Moving average is one of the most common indicators used by traders. It is an easy-to-use statistical tool primarily used for forecasting trends.

**Let us understand the basic definition of moving average.**

Moving average is an average of any subset of numbers. In trading, it is an average of closing prices within a time frame and is used for predicting future trends.

Because the moving average is based on past prices, it is a trend-following or lagging indicator. Further, what makes it more dynamic is the customization it offers.

Any time period (such as 15, 20, 30, 50 days) can be chosen by the trader while calculating the moving average. Sensitivity to price changes can be regulated by changing the time period. If the period is short, there will be more sensitivity to price change, and vice versa.

An intraday trader prefers a shorter-term moving average, whereas swing traders prefer longer-term moving averages.

**Trend analysis Using Moving Averages**

A rising moving average shows that the stock is in uptrend, whereas a declining moving average confirms a downtrend. Further, traders use two different moving averages to decide whether there is upward momentum or downward momentum in the stock price.

When a short-term moving average crosses above a long-term moving average, a bullish crossover forms (known as golden cross), which confirms that there is an upward momentum.

Similarly, if a short-term moving average crosses below a long-term moving average, then a bearish crossover is created (known as death cross), which confirms downward momentum in the stock.

**Types of Moving Averages:**

There are two types of moving averages: Simple moving average and exponential moving average.

**A)** **Simple Moving Average**

A simple moving average or SMA is an arithmetic moving average calculated by adding the recent prices and dividing the summation by the number of time periods in the calculated average.

Let us understand SMA with the help of an example:

The table above shows the closing price of a stock for 7 days. While calculating the SMA, the first 5 days’ values are considered. Here, the SMA comes out to be 7. Similarly, while calculating the next SMA, the Day 1 value is excluded, and the Day 6 value is considered to calculate the SMA value. Finally, the Day 3 value is excluded and the Day 7 value is taken to calculate the SMA.

**Exponential Moving Average**

Exponential Moving Average or EMA gives more weight to the most recent price data, which is considered more relevant than older data.

There are three simple steps that are followed in calculating EMA:

**1.** First, the SMA is calculated. Suppose you want to use 5 days as the number of observations for the EMA. Then, you must wait until the 5th day to arrive at the SMA. On the 6th day, you can then use the SMA from the previous day as the first EMA for yesterday.

**II.** After this, the multiplier (k) for weighing the EMA is determined.

Multiplier (k): [2 ÷ (number of observations + 1)]. Here, the number of observations = total time period. Taking the previously discussed example, number of observations = 5. Therefore, the multiplier in this case is k = 2/ (5+1) = 0.33.

**III.** Finally, the current EMA is calculated.

EMA = Closing price x multiplier + EMA (previous day) x (1 – multiplier)

Generally, 12-day and 26-day EMAs are used to identify short-term trends, whereas 50-day and 200-day EMAs are used to identify long-term trends.

Sensitivity to recent price point changes is more in EMA compared to SMA, making it more responsive to the latest price changes. We can observe how quickly EMA responds to price changes compared to SMA from the below graph.

This feature of EMA makes the results more timely and accurate, thus explaining why many traders prefer to use this indicator for trading.

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