Simple Vs. Exponential Moving Averages
the moving average is a tool commonly used by traders and technical analysts to analyze the price movement of securities. the moving average is simply an average of series of data points over a given period of time. traders use moving averages to smooth out fluctuating data in order to identify overall trends and cycles. there are two types of moving averages that are most commonly used by traders, the simple moving average, sma, and the exponential moving average, ema. the simple moving average is the mean of the data points. for example, if you are using a 20 day moving average on stocks, the price for each of the past 20 days will be added together and divided by 20 to generate the moving average. as new price data is added each day, the 20 day moving average shifts forward, always using the latest 20 available data points. each data point is weighted equally in the simple moving average regardless of whether it happened yesterday or 20 days ago. similarly, an exponential moving average will also take an average of data points of your given period of time, like the simple moving average. however, the weighting of each data point is not equal. more weight is given to the most recent data and weighting decreases as you go ? back in time. in other words, the exponential moving average treats recent data as more relevant and more important compared to historical data. in investing, traders are always looking for signals to buy or sell. by weighting recent data more heavily, exponential moving averages can give traders clear trend signals faster than the simple moving average. however, this could also increase the number of false signals. for this reason, many traders use an exponential moving average in combination with the simple moving average.