SIMPLE MOVING AVERAGE
A simple moving average is derived by calculating the average (mean) price of a security over a specified number of periods. Simple Moving Averages can be calculated by considering either the open, high, low or close data points for the security in question. But the predominant method is to compute considering the close data point or the closing price. For example: a 7-day simple moving average is calculated by adding the closing prices for the last 7 days and dividing the total by 7.
For eg. 8 + 9 + 10 + 11 +12 +13 + 14 = 77
Divide this by 7 will give the SMA = 77 / 7 = 11 for the 7 data points.
The calculation is repeated for each price bar on the technical charts. The averages derived then joined to form a smooth curving line which is called the moving average line. In the above example, if the next closing price in the average is 15, then this new period would be added and the oldest day, ie. The first one which is 8, would be dropped. The new 7-day simple moving average would now be calculated as follows:
9 + 10 + 11 +12 +13 + 14 + 15 = 84
Divide this by 7 will give the SMA = 84 / 7 = 12 for the 7 data points.
So at any point of time the 7 day SMA would reflect the average for the last 7 days only …as new days data gets added the oldest data gets dropped out and hence reflecting the last 7 days statistics for the 7 day SMA for the particular day.
Simple Moving averages are called as lagging indicators and hence work well only when the prices are trending. Otherwise they give misleading signals. The practice normally used by analysts and chartists is to follow the 10 day SMA to 30 day SMA for predicting the short term trend. The most reliable method often followed is whenever the current price of the stock crosses the 200 day SMA it is a strong buy signal and if the price of the stock drops below the 200 day SMA it is a strong sell signal.
EXPONENTIAL MOVING AVERAGE (EMA)
In order to reduce the lag in simple moving averages, analysts often use exponential moving averages (also called exponentially weighted moving averages) which puts more weight on the recent data or the recent prices as compared to the old data or prices. The specified period of the moving average decides the weightage applied to the most recent price. The more short the EMAs period and the more weight that will be applied to the most recent price. To make it simple and easy to understand considering a 10-period exponential moving average weighs the most recent price 18.18% while a 20-period EMA weighs the most recent price 9.52%. Calculation of EMA is a little complex compared to the SMA. The important thing to keep in mind is that the exponential moving average puts more weight on recent prices. Obviously, it will react quicker to recent price changes than a simple moving average. The formula is
EMA(current) = ( (Price(current) - EMA(prev) ) x Multiplier) + EMA(prev)
For a percentage-based EMA, "Multiplier" is equal to the EMA's specified percentage.
For a period-based EMA, "Multiplier" is equal to 2 / (1 + N) where N is the specified number of periods.
For example, a 10-period EMA's Multiplier is calculated like this:
This shows that a 10-period EMA is equivalent to an 18.18% EMA.
WHICH ONE TO USE SMA or EMA ?
EMA due to its more sensitivity to recent price movements is often preferred by most technical analysts for predicting short term trends. Similarly SMA is often preferred by most technical analysts for predicting medium to long term trends of a security.
Since sensitivity can bring in often false or misleading signals this subject has been debatable always. Since Moving Averages is a very helpful tool it should be used in conjunction with other indicators as well. The best strategy would be to use these averages and experiment by self on live data of the market and conclude which suits you the best.