What are Exponential Moving Averages?
An exponential or exponentially weighted moving average places more weight on recent prices and each price value gets a smaller weight as we move back in the series chronologically. The weight of each data point decrease exponentially.
The reason behind is that more recent prices are considered to be more important than the older prices. This is in contrast simple moving average, which places equal weights on daily prices. For example, a 200-day moving average which is over 6 months old could be less relevant to current market conditions.
Straightforward rules are used for all the moving average strategies. Each test differs only by the type of moving average used i.e. simple, weighted or exponential.
- Long entry: when the security’s current price crosses over its moving average. It means that the investor’s current expectations are higher than their average expectation and they are becoming increasingly bullish on it.
- Short entry: when the security’s current price crosses under its moving average. It means that the investor’s current expectations are below its average expectations and this leads to a bearish trend on the security.
Chart: 20-period, 50-period, and 200-period exponential moving average of the closing price of Google (GOOG). Timeframe: 1-day bars, so 20-period = 20 days
The computation of exponential moving average is shown below with an example:
For example, to calculate a 9% exponential moving average of a particular security, we will first take today’s closing price and multiply it by 9% and then add this product to the value of yesterday’s moving multiplied by 91%. (100% - 9% = 91%)
The percentage figures of exponential weighted moving average can be converted into an approximate number of days.
For example a 9% moving average is equal to a 21.2 time period exponential moving average.
The formula for converting exponential percentages to time period is:
The formula for converting time periods to exponential average is: