Calculate an exponential moving average and its smoothing factor.
The exponential moving average never fully discards old data; weights decay geometrically instead. That gives a shorter effective lag than a simple average of the same nominal length. Because the EMA is recursive it needs only the previous value and the current observation, which makes it cheap to maintain on streaming data.
Exponential Moving Average
EMA = current × α + previous EMA × (1 − α), with α = 2 ÷ (n + 1)
EMA = current × α + previous EMA × (1 − α), with α = 2 ÷ (n + 1) The exponential moving average never fully discards old data; weights decay geometrically instead. That gives a shorter effective lag than a simple average of the same nominal length.
Because the EMA is recursive it needs only the previous value and the current observation, which makes it cheap to maintain on streaming data.
This calculator takes 3 inputs: Current period value, Previous EMA, EMA period. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.