A moving average is referred as such because it is recalculated at each consecutive point in time. Moving averages are used in technical analysis. The effect is to produce a line that smooths out fluctuations in the original data.
 Types of Moving Averages
 Simple moving average (SMA)
The unweighted mean of the previous n data points in the time series. For example, a 10-day simple moving average closing price is the mean of the previous 10 days' closing prices. The larger the value of n, the greater the smoothing effect and the more the MA line is displaced from the origianl data.
A moving average is a cross over system designed to capture trends soon after they develop. It is based on the crossoverof two or more historical moving averages. The underlying logic is that one of the moving averages is more responsiveto price changes than the others, signaling a shift in the trend when it crosses the longer-term responsive moving average(s).
 Weighted moving average (WMA)
The weighted mean of the previous n data points in the time series. The weighting is generally (but not necessarily always) linear. That means a relative weight of 1 is assigned to time period t, with each previous period's value assigned a lower weight on down to a relative weight of 1/n assigned to time period t-n. The WMA is more responsive to recent movements than the SMA.
 Exponential moving average (EMA)
An exponentially weighted mean of previous data points. The parameter of an EWMA can be expressed as a proportional percentage. For example, a 10% EMA has each time period assigned a weight that is 90% of the weight assigned to the next more recent time period.