Calculate a weighted moving average that emphasises recent periods.
Linear weighting gives the most recent period the largest influence, which reduces lag compared with a simple moving average. The effective lag is roughly a third of the window rather than half. Weighted averages respond faster to genuine turning points but also to noise, which is the standard trade-off in smoothing.
Weighted Moving Average
WMA = Σ(value × weight) ÷ Σweight, with linearly declining weights
WMA = Σ(value × weight) ÷ Σweight, with linearly declining weights Linear weighting gives the most recent period the largest influence, which reduces lag compared with a simple moving average. The effective lag is roughly a third of the window rather than half.
Weighted averages respond faster to genuine turning points but also to noise, which is the standard trade-off in smoothing.
This calculator takes 4 inputs: Most recent period, Previous period, Two periods ago, Three periods ago. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.