A weighted moving average (WMA) is similar to a simple moving average except that
the prices are weighted so that recent price data is given more weight than older
price data. This reduces the lag seen in simple moving averages (which represents
all price data equally), hence WMAs react more quickly to price changes.
WMAs are calculated by adding all the closing prices from a specified period multiplied
by weighting factors and dividing by the sum of the weighting factors. Within the
Bourse, a linear WMA is used. So, for example, a 20-day WMA gives 20 times more
weight to the most recent price than to the price 20 days ago.
A linear WMA differs from an exponentially weighted moving average in that there
is less contrast between the weighting of earlier and more recent prices. Though
the linear WMA is more sensitive to trend changes than the simple moving average,
it is less sensitive than the exponential moving average. During "flat"
or "non-trending" markets the differences among the different moving averages
become negligible.
WMAs are lagging indicators. They are used to emphasise the direction of a trend
and to smooth out price and volume fluctuations ("noise") that can confuse
interpretation.