price of an asset using a given number of periods.

Simple Moving Average is one of the oldest indicators. It shows the simple trend of price through its average calculation. It follows the movement of the graphic homogeneously. The shorter the period used to calculate the Simple Moving Average, the closer to the current price the result will be. In return, it becomes more volatile and affected by price changes.

The equation that is used for this indicator is:

SMA = Sum of Closing Prices ÷ Number of days
Being CP, the Closing Prices, we have as an example a moving average of 5 periods:
SMA = {CP1 + CP2 + CP3 + CP4 + CP5} ÷ 5
Let’s move on to another example to simplify understanding:
Let’s use the 5-period Moving Average to set the average price in daily periods, and analyze price evolution on three different days. Consider daily closing as: 110,120,130,140,150,160 and 170.

• First day: (110 + 120 + 130 + 140 + 150) ÷ 5 = 130
• Second day: (120 + 130 + 140 + 150 + 160) ÷ 5 = 140
• Third day: (130 + 140 + 150 + 160 + 170) ÷ 5 = 150

Now observe that on the first day the SMA used the first 5 days in its calculation.

As the name says, this averaging moves over time. For this, old data is deleted as new data becomes available. During the second day, it removes the first value (110) and adds the new value of the subsequent day (160).

On the third day, it continues to remove the first number from the calculation (120) and adds a new recent value (170).

With this, it is possible to note that prices increase over time, from 110 to 170, over the 7 days and that there is an uptrend forming in this period.

Exponential Moving Average (EMA)

Based on the last example using Arithmetic Moving Average, it is simpler to understand EMA.

The EMA is similar to SMA, but the calculation uses other factors. For example, in this Moving Average, the most recent closing prices are taken into account, while the SMA has a lower weight on the price, the EMA will receive a greater influence, considering that it infers a greater importance on the most recent prices. Therefore, the EMA is a faster Moving Average that follows the price more closely. EMA is more sensitive to more recent price fluctuations and trend reversals, even in longer periods of time.

It is calculated by applying a percentage of the current closing price to the previous moving average. This percentage is defined by the equation:

Where, P= period defined for your moving average.

As an example, in a 50-day EMA, we obtain the 3.9% exponential average (2/50+1 = 0.039). This means that the most recent day will be weighted 3.9% of the value of the EMA. For a 50-day SMA, each day has a 2% equal weight. After that, we used this multiplier together with the EMA of the previous period to find the current EMA with the following equation:
EMA: {Closing Price - EMA (previous day)} x multiplier + EMA (previous day).

Weighted Moving Average (WMA)

The presence of this pattern in intraday charts is not as common and may not be as strong as in daily charts. Since the discovery of the cup and handle pattern there has been an improvement of the software bringing an ease of finding this pattern within the trades, as in a 4-hour chart for example. Typically, when this pattern is confirmed on an intraday chart and/or over a different chart time along with the volume that always accompanies it, you may be looking at a great investment opportunity.

Inverted Cup and Handle Pattern

Unlike the Exponential Moving Average, the Weighted Moving Average (WMA) is a degree of importance to a recent data set relative to previous data, this can be done by multiplying each candle by a weighting factor. Thus, a more recent data set collected represents a larger part of the total value of the WMA.
The weighting factor used in the calculation is determined by the period read by WMA. For example, in a 5-period WMA, the weighting factor would be the decreasing sequence of 5. Have a look at the following example:

Considering

• P1= most recent candle
• P2= previous candle
• And so on.

Crossing

The Crossing of Moving Averages is a strategy that has gained prominence in the trading of stocks and cryptocurrencies. It is used only as a basis for analysis, since it does not infer much information in the average prices. It consists of a deeper analysis of trades at the moment when the short-term moving average crosses the long-term moving average. This convergence of the long-term trend with the short-term trend, followed by its inversion, may signal a trend reversal. Depending on which moving average crosses the other above or below it is possible to predict a bearish or bullish trend. In most cases investors use the Exponential and Simple Moving Average in this strategy, with SMA in a longer period of time.

Conclusion

The Moving Average is an analysis of price behavior over time. By changing the amount of time and the importance of the most current price we can have different patterns of Moving Averages. The Moving Average can give us some important information on the chart, such as trend continuity and reversal, trend acceleration and deceleration, support and resistance areas, and even regions with higher trading noise. However, they depend on other indicators to form an analysis, as they display a calculation of past movements. You can use countless periods and test strategies with different indicators by modifying the Averages to better study the chart. Through this analysis it is possible to find input strategies and understand which ones are best suited to you.