# Moving Average

## Key Takeaways

1. A moving average (MA) can be used as a technical indicator to represent the prices of shares and stocks by eliminating or smoothening the short term effect on the stock price.
2. There are two types of moving average. They are Simple Moving Average and Exponential Moving Average.

Moving average or MA is an indicator in technical analysis, which smoothes out the spiked chart of share prices to reveal underlying trends by plotting the average of past share prices over a specific period of time.

The most common moving average in use is the simple moving average or SMA, which takes the simple average of past prices for a given period.

The other is the exponential moving average (EMA). While SMA gives equal weightage to all the past days’ prices in the period taken for averaging, EMA gives more weightage to more recent prices.

Example

The chart shows a 20-days SMAs of an imaginary share. It shows the average prices over the past 20 days for each price point on the chart. The longer the lag (time is taken), the smoother the MA will be.

About Moving Average

A moving average (MA) can be used as a technical indicator to represent the prices of shares and stocks by eliminating or smoothening the short term effect on the stock price.

In the short term, the prices of the stock may fluctuate a lot, which may cause the graph to look spiky, and this can hardly result in decision making. In order to eliminate the short term trends effect, we use this method.

Moving average is of two types

1. Simple moving average

2. Exponential moving average

Simple moving average: –

In this method, we calculate the simple arithmetic mean of the values of a certain period to predict the value for the next period. The formula used here for calculating the moving average is

SMA = (V1 + V2 ……+ Vn) ÷ N

Where

V = represents the value on a day

N= period for calculating the average

For example, we have the data of the last 30 days of the closing price, and we need to determine the price for the next day then we can take the sum of the 30 days value of the closing price and divide it by 30 to get the prediction of the next day.

Value for 31st day = [(Day 1 + Day 2 + Day 3 + … + Day 29 + Day 30)/30]

But SMA has certain drawbacks that it doesn’t consider the weightage of the most recent data i.e., all data points are given the same amount of weightage, which may lead to a huge difference in the predicted value and the actual value to overcome this problem we use the Exponential method.

Exponential moving average: –

The exponential moving average is used to calculate the value one the next day by providing the weightage to the most recent days, thus eliminating the drawback faced in the simple moving average.

EMAt = [VT × s ÷ (1+d)] + EMAy × [1− s ÷ (1+d)]

Where:

EMAt=EMA today

VT=Value today

EMAy=EMA yesterday

s=smoothing (given by [2 ÷ (selected time period + 1)])

d=number of days

The exponential moving average is used to create indicators like moving average convergence and divergence and percentage price oscillator. Moving averages are very useful and intuitive when employed properly for trading.

## Limitations of moving averages

It is not clear that we should emphasize more on the most recent days in the time period or the previous days. Many believe that new data reflects the current trends, but one cannot be sure of the next trend.