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# Moving Average Indicators ## Moving Averages

One of the first statistical tools that we learned in school was averages. Averages of marks, height, or weight of the students in the class were given as examples for us to understand the concept. Little did we know then that it is the same average that is being widely used by traders worldwide.

Traders use a modification of the average called as Moving Average. In its calculation, the latest value is taken under consideration and the oldest one is removed from the calculation.

Theoretically speaking, a moving average is a statistical calculation that helps to create a series of averages of different subsets of the full data set.

So a 10 period moving average will have a subset of 10 periods, which can be days or minutes, or hours, depending on the timeframe selected by the trader.

The advantage of doing this is that the moving average smoothens out the short-term fluctuations in the data. The holistic picture that it portrays clears all the noise and helps in understanding the trend in the underlying asset.

## Calculation of moving averages

 Day Closing Price 5-Day Moving Average 1st 82 – 2nd 84 – 3rd 85 – 4th 80 – 5th 83 82.8 6th 74 81.2 7th 75 79.4 8th 73 77 9th 72 75.4 10th 74 73.6 11th 75 73.8 12th 76 74 13th 74 74.2 14th 76 75 15th 78 75.8 16th 77 76.2 17th 79 76.8 18th 77 77.4 19th 80 78.2 20th 79 78.4

The moving average was calculated by taking the value of the latest entry and removing the oldest one. Note the Moving Average of the 5th day is 82.8 which is the average of the first five days. On the sixth day, when the price fell sharply lower from 83 to 74, the moving average moved from 82.8 to 81.2. While considering the moving average the data of the 6th day was taken while that of the 1st day was removed. This process is repeated throughout the data series.

To get a graphical view of the data series and moving averages, look at the chart below. The power and utility of the moving average are demonstrated in the example above. The blue line represents the data and the red is the five period moving average. Note the spikey movement of the data and the smooth movement of the moving average.

The moving average moved downward when the data was in a decreasing trend while it moved upward when data started moving higher.

In the above case, we have taken a very simple example considering only the closing price. Traders normally use a bar or a candlestick chart that has four data points – Open, High, Low, and Close. While the trader can select which four data points, they want their moving average to be constructed, most traders prefer the moving average based on closing prices. Charting software also uses the closing price as the default value for calculating moving averages.

## Types of Moving Averages

There are six types of moving averages that are in use.

1. Simple Moving Average
2. Exponential Moving Average
3. Weighted Moving Average
4. Double exponential moving average (DEMA)
5. The triple exponential moving average (TEMA)
6. Linear Regression or least square moving averages.

We shall consider the two most popular moving averages – Simple Moving Average (SMA) and Exponential Moving Average (EMA) for further explanation. The chart above shows a 20 period simple moving average and a 20 period exponential moving average.

Let’s now closely look at the two moving averages.

## Simple moving average

A simple moving average uses the calculation that we have described earlier. A 20 period simple moving average that is shown in the chart above calculates the moving average over a 20 period.

The chart shows Bank Nifty on a daily time frame, but the moving average can be calculated using the same calculations on any time frame.

For the mathematically inclined, here is the formula for the calculation of a simple moving average.

SMA20 = (A1+A2+A3+….+A20)/20

## Exponential Moving Average (EMA)

While simple moving averages use a simple average calculation to determine its value, exponential moving averages assign weight to recent data. This is the reason that exponential moving averages follow the price closely as compared to simple moving averages as seen in the Bank Nifty chart above.

Calculation of exponential moving average is slightly more complex.

For the calculation g the EMA we use a multiplier in order to add weight to the recent data.

EMA is calculated using the following formula:

EMA = (K x (C – P)) + P

Where:

C = Current Price

P = Previous periods EMA (A SMA is used for the first periods calculations)

K = Multiplier

Multiplier = 2/(Period+1)

For a 20 period EMA the Multiplier would be = 2/(20+1) = 2/21 = 0.0952

For a 5 period EMA the Multiplier would be = 2/(5+1) = 2/6 = 0.3333

As the period is reduced the multiplier value is increased.

Knowing the value of the multiplier we can calculate the EMA by substituting it in the formula:

EMA = Price X Multiplier + EMA (previous day) X (1-Multiplier)

## How to use moving averages

Moving averages are one of the most versatile tools. They can be used in isolation or in combination with more than one moving average.

One of the most popular moving averages used is the 200 period moving average.

The chart below shows the 200 period moving average on Nifty over a long term period. Whenever the index is above the 200 periods moving average, the market is considered to be bullish and when it goes below the 200 periods moving average, it is bearish.

Note how early the market gave a bearish signal during the Pandemic.

Since the 200 period moving average is widely followed, the market respects it and takes support around the average. Market tests the 200 moving average and moves above or below it.

The Golden Cross and the Death Cross are terms that are used by traders using moving averages of 200 periods and 50 periods.

In a Golden Cross the 50 period moving average cuts the 200 period moving average from below. In such a scenario the market is considered to be bullish as seen in the chart below. The death cross is when the 50 period moving average cuts the 200 period moving average from the top. This is considered a bearish phase by traders.

Traders use moving averages in a similar fashion. Either a crossover of moving averages or a test of moving averages is taken as low-risk entry points.

Various values of moving averages are used to test and trade. Similarly, the number of moving averages used by traders also changes from 2 to much higher levels.

The chart below shows a Rainbow indicator which is constructed using moving averages. When the price clears all the moving averages it is considered to be bullish and when it falls below all moving averages it is considered to be bearish. ## Drawback

While moving averages have a number of advantages, it comes with their own set of drawback. Its biggest drawback is that it is a lag indicator, which means it reacts only after the price has covered a lot of distance.

The second drawback is it gives a number of false signals. Though in the long run, a trend-following trader will benefit from using a moving average, before that it will test his patience by giving a number of false signals and increase his losses.

## Conclusion

Moving averages are a simple and effective tool that finds its place in the arsenal of most traders. It is used as a trend indicator as well as a moving support resistance line.

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